research article symbolic solution to complete ordinary...
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Hindawi Publishing CorporationJournal of Applied MathematicsVolume 2013 Article ID 518194 15 pageshttpdxdoiorg1011552013518194
Research ArticleSymbolic Solution to Complete Ordinary Differential Equationswith Constant Coefficients
Juan F Navarro and Antonio Peacuterez-Carrioacute
Department of Mathematics University of Alicante Carretera San Vicente del Raspeig sn 03690 San Vicente del RaspeigAlicante Spain
Correspondence should be addressed to Juan F Navarro jfnavarrouaes
Received 7 May 2013 Accepted 17 July 2013
Academic Editor Debasish Roy
Copyright copy 2013 J F Navarro and A Perez-Carrio This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited
The aim of this paper is to introduce a symbolic technique for the computation of the solution to a complete ordinary differentialequation with constant coefficients The symbolic solution is computed via the variation of parameters method and thusconstructed over the exponential matrix of the linear system associated with the homogeneous equation This matrix is alsosymbolically determined The accuracy of the symbolic solution is tested by comparing it with the exact solution of a test problem
1 Introduction
Perturbation theories for differential equations containinga small parameter 120598 are quite old The small perturbationtheory originated by Sir Isaac Newton has been highlydeveloped by many others and an extension of this theoryto the asymptotic expansion consisting of a power seriesexpansion in the small parameter was devised by Poincare[1] The main point is that for the most of the differentialequations it is not possible to obtain an exact solutionIn cases where equations contain a small parameter wecan consider it as a perturbation parameter to obtain anasymptotic expansion of the solution In practice the workinvolved in the application of this approach to compute thesolution to a differential equation cannot be performed byhand and algebraic processors result in being a very usefultool
As explained inHenrard [2] the first symbolic processorswere developed toworkwith Poisson series that ismultivari-ate Fourier series whose coefficients are multivariate Laurentseries
sum
1198941119894119899
sum
1198951119895119898
1198621198951119895119898
1198941119894119899
1199091198941
1sdot sdot sdot 119909
119894119899
119899
cossin(119895
11206011+ sdot sdot sdot + 119895
119898120601119898) (1)
where 1198621198951 1198951198981198941119894119899
isin R 1198941 119894
119899 119895
1 119895
119898isin Z and 119909
1 119909
119899
and 1206011 120601
119898are called polynomial and angular variables
respectively These processors were applied to problemsin nonlinear mechanics or nonlinear differential equationproblems in the field of celestial mechanics One of the firstapplications of these processorwas concernedwith the theoryof the Moon Delaunay invented his perturbation methodto treat it and spent 20 years doing algebraic manipulationsby hand to apply it to the problem Deprit et al [3 4]prolongated the solution of Delaunayrsquos work with the helpof a special purpose symbolic processor and Henrard [5]pushed to order 25 This solution was improved by iterationby Chapront-Touze [6] and planetary perturbations werealso introduced by Chapront-Touze [7] At present themost complete solution Ephemeride Lunaire Parisien (ELP)contains more than 50 000 periodic terms But the motion ofthe Moon is not the only application of algebraic processorsThere are many problems where the facilities provided byPoisson series processors can lead rather quickly to veryaccurate results As examples we would like to mentionplanetary theories the theory of the rotation of the Earth(see eg Navarro and Ferrandiz [8]) and artificial satellitetheories
In order to achieve better accuracies in the applications ofanalytical theories high orders of the approximate solutionmust be computed making necessary a continuous main-tenance and revision of the existing symbolic manipulationsystems as well as the development of new packages adapted
2 Journal of Applied Mathematics
to the peculiarities of the problem to be treated RecentlyNavarro [9 10] developed a symbolic processor to deal withthe solution to second order differential equations of the form
+ 1198861 + 119886
0119909 = 119906 (119905) + 120598119891 (119909 ) (2)
with initial conditions
119909 (0) = 1199090 (0) = 0
(3)
where 1198860 119886
1 119909
0 and
0isin R 119906(119905) is a quasipolynomial that
is an object of the form
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (4)
where 119899] isin N 120572] 120596] 120582] and 120583] isin R and 119891(119909 ) admits theexpansion
119891 (119909 ) =
119872
sum
120581=0
sum
0le]le120581
119891]120581minus]119909]120581minus] 119891]120581minus] isin R (5)
To face this problem the algebraic processor handles objectscalled quasipolynomials and it has resulted in being a usefultool in the computation of the solution to (2) by the appli-cation of the asymptotic expansion method A modificationof this processor has been employed to compute periodicsolutions in equations of type (2) via the Poincare-Lindstedtmethod in Navarro [9 10] To that end the idea is to expandboth the solution and the modified frequency with respectto the small parameter allowing to kill secular terms whichappear in the recursive scheme The elimination of secularterms is performed through a manipulation system whichworks with modified quasipolynomials that is quasipolyno-mials containing undetermined constants
119906 (119905) = sum
]ge0
1205911205901
1times sdot sdot sdot times 120591
120590119876
119876119905119899]119890120572]119905
times (120582] cos (120596]119905) + 120583] sin (120596]119905)) (6)
where 119899] isin N 120572] 120596] 120582] and 120583] isin R 120590] isin Z and 1205911 120591119876are real constants with unknown value
One year later Navarro [11] presented a symbolic com-putation package based on the object-oriented philosophyfor manipulating matrices whose elements lie on the set ofquasipolynomials of type (4) The kernel of the symbolicprocessor was developed in C++ defining a class for thisnew object as well as a set of functions that operate onthe data structure addition substraction differentiation andintegration with respect to 119905 substitution of an undeterminedcoefficient by a series and many others The goal of thisprocessor is to provide a tool to solve a perturbed 119899-orderdifferential equation of the class
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
0119909 = 119906 (119905) + 120598119891 (119909 119909
(119899minus1))
(7)
with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(8)
where 120598 is a small real parameter 1198860 119886
1 119886
119899minus1isin R 119906(119905) is
a quasipolynomial and 119891 is such that
119891 (119909 119909(119899minus1)) = sum
0le]1]119899le119872
119891]1]119899
119909]1sdot sdot sdot (119909
(119899minus1))
]119899
(9)
with119872 isin N ]1 ]
119899isin N and 119891]
1]119899
isin RAs a first step Navarro and Perez [12] have developed
a symbolic technique for the computation of the principalmatrix of the linear system associated with a homogeneousordinary differential equation with constant coefficients ofthe form
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 0 (10)
where 1198860 119886
1 119886
119899minus1isin R with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(11)
being 11990910 119909
1198990isin R This method provides a final
analytical solution which can be completely computed in asymbolic way
The second step in the construction of the solution to (7)is to obtain a symbolic procedure for computing the solutionto the nonhomogeneus equation
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
0119909 = 119906 (119905) (12)
where as above 119906(119905) is a quasipolynomialThis new symbolic package can be useful for research and
educational purposes in the field of differential equations ordynamical systems Nowadays there aremany open problemswhich requires massive symbolic computation as to cite oneexample the analytical theory of the resonant motion ofMercury We would like to stress that the aim of this work isto develop a symbolic tool not a numericmethod as numericsolutions cannot be used in perturbation methods for differ-ential equations However we have performed comparisonsbetween the symbolic solution with a numeric one just toshow the efficiency of the technique
In next section we summarize the scheme proposedin [12] to calculate the solution to (10) which is neededto express the solution to the complete problem (12) Thetechnique to construct this solution will be described inSection 3
2 Solution to the Homogeneous Problem
As mentioned Navarro and Perez [12] have proposed asymbolic method to compute the solution to (10)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 0 (13)
where 1198860 119886
1 119886
119899minus1isin R with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(14)
being 11990910 119909
1198990isin R This method provides a final
analytical solution which can be completely computed in asymbolic way
Journal of Applied Mathematics 3
21 Description of the Method With the aid of the substitu-tions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (15)
(10) is transformed into the system of differential equationsgiven by
(119905) = 119860119883 (119905) 119883 (0) = 1198830 (16)
where 119860 is the companion matrix
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
) 1198830= (
11990910
11990920
1199091198990
)
(17)
To compute the exponential of 119860 the matrix is splitted into119861 + 119862 where
119861 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
0 0 0 sdot sdot sdot 0
)
119862 = (
0 0 0 sdot sdot sdot 0
0 0 0 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
(18)
Then we use the approximation
119890119860asymp (119890
119861119898119890119862119898)
119898
(19)
with119898 isin NThis approach to obtain 119890119860 is of potential interestwhen the exponentials of matrices 119861 and 119862 can be efficientlycomputed and requires 119886
119899minus1to be nonequal to zero In our
case
119890119861119898=(
1198920 (119898) 1198921 (
119898) 1198922 (119898) sdot sdot sdot 119892119899minus1 (
119898)
0 1198920 (119898) 1198921 (
119898) sdot sdot sdot 119892119899minus2 (119898)
0 0 1198920 (119898) sdot sdot sdot 119892119899minus3 (
119898)
d
0 0 0 sdot sdot sdot 1198920 (119898)
)
119890119862119898= 119868 minus
1
119886119899minus1
(119890minus119886119899minus1
119898minus 1)119862
=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
120596012059611205962sdot sdot sdot 120596
119899minus1
)
(20)
being for any 119899 isin N
119892119899 (119898) =
1
119899119898119899 (21)
and for any 119894 = 0 119899 minus 2
120596119894=
119886119894
119886119899minus1
(119890minus119886119899minus1
119898minus 1) 120596
119899minus1= 119890
minus119886119899minus1
119898 (22)
As it is established in Moler and van Loan [13] for a generalsplitting 119860 = 119861 + 119862119898 can be determine from
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
2119898
[119861 119862] 119890119861+119862
(23)
Thus with 119860 being the companion matrix we get that
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
119898
1198901+119886119886 (24)
where 119886 = (1198860 119886
1 119886
119899minus1) Here
119909 = 1199091=10038161003816100381610038161199091
1003816100381610038161003816+ sdot sdot sdot +
1003816100381610038161003816119909119899
1003816100381610038161003816 (25)
for any 119909 = (1199091 119909
119899) isin R119899 and 119860 = max
1199091=1119860119909
1=
max](|1198861]| + sdot sdot sdot + |119886119899]|) for any matrix
119860 = (
1198861111988612sdot sdot sdot 119886
1119899
1198862111988622sdot sdot sdot 119886
2119899
d
11988611989911198861198992sdot sdot sdot 119886
119899119899
) (26)
22 Adaptation to a Symbolic Formalism Navarro and Perez[12 14] have proposed an adaptation of themethod describedabove in order to compute the matrix 119890119860119905 instead of 119890119860 If wedo so we obtain the principal matrix of (16) whose elementslie on the set of quasipolynomials and the symbolic processorresults in being suitable to work with those matrices Theapproach is to compute
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
(27)
taking into account that
119890119861119905119898= (
1198920 (119905 119898) 1198921 (
119905 119898) sdot sdot sdot 119892119899minus1 (119905 119898)
0 1198920 (119905 119898) sdot sdot sdot 119892119899minus2 (
119905 119898)
d
0 0 sdot sdot sdot 119892
0 (119905 119898)
)
119890119862119905119898=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
1205960 (119905) 1205961 (
119905) 1205962 (119905) sdot sdot sdot 120596119899minus1 (
119905)
)
(28)
being for any 119899 isin N
119892119899 (119905 119898) =
119905119899
119899119898119899 (29)
4 Journal of Applied Mathematics
and for any 119894 = 0 119899 minus 2
120596119894 (119905) =
119886119894
119886119899minus1
(119890minus119886119899minus1
119905119898minus 1) 120596
119899minus1 (119905) = 119890
minus119886119899minus1
119905119898
(30)
Thus 119890119860119905 is amatrix of quasipolynomials that can be com-pletely computed through the symbolic processor developedby Navarro [11] The procedure for the computation of theexponential matrix is substantially simplified by using thefollowing equation which avoids the symbolic multiplicationof 119890119861119905119898 and 119890119862119905119898
119890119861119905119898119890119862119905119898= 119890
119861119905119898+ 119867 (119905119898) (31)
where
119867(119905119898) =
1
119886119899minus1
119891 (119905 119898)(
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
119891 (119905 119898) = 119890minus119886119899minus1
119905119898minus 1
(32)
This relation can be obtained directly from themultiplicationof matrices 119890119861119905119898 and 119890119862119905119898 as given in (28)
23 Symbolic Expansion of the Exponential Matrix As it hasbeen stated in Section 22 the exponential matrix 119890119860119905 can besymbolically calculated through (27) and (31)
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
= (119890119861119905119898+ 119867 (119905119898))
119898
(33)
This expression can be calculated symbolically Let us express119867(119905119898) as
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898) (34)
with
120582 (119905 119898) =
1
119886119899minus1
119891 (119905 119898)
119869 (119905 119898) = (
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
(35)
Thus
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869 (119905 119898))
119898
119896
(36)
where (119860 119861)119898119896is the so-called noncommutative parenthesis
defined as
(119860 119861)119898
119896=
(119898
119896)
sum
119894=1
120590(119898119896)
prod
119895=1
(119860(1minus(minus1)
119895)2119861(1+(minus1)
119895)2)
119888119894119895
(37)
where 119860 and 119861 are two noncommutative 119899 times 119899 matrices119898 119896 119888
119894119895isin Z+cup 0
120590 (119898 119896) =
2119896 + 1 if 2119896 le 1198982 (119898 minus 119896 + 1) if 2119896 gt 119898
(38)
and 119888119894119895is determined by the following properties
(1) sum120590(119898119896)
119895=1119888119894119895= 119898 for all 119894 = 1 2 (119898119896 )
(2) sum[120590(119898119896)2]
119895=1119888119894(2119895)= 119898 minus 119896 for all 119894 = 1 2 (119898119896 ) with
[120590(119898 119896)2] being the entire part of 120590(119898 119896)2(3) 119888
1198942= 0 for all 119894 = 1 2 (119898119896 )
(4) if 119888119894119895= 0 and 119888
119894(119895+2)= 0 then 119888
119894(119895+1)= 0 for all 119894 =
1 2 (119898
119896 ) and 119895 = 1 2 120590(119898 119896) minus 2
In the following we summarize some expressions whichsimplify the way in which the matrix (119890119861119905119898 + 119867(119905119898))119898 issymbolically computed First let us introduce the followingmatrices
119878119899minus1 (119905 119898) = (1198860
1198861sdot sdot sdot 119886
119899minus1) 119865 (119905 119898)
119865 (119905 119898) =(
(
(
119905119899minus1
(119899 minus 1) 119905119899minus2119898
(119899 minus 1) (119899 minus 2) 119905119899minus3119898
2
(119899 minus 1)119905
0119898
119899minus1
)
)
)
(39)
Lemma 1 For any 119896 isin Z such that 119896 gt 1
(119890119861119905119898)
119896
=(
1198660119896 (119905 119898) 1198661119896 (
119905 119898) sdot sdot sdot 119866119899minus1119896 (119905 119898)
0 1198660119896 (119905 119898) sdot sdot sdot 119866119899minus2119896 (
119905 119898)
d
0 0 sdot sdot sdot 119866
0119896 (119905 119898)
)
(40)
with
119866]119896 (119905 119898) = 119896]119892] (119905 119898) (41)
for each ] = 0 119899 minus 1 where 119892](119905 119898) is given by (29)
Lemma 2 For any 119901 isin Z such that 119901 gt 1
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905 119898))
119901minus1
times 119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(42)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
Lemma 3 For any 119901 119896 isin Z such that 119901 119896 ge 1
(119890119861119905119898)
119896
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905))
119901minus1
times Ω119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(43)
Journal of Applied Mathematics 5
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39) and
Ω =(
(119896 + 1)119899minus1
0 sdot sdot sdot 0
0 (119896 + 1)119899minus2sdot sdot sdot 0
d
0 0 sdot sdot sdot 1
) (44)
Lemma 4 For any 119901 119896 isin Z such that 119901 119896 ge 1
119867119901(119905 119898) (119890
119861119905119898)
119896
= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
times (119878119899minus1 (119905))
119901minus1119865 (119905 119898)119860 (119905 119898)
(45)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
119860 (119905119898) = (1198600 (119905 119898) 1198601 (
119905 119898) sdot sdot sdot 119860119899minus1 (119905 119898))
119860120583 (119905 119898) =
120583
sum
]=0
119886]119896120583minus]119892120583minus]
(46)
for any 120583 = 0 119899 minus 1 and 119892] is given by (29)
For the sake of simplicity we have omitted the depen-dence on119898 and 119905 of 119892]
3 Solution to the Nonhomogeneous Problem
The general solution to a nonhomogeneous linear differentialequation of order 119899 can be expressed as the sum of the generalsolution to the corresponding homogeneous linear differen-tial equation and any solution to the complete equation Thesymbolic manipulation system calculates the solution to anonperturbed differential equation with initial conditions ofthe form (12)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 119906 (119905) (47)
with initial conditions
119909 (0) = 11990910 119909
(119899minus1)(0) = 1199091198990
(48)
where 1198860 119886
1 119886
119899minus1isin R 119909
10 119909
1198990isin R and
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (49)
being 119899] isin N and 120572] 120596] 120582] 120583] isin R With the aid of thesubstitutions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (50)
(12) is reduced to the system of differential equations given by
(119905) = 119860119883 (119905) + 119861 (119905) 119883 (0) = 1198830 (51)
where
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119861 (119905) = (
0
0
119906 (119905)
) 119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
)
1198830= (
11990910
11990920
1199091198990
)
(52)
The computation of the solution to the constant coeffi-cients linear part requires the calculation of the exponentialof the matrix 119860 Φ(119905) = 119890119860119905
119883 (119905) = Φ (119905)1198830+ Φ (119905) int
119905
0
exp (119860120591) 119861 (120591) 119889120591 (53)
31 Symbolic Expansion of the Solution In the following wegive a formula for the symbolic expansion of the solution tothe complete ordinary differential equation To that end letus express the noncommutative parenthesis (119890119861119905119898 119869(119905 119898))
119898
119896
as
(119890119861119905119898 119869(119905 119898))
119898
119896= (
119901(119898119896)
11990311
(119905) sdot sdot sdot 119901(119898119896)
1199031119899
(119905)
d
119901(119898119896)
1199031198991
(119905) sdot sdot sdot 119901(119898119896)
119903119899119899
(119905)
)
= (119901(119898119896)
119903119894119895
(119905))
119899
119894119895=1
= 119875 (119898 119896) (119905)
(54)
where each 119901(119898119896)
1199031119899
(119905) is a polynomial of degree 119903119894119895le 119898(119899 minus 1)
in the indeterminate 119905 with coefficients from R and119898 = 0Let us also express
120582119896(119905 119898) = (
1
119886119899minus1
(119890119886119899minus1
119905119898minus 1))
119896
=
119896
sum
]=0
120572]119890120573]119905 (55)
being
120572] = (1
119886119899minus1
)
119896
(
119896
]) (minus1)
]
120573] = minus119886119899minus1
119898
(119896 minus ])
(56)
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
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Differential EquationsInternational Journal of
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Mathematical PhysicsAdvances in
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OptimizationJournal of
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International Journal of
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Operations ResearchAdvances in
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
Discrete Dynamics in Nature and Society
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
2 Journal of Applied Mathematics
to the peculiarities of the problem to be treated RecentlyNavarro [9 10] developed a symbolic processor to deal withthe solution to second order differential equations of the form
+ 1198861 + 119886
0119909 = 119906 (119905) + 120598119891 (119909 ) (2)
with initial conditions
119909 (0) = 1199090 (0) = 0
(3)
where 1198860 119886
1 119909
0 and
0isin R 119906(119905) is a quasipolynomial that
is an object of the form
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (4)
where 119899] isin N 120572] 120596] 120582] and 120583] isin R and 119891(119909 ) admits theexpansion
119891 (119909 ) =
119872
sum
120581=0
sum
0le]le120581
119891]120581minus]119909]120581minus] 119891]120581minus] isin R (5)
To face this problem the algebraic processor handles objectscalled quasipolynomials and it has resulted in being a usefultool in the computation of the solution to (2) by the appli-cation of the asymptotic expansion method A modificationof this processor has been employed to compute periodicsolutions in equations of type (2) via the Poincare-Lindstedtmethod in Navarro [9 10] To that end the idea is to expandboth the solution and the modified frequency with respectto the small parameter allowing to kill secular terms whichappear in the recursive scheme The elimination of secularterms is performed through a manipulation system whichworks with modified quasipolynomials that is quasipolyno-mials containing undetermined constants
119906 (119905) = sum
]ge0
1205911205901
1times sdot sdot sdot times 120591
120590119876
119876119905119899]119890120572]119905
times (120582] cos (120596]119905) + 120583] sin (120596]119905)) (6)
where 119899] isin N 120572] 120596] 120582] and 120583] isin R 120590] isin Z and 1205911 120591119876are real constants with unknown value
One year later Navarro [11] presented a symbolic com-putation package based on the object-oriented philosophyfor manipulating matrices whose elements lie on the set ofquasipolynomials of type (4) The kernel of the symbolicprocessor was developed in C++ defining a class for thisnew object as well as a set of functions that operate onthe data structure addition substraction differentiation andintegration with respect to 119905 substitution of an undeterminedcoefficient by a series and many others The goal of thisprocessor is to provide a tool to solve a perturbed 119899-orderdifferential equation of the class
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
0119909 = 119906 (119905) + 120598119891 (119909 119909
(119899minus1))
(7)
with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(8)
where 120598 is a small real parameter 1198860 119886
1 119886
119899minus1isin R 119906(119905) is
a quasipolynomial and 119891 is such that
119891 (119909 119909(119899minus1)) = sum
0le]1]119899le119872
119891]1]119899
119909]1sdot sdot sdot (119909
(119899minus1))
]119899
(9)
with119872 isin N ]1 ]
119899isin N and 119891]
1]119899
isin RAs a first step Navarro and Perez [12] have developed
a symbolic technique for the computation of the principalmatrix of the linear system associated with a homogeneousordinary differential equation with constant coefficients ofthe form
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 0 (10)
where 1198860 119886
1 119886
119899minus1isin R with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(11)
being 11990910 119909
1198990isin R This method provides a final
analytical solution which can be completely computed in asymbolic way
The second step in the construction of the solution to (7)is to obtain a symbolic procedure for computing the solutionto the nonhomogeneus equation
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
0119909 = 119906 (119905) (12)
where as above 119906(119905) is a quasipolynomialThis new symbolic package can be useful for research and
educational purposes in the field of differential equations ordynamical systems Nowadays there aremany open problemswhich requires massive symbolic computation as to cite oneexample the analytical theory of the resonant motion ofMercury We would like to stress that the aim of this work isto develop a symbolic tool not a numericmethod as numericsolutions cannot be used in perturbation methods for differ-ential equations However we have performed comparisonsbetween the symbolic solution with a numeric one just toshow the efficiency of the technique
In next section we summarize the scheme proposedin [12] to calculate the solution to (10) which is neededto express the solution to the complete problem (12) Thetechnique to construct this solution will be described inSection 3
2 Solution to the Homogeneous Problem
As mentioned Navarro and Perez [12] have proposed asymbolic method to compute the solution to (10)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 0 (13)
where 1198860 119886
1 119886
119899minus1isin R with initial conditions
119909 (0) = 11990910 (0) = 11990920
119909(119899minus1)(0) = 1199091198990
(14)
being 11990910 119909
1198990isin R This method provides a final
analytical solution which can be completely computed in asymbolic way
Journal of Applied Mathematics 3
21 Description of the Method With the aid of the substitu-tions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (15)
(10) is transformed into the system of differential equationsgiven by
(119905) = 119860119883 (119905) 119883 (0) = 1198830 (16)
where 119860 is the companion matrix
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
) 1198830= (
11990910
11990920
1199091198990
)
(17)
To compute the exponential of 119860 the matrix is splitted into119861 + 119862 where
119861 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
0 0 0 sdot sdot sdot 0
)
119862 = (
0 0 0 sdot sdot sdot 0
0 0 0 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
(18)
Then we use the approximation
119890119860asymp (119890
119861119898119890119862119898)
119898
(19)
with119898 isin NThis approach to obtain 119890119860 is of potential interestwhen the exponentials of matrices 119861 and 119862 can be efficientlycomputed and requires 119886
119899minus1to be nonequal to zero In our
case
119890119861119898=(
1198920 (119898) 1198921 (
119898) 1198922 (119898) sdot sdot sdot 119892119899minus1 (
119898)
0 1198920 (119898) 1198921 (
119898) sdot sdot sdot 119892119899minus2 (119898)
0 0 1198920 (119898) sdot sdot sdot 119892119899minus3 (
119898)
d
0 0 0 sdot sdot sdot 1198920 (119898)
)
119890119862119898= 119868 minus
1
119886119899minus1
(119890minus119886119899minus1
119898minus 1)119862
=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
120596012059611205962sdot sdot sdot 120596
119899minus1
)
(20)
being for any 119899 isin N
119892119899 (119898) =
1
119899119898119899 (21)
and for any 119894 = 0 119899 minus 2
120596119894=
119886119894
119886119899minus1
(119890minus119886119899minus1
119898minus 1) 120596
119899minus1= 119890
minus119886119899minus1
119898 (22)
As it is established in Moler and van Loan [13] for a generalsplitting 119860 = 119861 + 119862119898 can be determine from
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
2119898
[119861 119862] 119890119861+119862
(23)
Thus with 119860 being the companion matrix we get that
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
119898
1198901+119886119886 (24)
where 119886 = (1198860 119886
1 119886
119899minus1) Here
119909 = 1199091=10038161003816100381610038161199091
1003816100381610038161003816+ sdot sdot sdot +
1003816100381610038161003816119909119899
1003816100381610038161003816 (25)
for any 119909 = (1199091 119909
119899) isin R119899 and 119860 = max
1199091=1119860119909
1=
max](|1198861]| + sdot sdot sdot + |119886119899]|) for any matrix
119860 = (
1198861111988612sdot sdot sdot 119886
1119899
1198862111988622sdot sdot sdot 119886
2119899
d
11988611989911198861198992sdot sdot sdot 119886
119899119899
) (26)
22 Adaptation to a Symbolic Formalism Navarro and Perez[12 14] have proposed an adaptation of themethod describedabove in order to compute the matrix 119890119860119905 instead of 119890119860 If wedo so we obtain the principal matrix of (16) whose elementslie on the set of quasipolynomials and the symbolic processorresults in being suitable to work with those matrices Theapproach is to compute
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
(27)
taking into account that
119890119861119905119898= (
1198920 (119905 119898) 1198921 (
119905 119898) sdot sdot sdot 119892119899minus1 (119905 119898)
0 1198920 (119905 119898) sdot sdot sdot 119892119899minus2 (
119905 119898)
d
0 0 sdot sdot sdot 119892
0 (119905 119898)
)
119890119862119905119898=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
1205960 (119905) 1205961 (
119905) 1205962 (119905) sdot sdot sdot 120596119899minus1 (
119905)
)
(28)
being for any 119899 isin N
119892119899 (119905 119898) =
119905119899
119899119898119899 (29)
4 Journal of Applied Mathematics
and for any 119894 = 0 119899 minus 2
120596119894 (119905) =
119886119894
119886119899minus1
(119890minus119886119899minus1
119905119898minus 1) 120596
119899minus1 (119905) = 119890
minus119886119899minus1
119905119898
(30)
Thus 119890119860119905 is amatrix of quasipolynomials that can be com-pletely computed through the symbolic processor developedby Navarro [11] The procedure for the computation of theexponential matrix is substantially simplified by using thefollowing equation which avoids the symbolic multiplicationof 119890119861119905119898 and 119890119862119905119898
119890119861119905119898119890119862119905119898= 119890
119861119905119898+ 119867 (119905119898) (31)
where
119867(119905119898) =
1
119886119899minus1
119891 (119905 119898)(
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
119891 (119905 119898) = 119890minus119886119899minus1
119905119898minus 1
(32)
This relation can be obtained directly from themultiplicationof matrices 119890119861119905119898 and 119890119862119905119898 as given in (28)
23 Symbolic Expansion of the Exponential Matrix As it hasbeen stated in Section 22 the exponential matrix 119890119860119905 can besymbolically calculated through (27) and (31)
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
= (119890119861119905119898+ 119867 (119905119898))
119898
(33)
This expression can be calculated symbolically Let us express119867(119905119898) as
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898) (34)
with
120582 (119905 119898) =
1
119886119899minus1
119891 (119905 119898)
119869 (119905 119898) = (
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
(35)
Thus
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869 (119905 119898))
119898
119896
(36)
where (119860 119861)119898119896is the so-called noncommutative parenthesis
defined as
(119860 119861)119898
119896=
(119898
119896)
sum
119894=1
120590(119898119896)
prod
119895=1
(119860(1minus(minus1)
119895)2119861(1+(minus1)
119895)2)
119888119894119895
(37)
where 119860 and 119861 are two noncommutative 119899 times 119899 matrices119898 119896 119888
119894119895isin Z+cup 0
120590 (119898 119896) =
2119896 + 1 if 2119896 le 1198982 (119898 minus 119896 + 1) if 2119896 gt 119898
(38)
and 119888119894119895is determined by the following properties
(1) sum120590(119898119896)
119895=1119888119894119895= 119898 for all 119894 = 1 2 (119898119896 )
(2) sum[120590(119898119896)2]
119895=1119888119894(2119895)= 119898 minus 119896 for all 119894 = 1 2 (119898119896 ) with
[120590(119898 119896)2] being the entire part of 120590(119898 119896)2(3) 119888
1198942= 0 for all 119894 = 1 2 (119898119896 )
(4) if 119888119894119895= 0 and 119888
119894(119895+2)= 0 then 119888
119894(119895+1)= 0 for all 119894 =
1 2 (119898
119896 ) and 119895 = 1 2 120590(119898 119896) minus 2
In the following we summarize some expressions whichsimplify the way in which the matrix (119890119861119905119898 + 119867(119905119898))119898 issymbolically computed First let us introduce the followingmatrices
119878119899minus1 (119905 119898) = (1198860
1198861sdot sdot sdot 119886
119899minus1) 119865 (119905 119898)
119865 (119905 119898) =(
(
(
119905119899minus1
(119899 minus 1) 119905119899minus2119898
(119899 minus 1) (119899 minus 2) 119905119899minus3119898
2
(119899 minus 1)119905
0119898
119899minus1
)
)
)
(39)
Lemma 1 For any 119896 isin Z such that 119896 gt 1
(119890119861119905119898)
119896
=(
1198660119896 (119905 119898) 1198661119896 (
119905 119898) sdot sdot sdot 119866119899minus1119896 (119905 119898)
0 1198660119896 (119905 119898) sdot sdot sdot 119866119899minus2119896 (
119905 119898)
d
0 0 sdot sdot sdot 119866
0119896 (119905 119898)
)
(40)
with
119866]119896 (119905 119898) = 119896]119892] (119905 119898) (41)
for each ] = 0 119899 minus 1 where 119892](119905 119898) is given by (29)
Lemma 2 For any 119901 isin Z such that 119901 gt 1
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905 119898))
119901minus1
times 119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(42)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
Lemma 3 For any 119901 119896 isin Z such that 119901 119896 ge 1
(119890119861119905119898)
119896
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905))
119901minus1
times Ω119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(43)
Journal of Applied Mathematics 5
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39) and
Ω =(
(119896 + 1)119899minus1
0 sdot sdot sdot 0
0 (119896 + 1)119899minus2sdot sdot sdot 0
d
0 0 sdot sdot sdot 1
) (44)
Lemma 4 For any 119901 119896 isin Z such that 119901 119896 ge 1
119867119901(119905 119898) (119890
119861119905119898)
119896
= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
times (119878119899minus1 (119905))
119901minus1119865 (119905 119898)119860 (119905 119898)
(45)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
119860 (119905119898) = (1198600 (119905 119898) 1198601 (
119905 119898) sdot sdot sdot 119860119899minus1 (119905 119898))
119860120583 (119905 119898) =
120583
sum
]=0
119886]119896120583minus]119892120583minus]
(46)
for any 120583 = 0 119899 minus 1 and 119892] is given by (29)
For the sake of simplicity we have omitted the depen-dence on119898 and 119905 of 119892]
3 Solution to the Nonhomogeneous Problem
The general solution to a nonhomogeneous linear differentialequation of order 119899 can be expressed as the sum of the generalsolution to the corresponding homogeneous linear differen-tial equation and any solution to the complete equation Thesymbolic manipulation system calculates the solution to anonperturbed differential equation with initial conditions ofthe form (12)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 119906 (119905) (47)
with initial conditions
119909 (0) = 11990910 119909
(119899minus1)(0) = 1199091198990
(48)
where 1198860 119886
1 119886
119899minus1isin R 119909
10 119909
1198990isin R and
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (49)
being 119899] isin N and 120572] 120596] 120582] 120583] isin R With the aid of thesubstitutions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (50)
(12) is reduced to the system of differential equations given by
(119905) = 119860119883 (119905) + 119861 (119905) 119883 (0) = 1198830 (51)
where
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119861 (119905) = (
0
0
119906 (119905)
) 119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
)
1198830= (
11990910
11990920
1199091198990
)
(52)
The computation of the solution to the constant coeffi-cients linear part requires the calculation of the exponentialof the matrix 119860 Φ(119905) = 119890119860119905
119883 (119905) = Φ (119905)1198830+ Φ (119905) int
119905
0
exp (119860120591) 119861 (120591) 119889120591 (53)
31 Symbolic Expansion of the Solution In the following wegive a formula for the symbolic expansion of the solution tothe complete ordinary differential equation To that end letus express the noncommutative parenthesis (119890119861119905119898 119869(119905 119898))
119898
119896
as
(119890119861119905119898 119869(119905 119898))
119898
119896= (
119901(119898119896)
11990311
(119905) sdot sdot sdot 119901(119898119896)
1199031119899
(119905)
d
119901(119898119896)
1199031198991
(119905) sdot sdot sdot 119901(119898119896)
119903119899119899
(119905)
)
= (119901(119898119896)
119903119894119895
(119905))
119899
119894119895=1
= 119875 (119898 119896) (119905)
(54)
where each 119901(119898119896)
1199031119899
(119905) is a polynomial of degree 119903119894119895le 119898(119899 minus 1)
in the indeterminate 119905 with coefficients from R and119898 = 0Let us also express
120582119896(119905 119898) = (
1
119886119899minus1
(119890119886119899minus1
119905119898minus 1))
119896
=
119896
sum
]=0
120572]119890120573]119905 (55)
being
120572] = (1
119886119899minus1
)
119896
(
119896
]) (minus1)
]
120573] = minus119886119899minus1
119898
(119896 minus ])
(56)
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
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Mathematical Problems in Engineering
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Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical PhysicsAdvances in
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
Journal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
Discrete Dynamics in Nature and Society
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Decision SciencesAdvances in
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 3
21 Description of the Method With the aid of the substitu-tions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (15)
(10) is transformed into the system of differential equationsgiven by
(119905) = 119860119883 (119905) 119883 (0) = 1198830 (16)
where 119860 is the companion matrix
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
) 1198830= (
11990910
11990920
1199091198990
)
(17)
To compute the exponential of 119860 the matrix is splitted into119861 + 119862 where
119861 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
0 0 0 sdot sdot sdot 0
)
119862 = (
0 0 0 sdot sdot sdot 0
0 0 0 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
(18)
Then we use the approximation
119890119860asymp (119890
119861119898119890119862119898)
119898
(19)
with119898 isin NThis approach to obtain 119890119860 is of potential interestwhen the exponentials of matrices 119861 and 119862 can be efficientlycomputed and requires 119886
119899minus1to be nonequal to zero In our
case
119890119861119898=(
1198920 (119898) 1198921 (
119898) 1198922 (119898) sdot sdot sdot 119892119899minus1 (
119898)
0 1198920 (119898) 1198921 (
119898) sdot sdot sdot 119892119899minus2 (119898)
0 0 1198920 (119898) sdot sdot sdot 119892119899minus3 (
119898)
d
0 0 0 sdot sdot sdot 1198920 (119898)
)
119890119862119898= 119868 minus
1
119886119899minus1
(119890minus119886119899minus1
119898minus 1)119862
=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
120596012059611205962sdot sdot sdot 120596
119899minus1
)
(20)
being for any 119899 isin N
119892119899 (119898) =
1
119899119898119899 (21)
and for any 119894 = 0 119899 minus 2
120596119894=
119886119894
119886119899minus1
(119890minus119886119899minus1
119898minus 1) 120596
119899minus1= 119890
minus119886119899minus1
119898 (22)
As it is established in Moler and van Loan [13] for a generalsplitting 119860 = 119861 + 119862119898 can be determine from
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
2119898
[119861 119862] 119890119861+119862
(23)
Thus with 119860 being the companion matrix we get that
100381710038171003817100381710038171003817
119890119860minus (119890
119861119898119890119862119898)
119898100381710038171003817100381710038171003817
le
1
119898
1198901+119886119886 (24)
where 119886 = (1198860 119886
1 119886
119899minus1) Here
119909 = 1199091=10038161003816100381610038161199091
1003816100381610038161003816+ sdot sdot sdot +
1003816100381610038161003816119909119899
1003816100381610038161003816 (25)
for any 119909 = (1199091 119909
119899) isin R119899 and 119860 = max
1199091=1119860119909
1=
max](|1198861]| + sdot sdot sdot + |119886119899]|) for any matrix
119860 = (
1198861111988612sdot sdot sdot 119886
1119899
1198862111988622sdot sdot sdot 119886
2119899
d
11988611989911198861198992sdot sdot sdot 119886
119899119899
) (26)
22 Adaptation to a Symbolic Formalism Navarro and Perez[12 14] have proposed an adaptation of themethod describedabove in order to compute the matrix 119890119860119905 instead of 119890119860 If wedo so we obtain the principal matrix of (16) whose elementslie on the set of quasipolynomials and the symbolic processorresults in being suitable to work with those matrices Theapproach is to compute
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
(27)
taking into account that
119890119861119905119898= (
1198920 (119905 119898) 1198921 (
119905 119898) sdot sdot sdot 119892119899minus1 (119905 119898)
0 1198920 (119905 119898) sdot sdot sdot 119892119899minus2 (
119905 119898)
d
0 0 sdot sdot sdot 119892
0 (119905 119898)
)
119890119862119905119898=(
1 0 0 sdot sdot sdot 0
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
1205960 (119905) 1205961 (
119905) 1205962 (119905) sdot sdot sdot 120596119899minus1 (
119905)
)
(28)
being for any 119899 isin N
119892119899 (119905 119898) =
119905119899
119899119898119899 (29)
4 Journal of Applied Mathematics
and for any 119894 = 0 119899 minus 2
120596119894 (119905) =
119886119894
119886119899minus1
(119890minus119886119899minus1
119905119898minus 1) 120596
119899minus1 (119905) = 119890
minus119886119899minus1
119905119898
(30)
Thus 119890119860119905 is amatrix of quasipolynomials that can be com-pletely computed through the symbolic processor developedby Navarro [11] The procedure for the computation of theexponential matrix is substantially simplified by using thefollowing equation which avoids the symbolic multiplicationof 119890119861119905119898 and 119890119862119905119898
119890119861119905119898119890119862119905119898= 119890
119861119905119898+ 119867 (119905119898) (31)
where
119867(119905119898) =
1
119886119899minus1
119891 (119905 119898)(
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
119891 (119905 119898) = 119890minus119886119899minus1
119905119898minus 1
(32)
This relation can be obtained directly from themultiplicationof matrices 119890119861119905119898 and 119890119862119905119898 as given in (28)
23 Symbolic Expansion of the Exponential Matrix As it hasbeen stated in Section 22 the exponential matrix 119890119860119905 can besymbolically calculated through (27) and (31)
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
= (119890119861119905119898+ 119867 (119905119898))
119898
(33)
This expression can be calculated symbolically Let us express119867(119905119898) as
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898) (34)
with
120582 (119905 119898) =
1
119886119899minus1
119891 (119905 119898)
119869 (119905 119898) = (
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
(35)
Thus
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869 (119905 119898))
119898
119896
(36)
where (119860 119861)119898119896is the so-called noncommutative parenthesis
defined as
(119860 119861)119898
119896=
(119898
119896)
sum
119894=1
120590(119898119896)
prod
119895=1
(119860(1minus(minus1)
119895)2119861(1+(minus1)
119895)2)
119888119894119895
(37)
where 119860 and 119861 are two noncommutative 119899 times 119899 matrices119898 119896 119888
119894119895isin Z+cup 0
120590 (119898 119896) =
2119896 + 1 if 2119896 le 1198982 (119898 minus 119896 + 1) if 2119896 gt 119898
(38)
and 119888119894119895is determined by the following properties
(1) sum120590(119898119896)
119895=1119888119894119895= 119898 for all 119894 = 1 2 (119898119896 )
(2) sum[120590(119898119896)2]
119895=1119888119894(2119895)= 119898 minus 119896 for all 119894 = 1 2 (119898119896 ) with
[120590(119898 119896)2] being the entire part of 120590(119898 119896)2(3) 119888
1198942= 0 for all 119894 = 1 2 (119898119896 )
(4) if 119888119894119895= 0 and 119888
119894(119895+2)= 0 then 119888
119894(119895+1)= 0 for all 119894 =
1 2 (119898
119896 ) and 119895 = 1 2 120590(119898 119896) minus 2
In the following we summarize some expressions whichsimplify the way in which the matrix (119890119861119905119898 + 119867(119905119898))119898 issymbolically computed First let us introduce the followingmatrices
119878119899minus1 (119905 119898) = (1198860
1198861sdot sdot sdot 119886
119899minus1) 119865 (119905 119898)
119865 (119905 119898) =(
(
(
119905119899minus1
(119899 minus 1) 119905119899minus2119898
(119899 minus 1) (119899 minus 2) 119905119899minus3119898
2
(119899 minus 1)119905
0119898
119899minus1
)
)
)
(39)
Lemma 1 For any 119896 isin Z such that 119896 gt 1
(119890119861119905119898)
119896
=(
1198660119896 (119905 119898) 1198661119896 (
119905 119898) sdot sdot sdot 119866119899minus1119896 (119905 119898)
0 1198660119896 (119905 119898) sdot sdot sdot 119866119899minus2119896 (
119905 119898)
d
0 0 sdot sdot sdot 119866
0119896 (119905 119898)
)
(40)
with
119866]119896 (119905 119898) = 119896]119892] (119905 119898) (41)
for each ] = 0 119899 minus 1 where 119892](119905 119898) is given by (29)
Lemma 2 For any 119901 isin Z such that 119901 gt 1
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905 119898))
119901minus1
times 119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(42)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
Lemma 3 For any 119901 119896 isin Z such that 119901 119896 ge 1
(119890119861119905119898)
119896
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905))
119901minus1
times Ω119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(43)
Journal of Applied Mathematics 5
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39) and
Ω =(
(119896 + 1)119899minus1
0 sdot sdot sdot 0
0 (119896 + 1)119899minus2sdot sdot sdot 0
d
0 0 sdot sdot sdot 1
) (44)
Lemma 4 For any 119901 119896 isin Z such that 119901 119896 ge 1
119867119901(119905 119898) (119890
119861119905119898)
119896
= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
times (119878119899minus1 (119905))
119901minus1119865 (119905 119898)119860 (119905 119898)
(45)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
119860 (119905119898) = (1198600 (119905 119898) 1198601 (
119905 119898) sdot sdot sdot 119860119899minus1 (119905 119898))
119860120583 (119905 119898) =
120583
sum
]=0
119886]119896120583minus]119892120583minus]
(46)
for any 120583 = 0 119899 minus 1 and 119892] is given by (29)
For the sake of simplicity we have omitted the depen-dence on119898 and 119905 of 119892]
3 Solution to the Nonhomogeneous Problem
The general solution to a nonhomogeneous linear differentialequation of order 119899 can be expressed as the sum of the generalsolution to the corresponding homogeneous linear differen-tial equation and any solution to the complete equation Thesymbolic manipulation system calculates the solution to anonperturbed differential equation with initial conditions ofthe form (12)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 119906 (119905) (47)
with initial conditions
119909 (0) = 11990910 119909
(119899minus1)(0) = 1199091198990
(48)
where 1198860 119886
1 119886
119899minus1isin R 119909
10 119909
1198990isin R and
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (49)
being 119899] isin N and 120572] 120596] 120582] 120583] isin R With the aid of thesubstitutions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (50)
(12) is reduced to the system of differential equations given by
(119905) = 119860119883 (119905) + 119861 (119905) 119883 (0) = 1198830 (51)
where
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119861 (119905) = (
0
0
119906 (119905)
) 119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
)
1198830= (
11990910
11990920
1199091198990
)
(52)
The computation of the solution to the constant coeffi-cients linear part requires the calculation of the exponentialof the matrix 119860 Φ(119905) = 119890119860119905
119883 (119905) = Φ (119905)1198830+ Φ (119905) int
119905
0
exp (119860120591) 119861 (120591) 119889120591 (53)
31 Symbolic Expansion of the Solution In the following wegive a formula for the symbolic expansion of the solution tothe complete ordinary differential equation To that end letus express the noncommutative parenthesis (119890119861119905119898 119869(119905 119898))
119898
119896
as
(119890119861119905119898 119869(119905 119898))
119898
119896= (
119901(119898119896)
11990311
(119905) sdot sdot sdot 119901(119898119896)
1199031119899
(119905)
d
119901(119898119896)
1199031198991
(119905) sdot sdot sdot 119901(119898119896)
119903119899119899
(119905)
)
= (119901(119898119896)
119903119894119895
(119905))
119899
119894119895=1
= 119875 (119898 119896) (119905)
(54)
where each 119901(119898119896)
1199031119899
(119905) is a polynomial of degree 119903119894119895le 119898(119899 minus 1)
in the indeterminate 119905 with coefficients from R and119898 = 0Let us also express
120582119896(119905 119898) = (
1
119886119899minus1
(119890119886119899minus1
119905119898minus 1))
119896
=
119896
sum
]=0
120572]119890120573]119905 (55)
being
120572] = (1
119886119899minus1
)
119896
(
119896
]) (minus1)
]
120573] = minus119886119899minus1
119898
(119896 minus ])
(56)
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
4 Journal of Applied Mathematics
and for any 119894 = 0 119899 minus 2
120596119894 (119905) =
119886119894
119886119899minus1
(119890minus119886119899minus1
119905119898minus 1) 120596
119899minus1 (119905) = 119890
minus119886119899minus1
119905119898
(30)
Thus 119890119860119905 is amatrix of quasipolynomials that can be com-pletely computed through the symbolic processor developedby Navarro [11] The procedure for the computation of theexponential matrix is substantially simplified by using thefollowing equation which avoids the symbolic multiplicationof 119890119861119905119898 and 119890119862119905119898
119890119861119905119898119890119862119905119898= 119890
119861119905119898+ 119867 (119905119898) (31)
where
119867(119905119898) =
1
119886119899minus1
119891 (119905 119898)(
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
119891 (119905 119898) = 119890minus119886119899minus1
119905119898minus 1
(32)
This relation can be obtained directly from themultiplicationof matrices 119890119861119905119898 and 119890119862119905119898 as given in (28)
23 Symbolic Expansion of the Exponential Matrix As it hasbeen stated in Section 22 the exponential matrix 119890119860119905 can besymbolically calculated through (27) and (31)
119890119860119905≃ (119890
119861119905119898119890119862119905119898)
119898
= (119890119861119905119898+ 119867 (119905119898))
119898
(33)
This expression can be calculated symbolically Let us express119867(119905119898) as
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898) (34)
with
120582 (119905 119898) =
1
119886119899minus1
119891 (119905 119898)
119869 (119905 119898) = (
119892119899minus1 (119905 119898)
1198920 (119905 119898)
) (11988601198861sdot sdot sdot 119886
119899minus1)
(35)
Thus
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869 (119905 119898))
119898
119896
(36)
where (119860 119861)119898119896is the so-called noncommutative parenthesis
defined as
(119860 119861)119898
119896=
(119898
119896)
sum
119894=1
120590(119898119896)
prod
119895=1
(119860(1minus(minus1)
119895)2119861(1+(minus1)
119895)2)
119888119894119895
(37)
where 119860 and 119861 are two noncommutative 119899 times 119899 matrices119898 119896 119888
119894119895isin Z+cup 0
120590 (119898 119896) =
2119896 + 1 if 2119896 le 1198982 (119898 minus 119896 + 1) if 2119896 gt 119898
(38)
and 119888119894119895is determined by the following properties
(1) sum120590(119898119896)
119895=1119888119894119895= 119898 for all 119894 = 1 2 (119898119896 )
(2) sum[120590(119898119896)2]
119895=1119888119894(2119895)= 119898 minus 119896 for all 119894 = 1 2 (119898119896 ) with
[120590(119898 119896)2] being the entire part of 120590(119898 119896)2(3) 119888
1198942= 0 for all 119894 = 1 2 (119898119896 )
(4) if 119888119894119895= 0 and 119888
119894(119895+2)= 0 then 119888
119894(119895+1)= 0 for all 119894 =
1 2 (119898
119896 ) and 119895 = 1 2 120590(119898 119896) minus 2
In the following we summarize some expressions whichsimplify the way in which the matrix (119890119861119905119898 + 119867(119905119898))119898 issymbolically computed First let us introduce the followingmatrices
119878119899minus1 (119905 119898) = (1198860
1198861sdot sdot sdot 119886
119899minus1) 119865 (119905 119898)
119865 (119905 119898) =(
(
(
119905119899minus1
(119899 minus 1) 119905119899minus2119898
(119899 minus 1) (119899 minus 2) 119905119899minus3119898
2
(119899 minus 1)119905
0119898
119899minus1
)
)
)
(39)
Lemma 1 For any 119896 isin Z such that 119896 gt 1
(119890119861119905119898)
119896
=(
1198660119896 (119905 119898) 1198661119896 (
119905 119898) sdot sdot sdot 119866119899minus1119896 (119905 119898)
0 1198660119896 (119905 119898) sdot sdot sdot 119866119899minus2119896 (
119905 119898)
d
0 0 sdot sdot sdot 119866
0119896 (119905 119898)
)
(40)
with
119866]119896 (119905 119898) = 119896]119892] (119905 119898) (41)
for each ] = 0 119899 minus 1 where 119892](119905 119898) is given by (29)
Lemma 2 For any 119901 isin Z such that 119901 gt 1
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905 119898))
119901minus1
times 119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(42)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
Lemma 3 For any 119901 119896 isin Z such that 119901 119896 ge 1
(119890119861119905119898)
119896
(119867 (119905 119898))119901= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
(119878119899minus1 (119905))
119901minus1
times Ω119865 (119905 119898) (11988601198861sdot sdot sdot 119886
119899minus1)
(43)
Journal of Applied Mathematics 5
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39) and
Ω =(
(119896 + 1)119899minus1
0 sdot sdot sdot 0
0 (119896 + 1)119899minus2sdot sdot sdot 0
d
0 0 sdot sdot sdot 1
) (44)
Lemma 4 For any 119901 119896 isin Z such that 119901 119896 ge 1
119867119901(119905 119898) (119890
119861119905119898)
119896
= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
times (119878119899minus1 (119905))
119901minus1119865 (119905 119898)119860 (119905 119898)
(45)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
119860 (119905119898) = (1198600 (119905 119898) 1198601 (
119905 119898) sdot sdot sdot 119860119899minus1 (119905 119898))
119860120583 (119905 119898) =
120583
sum
]=0
119886]119896120583minus]119892120583minus]
(46)
for any 120583 = 0 119899 minus 1 and 119892] is given by (29)
For the sake of simplicity we have omitted the depen-dence on119898 and 119905 of 119892]
3 Solution to the Nonhomogeneous Problem
The general solution to a nonhomogeneous linear differentialequation of order 119899 can be expressed as the sum of the generalsolution to the corresponding homogeneous linear differen-tial equation and any solution to the complete equation Thesymbolic manipulation system calculates the solution to anonperturbed differential equation with initial conditions ofthe form (12)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 119906 (119905) (47)
with initial conditions
119909 (0) = 11990910 119909
(119899minus1)(0) = 1199091198990
(48)
where 1198860 119886
1 119886
119899minus1isin R 119909
10 119909
1198990isin R and
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (49)
being 119899] isin N and 120572] 120596] 120582] 120583] isin R With the aid of thesubstitutions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (50)
(12) is reduced to the system of differential equations given by
(119905) = 119860119883 (119905) + 119861 (119905) 119883 (0) = 1198830 (51)
where
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119861 (119905) = (
0
0
119906 (119905)
) 119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
)
1198830= (
11990910
11990920
1199091198990
)
(52)
The computation of the solution to the constant coeffi-cients linear part requires the calculation of the exponentialof the matrix 119860 Φ(119905) = 119890119860119905
119883 (119905) = Φ (119905)1198830+ Φ (119905) int
119905
0
exp (119860120591) 119861 (120591) 119889120591 (53)
31 Symbolic Expansion of the Solution In the following wegive a formula for the symbolic expansion of the solution tothe complete ordinary differential equation To that end letus express the noncommutative parenthesis (119890119861119905119898 119869(119905 119898))
119898
119896
as
(119890119861119905119898 119869(119905 119898))
119898
119896= (
119901(119898119896)
11990311
(119905) sdot sdot sdot 119901(119898119896)
1199031119899
(119905)
d
119901(119898119896)
1199031198991
(119905) sdot sdot sdot 119901(119898119896)
119903119899119899
(119905)
)
= (119901(119898119896)
119903119894119895
(119905))
119899
119894119895=1
= 119875 (119898 119896) (119905)
(54)
where each 119901(119898119896)
1199031119899
(119905) is a polynomial of degree 119903119894119895le 119898(119899 minus 1)
in the indeterminate 119905 with coefficients from R and119898 = 0Let us also express
120582119896(119905 119898) = (
1
119886119899minus1
(119890119886119899minus1
119905119898minus 1))
119896
=
119896
sum
]=0
120572]119890120573]119905 (55)
being
120572] = (1
119886119899minus1
)
119896
(
119896
]) (minus1)
]
120573] = minus119886119899minus1
119898
(119896 minus ])
(56)
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
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Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 5
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39) and
Ω =(
(119896 + 1)119899minus1
0 sdot sdot sdot 0
0 (119896 + 1)119899minus2sdot sdot sdot 0
d
0 0 sdot sdot sdot 1
) (44)
Lemma 4 For any 119901 119896 isin Z such that 119901 119896 ge 1
119867119901(119905 119898) (119890
119861119905119898)
119896
= (
119891 (119905 119898)
119886119899minus1 (119899 minus 1)119898
119899minus1)
119901
times (119878119899minus1 (119905))
119901minus1119865 (119905 119898)119860 (119905 119898)
(45)
where 119878119899minus1(119905 119898) and 119865(119905 119898) are given by (39)
119860 (119905119898) = (1198600 (119905 119898) 1198601 (
119905 119898) sdot sdot sdot 119860119899minus1 (119905 119898))
119860120583 (119905 119898) =
120583
sum
]=0
119886]119896120583minus]119892120583minus]
(46)
for any 120583 = 0 119899 minus 1 and 119892] is given by (29)
For the sake of simplicity we have omitted the depen-dence on119898 and 119905 of 119892]
3 Solution to the Nonhomogeneous Problem
The general solution to a nonhomogeneous linear differentialequation of order 119899 can be expressed as the sum of the generalsolution to the corresponding homogeneous linear differen-tial equation and any solution to the complete equation Thesymbolic manipulation system calculates the solution to anonperturbed differential equation with initial conditions ofthe form (12)
119909(119899)+ 119886
119899minus1119909(119899minus1)+ sdot sdot sdot + 119886
1 + 119886
0119909 = 119906 (119905) (47)
with initial conditions
119909 (0) = 11990910 119909
(119899minus1)(0) = 1199091198990
(48)
where 1198860 119886
1 119886
119899minus1isin R 119909
10 119909
1198990isin R and
119906 (119905) = sum
]ge0
119905119899]119890120572]119905(120582] cos (120596]119905) + 120583] sin (120596]119905)) (49)
being 119899] isin N and 120572] 120596] 120582] 120583] isin R With the aid of thesubstitutions
1199091= 119909 119909
2= 119909
119899= 119909
(119899minus1) (50)
(12) is reduced to the system of differential equations given by
(119905) = 119860119883 (119905) + 119861 (119905) 119883 (0) = 1198830 (51)
where
119860 = (
0 1 0 sdot sdot sdot 0
0 0 1 sdot sdot sdot 0
d
minus1198860minus119886
1minus119886
2sdot sdot sdot minus119886
119899minus1
)
119861 (119905) = (
0
0
119906 (119905)
) 119883 (119905) = (
1199091 (119905)
1199092 (119905)
119909119899 (119905)
)
1198830= (
11990910
11990920
1199091198990
)
(52)
The computation of the solution to the constant coeffi-cients linear part requires the calculation of the exponentialof the matrix 119860 Φ(119905) = 119890119860119905
119883 (119905) = Φ (119905)1198830+ Φ (119905) int
119905
0
exp (119860120591) 119861 (120591) 119889120591 (53)
31 Symbolic Expansion of the Solution In the following wegive a formula for the symbolic expansion of the solution tothe complete ordinary differential equation To that end letus express the noncommutative parenthesis (119890119861119905119898 119869(119905 119898))
119898
119896
as
(119890119861119905119898 119869(119905 119898))
119898
119896= (
119901(119898119896)
11990311
(119905) sdot sdot sdot 119901(119898119896)
1199031119899
(119905)
d
119901(119898119896)
1199031198991
(119905) sdot sdot sdot 119901(119898119896)
119903119899119899
(119905)
)
= (119901(119898119896)
119903119894119895
(119905))
119899
119894119895=1
= 119875 (119898 119896) (119905)
(54)
where each 119901(119898119896)
1199031119899
(119905) is a polynomial of degree 119903119894119895le 119898(119899 minus 1)
in the indeterminate 119905 with coefficients from R and119898 = 0Let us also express
120582119896(119905 119898) = (
1
119886119899minus1
(119890119886119899minus1
119905119898minus 1))
119896
=
119896
sum
]=0
120572]119890120573]119905 (55)
being
120572] = (1
119886119899minus1
)
119896
(
119896
]) (minus1)
]
120573] = minus119886119899minus1
119898
(119896 minus ])
(56)
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Stochastic AnalysisInternational Journal of
6 Journal of Applied Mathematics
Thus taking into account (33) the exponential matrix of 119860can be arranged as
119890119860119905≃
119898
sum
119896=0
(
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot 120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
=(
(
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
11990311
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031119899
(119905)
d
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
1199031198991
(119905) sdot sdot sdot
119898
sum
119896=0
120601119896 (119905) 119901
(119898119896)
119903119899119899
(119905)
)
)
(57)
where
120601119896 (119905) =
119896
sum
]=0
120572]119890120573]119905 (58)
In order to develop a symbolic expression of the solutionto the complete differential equation let us express 119906(119905) as
119906 (119905) = 119890120575119905(119876
119886 (119905) cos (120596119905) + 119879119887 (119905) sin (120596119905)) (59)
with 119886 119887 isin Z cup 0 120575 120596 isin R and 119876119886(119905) and 119879
119887(119905) being
real polynomials of degrees 119886 and 119887 respectively in theindeterminate 119905
The product 119890minus119860120591119861(120591) can be arranged as follows
119890minus119860120591119861 (120591)
=
(
(
(
(
(
(
(
(
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199031119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
1199032119899
(minus120591)) 119906 (120591) 119889120591
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119899119899
(minus120591)) 119906 (120591) 119889120591
)
)
)
)
)
)
)
)
(60)
Here the integrand of each element of the above matrix canbe written in the form of a quasipolynomial Hence we arriveto the formulae
int
119905
0
(
119898
sum
119896=0
(
119896
sum
]=0
120572]119890120573]120591)119901
(119898119896)
119903119895119899
(minus120591)) 119906 (120591) 119889120591
= sum
120572119895119899
(120578120572119895119899
119862120572119895119899120573119895119899120574119895119899(119905) + ]120572
119895119899
119878120572119895119899120573119895119899120574119895119899(119905))
(61)
where 120572119895119899isin Z+cup 0 120573
119895119899 120574
119895119899isin R 119895 = 1 119899 and
119862119898120573120574 (119905) = int 119905
119898119890120573119905 cos (120574119905) 119889119905
119878119898120573120574 (119905) = int 119905
119898119890120573119905 sin (120574119905) 119889119905
(62)
These functions are computed recursively through
1198620120573120574 (119905) =
120574
1205732+ 120574
2119890120573119905 sin (120574119905) +
120573
1205732+ 120574
2119890120573119905 cos (120574119905)
1198780120573120574 (119905) =
120573
1205732+ 120574
2119890120573119905 sin (120574119905) minus
120574
1205732+ 120574
2119890120573119905 cos (120574119905)
(63)
and for any119898 ge 1
119862119898120573120574 (119905) = 119905
1198981198620120573120574 (119905) minus 119898
120574
1205732+ 120574
2119878119898minus1120573120574
minus 119898
120573
1205732+ 120574
2119862119898minus1120573120574 (
119905)
119878119898120573120574 (119905) = 119905
1198981198780120573120574 (119905) minus 119898
120573
1205732+ 120574
2119878119898minus1120573120574
+ 119898
120574
1205732+ 120574
2119862119898minus1120573120574 (
119905)
(64)
Thus (53) can be expressed via a quasipolynomial andthus obtained through the designed symbolic system
4 Symbolic and Numeric Results
41 On the Form of the Exponential Matrix The aim of thissection is to illustrate the form that the approximation of theexponential matrix adopts For that purpose let us considerthe differential equation given by
119909(4)+ 4 + 3 + 2 + 119909 = 0 (65)
with initial conditions
119909 (0) = 1 (0) = 0 (0) = 0 (0) = 0
(66)
This equation is transformed into the system of differentialequations given by
(119905) = 119860119883 (119905) (67)
where 119860 is the companion matrix
119860 = (
0 1 0 0
0 0 1 0
0 0 0 1
minus1 minus2 minus3 minus4
) (68)
According to the technique described in Section 2 we splitmatrix 119860 into 119861 + 119862 where
119861 = (
0 1 0 0
0 0 1 0
0 0 0 1
0 0 0 0
) 119862 = (
0 0 0 0
0 0 0 0
0 0 0 0
minus1 minus2 minus3 minus4
)
(69)
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
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Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical PhysicsAdvances in
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
Discrete Dynamics in Nature and Society
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 7
Equation (36)
(119890119861119905119898+ 119867 (119905119898))
119898
=
119898
sum
119896=0
120582119896(119905 119898) (119890
119861119905119898 119869(119905 119898))
119898
119896
(70)
allows us to compute a symbolic approximation to thesolution to the differential equation In the problem we arediscussing 119890119861119905119898119867(119905119898) 120582(119905 119898) and 119869(119905 119898) can be writtenas
119890119861119905119898=
(
(
(
(
(
(
(
1
119905
119898
1199052
(2119898)
1199053
(6119898)
0 1
119905
119898
1199052
(2119898)
0 0 1
119905
119898
0 0 0 1
)
)
)
)
)
)
)
119867(119905119898) = 120582 (119905 119898) 119869 (119905 119898)
(71)
with
120582 (119905 119898) =
1
4
(eminus4119905119898 minus 1)
119869 (119905 119898) =
(
(
(
(
(
(
1199053
(61198983)
21199053
(61198983)
31199053
(61198983)
41199053
(61198983)
1199052
(21198982)
21199052
(21198982)
31199052
(21198982)
41199052
(21198982)
119905
119898
2119905
119898
3119905
119898
4119905
119898
1 2 3 4
)
)
)
)
)
)
(72)
Taking for instance119898 = 3 we get that
119890119860119905≃
3
sum
119896=0
120582119896(119905 3) (119890
1198611199053 119869 (119905 3))
3
119896
= A3+ 120582 (A
2B +BA
2+ABA)
+ 1205822(AB
2+B
2A +BAB) + 120582
3B
3
(73)
For the sake of simplicity we have introduced the followingnotation
A = 1198901198611199053 B = 119869 (119905 3) (74)
0 10987654321
05
minus05
0
x1(t
)
t
Figure 1 Comparison of the solution computed through thesymbolic method presented in this paper and the numeric solutionto the problem calculated by a Runge-Kutta fourth order methodwith a step of ℎ = 0001
Matrices A3 A2B BA2 ABA AB2 B2A BABandB3 are computed with the help of the designed symbolicprocessor with the result
A3=
(
(
(
(
1 119905
1199052
2
1199053
6
0 1 119905
1199052
2
0 0 1 119905
0 0 0 1
)
)
)
)
A2B =(
(
(
(
1199053
6
1199053
3
1199053
2
21199053
3
1199052
2
1199052 3119905
2
2
21199052
119905 2119905 3119905 4119905
1 2 3 4
)
)
)
)
AB2
=(
(AB2)11(AB2
)12(AB2
)13(AB2
)14
(AB2)21(AB2
)22(AB2
)23(AB2
)24
(AB2)31(AB2
)32(AB2
)33(AB2
)34
(AB2)41(AB2
)42(AB2
)43(AB2
)44
)
(75)
where
(AB2)11=
2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(AB2)12=
4
6561
1199056+
8
729
1199055+
8
81
1199054+
32
81
1199053
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Mathematical PhysicsAdvances in
Complex AnalysisJournal of
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
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Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
8 Journal of Applied Mathematics
Exponential matrix
Dep variable Indep variable
Coeff and func
ODE
Initial conditions
ODE order
Initial cond
2
0 1
1 1 1
x t
u(t)
sin(t)
t = 0
a1 a0a2
x10 x20
Figure 2 The first window shown by the symbolic processor allows us to introduce the parameters which define the differential equation tobe solved including the initial conditions
(AB2)13=
2
2187
1199056+
4
243
1199055+
4
27
1199054+
16
27
1199053
(AB2)14=
8
6561
1199056+
16
729
1199055+
16
81
1199054+
64
81
1199053
(AB2)21=
1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(AB2)22=
2
729
1199055+
4
81
1199054+
4
9
1199053+
16
9
1199052
(AB2)23=
1
243
1199055+
2
27
1199054+
2
3
1199053+
8
3
1199052
(AB2)24=
4
729
1199055+
8
81
1199054+
8
9
1199053+
32
9
1199052
(AB2)31=
1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(AB2)32=
2
243
1199054+
4
27
1199053+
4
3
1199052+
16
3
119905
(AB2)33=
1
81
1199054+
2
9
1199053+ 2119905
2+ 8119905
(AB2)34=
4
243
1199054+
8
27
1199053+
8
3
1199052+
32
3
119905
(AB2)41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(AB2)42=
1
81
1199053+
2
9
1199052+ 2119905 + 8
(AB2)43=
1
54
1199053+
1
3
1199052+ 3119905 + 12
(AB2)44=
2
81
1199053+
4
9
1199052+ 4119905 + 16
ABA
= (
(ABA)11 (ABA)12 (ABA)13 (ABA)14(ABA)21 (ABA)22 (ABA)23 (ABA)24(ABA)31 (ABA)32 (ABA)33 (ABA)34(ABA)41 (ABA)42 (ABA)43 (ABA)44
)
(76)
where
(ABA)11 =4
81
1199053
(ABA)12 =4
243
1199054+
8
81
1199053
(ABA)13 =2
729
1199055+
8
243
1199054+
4
27
1199053
(ABA)14 =2
6561
1199056+
4
729
1199055+
4
81
1199054+
16
81
1199053
(ABA)21 =2
9
1199052
(ABA)22 =2
27
1199053+
4
9
1199052
(ABA)23 =1
81
1199054+
4
27
1199053+
2
3
1199052
(ABA)24 =1
729
1199055+
2
81
1199054+
2
9
1199053+
8
9
1199052
(ABA)31 =2
3
119905
(ABA)32 =2
9
1199052+
4
3
119905
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
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Mathematical PhysicsAdvances in
Complex AnalysisJournal of
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
Discrete Dynamics in Nature and Society
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Decision SciencesAdvances in
Discrete MathematicsJournal of
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 9
(ABA)33 =1
27
1199053+
4
9
1199052+ 2119905
(ABA)34 =1
243
1199054+
2
27
1199053+
2
3
1199052+
8
3
119905
(ABA)41 = 1
(ABA)42 =1
3
119905 + 2
(ABA)43 =1
18
1199052+
2
3
119905 + 3
(ABA)44 =1
162
1199053+
1
9
1199052+ 119905 + 4
B3=(
(
(B3)11(B3)12(B3)13(B3)14
(B3)21(B3)22(B3)23(B3)24
(B3)31(B3)32(B3)33(B3)34
(B3)41(B3)42(B3)43(B3)44
)
)
(77)
where
(B3)11=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B3)12=
1
2125764
1199059+
1
59049
1199058+
2
6561
1199057+
22
6561
1199056
+
17
729
1199055+
8
81
1199054+
16
81
1199053
(B3)13=
1
1417176
1199059+
1
39366
1199058+
1
2187
1199057+
11
2187
1199056
+
17
486
1199055+
4
27
1199054+
8
27
1199053
(B3)14=
1
1062882
1199059+
2
59049
1199058+
4
6561
1199057+
44
6561
1199056
+
34
729
1199055+
16
81
1199054+
32
81
1199053
(B3)21=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B3)22=
1
236196
1199058+
1
6561
1199057+
2
729
1199056+
22
729
1199055
+
17
81
1199054+
8
9
1199053+
16
9
1199052
(B3)23=
1
157464
1199058+
1
4374
1199057+
1
243
1199056+
11
243
1199055
+
17
54
1199054+
4
3
1199053+
8
3
1199052
(B3)24=
1
118098
1199058+
2
6561
1199057+
4
729
1199056+
44
729
1199055
+
34
81
1199054+
16
9
1199053+
32
9
1199052
(B3)31=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B3)32=
1
39366
1199057+
2
2187
1199056+
4
243
1199055+
44
243
1199054
+
34
27
1199053+
16
3
1199052+
32
3
119905
(B3)33=
1
26244
1199057+
1
729
1199056+
2
81
1199055+
22
81
1199054
+
17
9
1199053+ 8119905
2+ 16119905
(B3)34=
1
19683
1199057+
4
2187
1199056+
8
243
1199055+
88
243
1199054
+
68
27
1199053+
32
3
1199052+
64
3
119905
(B3)41=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053
+
17
9
1199052+ 8119905 + 16
(B3)42=
1
13122
1199056+
2
729
1199055+
4
81
1199054+
44
81
1199053
+
34
9
1199052+ 16119905 + 32
(B3)43=
1
8748
1199056+
1
243
1199055+
2
27
1199054+
22
27
1199053
+
17
3
1199052+ 24119905 + 48
(B3)44=
1
6561
1199056+
4
729
1199055+
8
81
1199054+
88
81
1199053
+
68
9
1199052+ 32119905 + 64
B2A
=(
(B2A)11(B2A)
12(B2A)
13(B2A)
14
(B2A)21(B2A)
22(B2A)
23(B2A)
24
(B2A)31(B2A)
32(B2A)
33(B2A)
34
(B2A)41(B2A)
42(B2A)
43(B2A)
44
)
(78)
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
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Differential EquationsInternational Journal of
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International Journal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
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Decision SciencesAdvances in
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
10 Journal of Applied Mathematics
where
(B2A)
11=
1
26244
1199056+
1
1458
1199055+
1
162
1199054+
2
81
1199053
(B2A)
12=
1
78732
1199057+
2
6561
1199056+
5
1458
1199055+
5
243
1199054+
4
81
1199053
(B2A)
13=
1
472392
1199058+
5
78732
1199057+
2
2187
1199056+
11
1458
1199055
+
17
486
1199054+
2
27
1199053
(B2A)
14=
1
4251528
1199059+
1
118098
1199058+
1
6561
1199057+
11
6561
1199056
+
17
1458
1199055+
4
81
1199054+
8
81
1199053
(B2A)
21=
1
2916
1199055+
1
162
1199054+
1
18
1199053+
2
9
1199052
(B2A)
22=
1
8748
1199056+
2
729
1199055+
5
162
1199054+
5
27
1199053+
4
9
1199052
(B2A)
23=
1
52488
1199057+
5
8748
1199056+
2
243
1199055+
11
162
1199054
+
17
54
1199053+
2
3
1199052
(B2A)
24=
1
472392
1199058+
1
13122
1199057+
1
729
1199056+
11
729
1199055
+
17
162
1199054+
4
9
1199053+
8
9
1199052
(B2A)
31=
1
486
1199054+
1
27
1199053+
1
3
1199052+
4
3
119905
(B2A)
32=
1
1458
1199055+
4
243
1199054+
5
27
1199053+
10
9
1199052+
8
3
119905
(B2A)
33=
1
8748
1199056+
5
1458
1199055+
4
81
1199054+
11
27
1199053+
17
9
1199052+ 4119905
(B2A)
34=
1
78732
1199057+
1
2187
1199056+
2
243
1199055+
22
243
1199054
+
17
27
1199053+
8
3
1199052+
16
3
119905
(B2A)
41=
1
162
1199053+
1
9
1199052+ 119905 + 4
(B2A)
42=
1
486
1199054+
4
81
1199053+
5
9
1199052+
10
3
119905 + 8
(B2A)
43=
1
2916
1199055+
5
486
1199054+
4
27
1199053+
11
9
1199052+
17
3
119905 + 12
(B2A)
44=
1
26244
1199056+
1
729
1199055+
2
81
1199054+
22
81
1199053+
17
9
1199052
+ 8119905 + 16
BA2
=(
(
(BA2)11(BA2
)12(BA2
)13(BA2
)14
(BA2)21(BA2
)22(BA2
)23(BA2
)24
(BA2)31(BA2
)32(BA2
)33(BA2
)34
(BA2)41(BA2
)42(BA2
)43(BA2
)44
)
)
(79)
where
(BA2)11=
1
162
1199053
(BA2)12=
1
243
1199054+
1
81
1199053
(BA2)13=
1
729
1199055+
2
243
1199054+
1
54
1199053
(BA2)14=
2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BA2)21=
1
18
1199052
(BA2)22=
1
27
1199053+
1
9
1199052
(BA2)23=
1
81
1199054+
2
27
1199053+
1
6
1199052
(BA2)24=
2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BA2)31=
1
3
119905
(BA2)32=
2
9
1199052+
2
3
119905
(BA2)33=
2
27
1199053+
4
9
1199052+ 119905
(BA2)34=
4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BA2)41= 1
(BA2)42=
2
3
119905 + 2
(BA2)43=
2
9
1199052+
4
3
119905 + 3
(BA2)44=
4
81
1199053+
4
9
1199052+ 2119905 + 4
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
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Mathematical PhysicsAdvances in
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 11
BAB
= (
(BAB)11 (BAB)12 (BAB)13 (BAB)14(BAB)21 (BAB)22 (BAB)23 (BAB)24(BAB)31 (BAB)32 (BAB)33 (BAB)34(BAB)41 (BAB)42 (BAB)43 (BAB)44
)
(80)
where
(BAB)11 =2
6561
1199056+
2
729
1199055+
1
81
1199054+
2
81
1199053
(BAB)11 =4
6561
1199056+
4
729
1199055+
2
81
1199054+
4
81
1199053
(BAB)11 =2
2187
1199056+
2
243
1199055+
1
27
1199054+
2
27
1199053
(BAB)11 =8
6561
1199056+
8
729
1199055+
4
81
1199054+
8
81
1199053
(BAB)11 =2
729
1199055+
2
81
1199054+
1
9
1199053+
2
9
1199052
(BAB)11 =4
729
1199055+
4
81
1199054+
2
9
1199053+
4
9
1199052
(BAB)11 =2
243
1199055+
2
27
1199054+
1
3
1199053+
2
3
1199052
(BAB)11 =8
729
1199055+
8
81
1199054+
4
9
1199053+
8
9
1199052
(BAB)11 =4
243
1199054+
4
27
1199053+
2
3
1199052+
4
3
119905
(BAB)11 =8
243
1199054+
8
27
1199053+
4
3
1199052+
8
3
119905
(BAB)11 =4
81
1199054+
4
9
1199053+ 2119905
2+ 4119905
(BAB)11 =16
243
1199054+
16
27
1199053+
8
3
1199052+
16
3
119905
(BAB)11 =4
81
1199053+
4
9
1199052+ 2119905 + 4
(BAB)11 =8
81
1199053+
8
9
1199052+ 4119905 + 8
(BAB)11 =4
27
1199053+
4
3
1199052+ 6119905 + 12
(BAB)11 =16
81
1199053+
16
9
1199052+ 8119905 + 16
(81)
So the noncommutative parentheses are given by
(AB)3
0= A
3 (AB)
3
3=B
3
(AB)3
1= (A
2B +BA
2+ABA)
= (
12057211120572121205721312057214
12057221120572221205722312057224
12057231120572321205723312057234
12057241120572421205724312057244
)
(82)
where
12057211=
2
9
1199053
12057212=
4
9
1199053+
5
243
1199054
12057213=
2
3
1199053+
1
243
1199055+
10
243
1199054
12057214=
8
9
1199053+
4
6561
1199056+
2
243
1199055+
5
81
1199054
12057221=
7
9
1199052
12057222=
14
9
1199052+
1
9
1199053
12057223=
7
3
1199052+
2
81
1199054+
2
9
1199053
12057224=
28
9
1199052+
1
243
1199055+
4
81
1199054+
1
3
1199053
12057231= 2119905
12057232= 4119905 +
4
9
1199052
12057233= 6119905 +
1
9
1199053+
8
9
1199052
12057234= 8119905 +
5
243
1199054+
2
9
1199053+
4
3
1199052
12057241= 3
12057242= 6 + 119905
12057243= 9 +
5
18
1199052+ 2119905
12057244= 12 +
1
18
1199053+
5
9
1199052+ 3119905
(AB)3
2= (AB
2+B
2A +BAB)
= (
12057311120573121205731312057314
12057321120573221205732312057324
12057331120573321205733312057334
12057341120573421205734312057344
)
(83)
being
12057311=
17
26244
1199056+
13
1458
1199055+
11
162
1199054+
20
81
1199053
12057312=
10
6561
1199056+
29
1458
1199055+
35
243
1199054+
40
81
1199053+
1
78732
1199057
12057313=
2
729
1199056+
47
1458
1199055+
107
486
1199054+
20
27
1199053
+
1
472392
1199058+
5
78732
1199057
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
12 Journal of Applied Mathematics
12057314=
1
243
1199056+
65
1458
1199055+
8
27
1199054+
80
81
1199053+
1
4251528
1199059
+
1
118098
1199058+
1
6561
1199057
12057321=
13
2916
1199055+
1
18
1199054+
7
18
1199053+
4
3
1199052
12057322=
8
729
1199055+
7
54
1199054+
23
27
1199053+
8
3
1199052+
1
8748
1199056
12057323=
5
243
1199055+
35
162
1199054+
71
54
1199053+ 4119905
2+
1
52488
1199057+
5
8748
1199056
12057324=
23
729
1199055+
49
162
1199054+
16
9
1199053+
16
3
1199052+
1
472392
1199058
+
1
13122
1199057+
1
729
1199056
12057331=
11
486
1199054+
7
27
1199053+
5
3
1199052+
16
3
119905
12057332=
14
243
1199054+
17
27
1199053+
34
9
1199052+
32
3
119905 +
1
1458
1199055
12057333=
1
9
1199054+
29
27
1199053+
53
9
1199052+ 16119905 +
1
8748
1199056+
5
1458
1199055
12057334=
14
81
1199054+
41
27
1199053+ 8119905
2+
64
3
119905 +
1
78732
1199057
+
1
2187
1199056+
2
243
1199055
12057341=
5
81
1199053+
2
3
1199052+ 4119905 + 12
12057342=
13
81
1199053+
5
3
1199052+
28
3
119905 + 24 +
1
486
1199054
12057343=
17
54
1199053+
26
9
1199052+
44
3
119905 + 36 +
1
2916
1199055+
5
486
1199054
12057344=
40
81
1199053+
37
9
1199052+ 20119905 + 48 +
1
26244
1199056
+
1
729
1199055+
2
81
1199054
(84)
In Figure 1 we show a comparison of the solution com-puted through the symbolic method presented in this paperand the numeric solution to the problem calculated by aRunge-Kutta fourth order method with a step of ℎ = 0001Let us stress that the difference between both solutions at anytime is smaller than 10minus7
42 Description of the Program In order to describe the alge-braic processor let us introduce the following test problem
+ + 119909 = sin 119905 (85)
Matrix A
0 1
minus1 minus1
Figure 3 Matrix 119860
Matrix B
0 1
0 0
Figure 4 Matrix 119861
with initial conditions
119909 (0) = 0 (0) = 1 (86)
This equation describes the (small) angular position inradians 119909(119905) of a forced damped pendulum with a periodicdriving force In this equation (119905) represents the inertia(119905) represents the friction and sin(119905) represents a sinusoidaldriving torque applied at the pivot of the pendulumThe exactsolution to this problem is given by
119909 (119905) = minus cos 119905 + 119890minus1199052 cos(radic3
2
119905) + radic3119890minus1199052 sin(
radic3
2
119905)
(87)
The program proceeds as followsThe first window (Figure 2)allows us introducing the definition of variables the orderof the ODE and its coefficients and the function of thenonhomogeneous term 119906(119905)
The next window visualizes the expression of the com-panion matrix related to the ODE (Figure 3)
Then matrices 119861 exp(119861119905119898) 119862 and exp(119862119905119898) whichare used in the calculation of the exponential matrix are
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 13
exp (Bm)
0
((tm)0)(10) ((tm)1)(11)
((tm)0)(10)
Figure 5 Matrix exp(119861119905119898)
Matrix C
0 0
minus1 minus1
Figure 6 Matrix 119862
computed by using a value of119898 satisfying (23)Thesematricesare presented in Figures 4 5 6 and 7
In Figures 8 and 9 we evaluate the exponential matrix 119890119860119905in 119905 = 1 and for119898 = 1000 The algebraic processor enables usto change these two parameters We should emphasize thatthe symbolic solution to the problem is dependent on thevalue of parameter 119898 We have computed this solution fordifferent values of this parameter (119898 = 10 100 1000 and10000) In Figures 10 and 11 we compare the real solutionwithsymbolic solutions 119909(119905) for these values of119898 We observe thatthe symbolic solution gets closer to the real solution as thevalue of119898 is increased
Table 1 shows the numerical evolution of the symbolicapproximation 119909
119878(119905) computed for 119898 = 1000 These values
have been obtained by substituting variable 119905 in the symbolicsolution by values 01 02 1
In Figure 12 we compare the symbolic approximationcomputed via the symbolic processor with the exact solution(87) We also compare these two functions with a numericsolution computed through a Runge-Kutta 4th order methodwith step ℎ = 01 We see that the solution symbolicallycomputed fits better to the exact solution to than thedescribed numerical solution In Table 2 we show the error
exp (Cm)
01
exp(minustm) exp(minustm)
Figure 7 Matrix exp(119862119905119898)
Evaluation on a value of t
Automatic procedure
Variation of the matrix norm
Precision
Digits
t
Value of m
18
13
1
1000
Aproximation of eAt for t
Figure 8 Parameters related to the accuracy of the solution to thedifferential equation
exp (A)
06596974858612 05335045275926
minus05335071951242 01261956258061
Figure 9 Matrix exp(119860)
on the solution computed using both methods We observethat error obtained in the symbolic approximation is quitesmaller that the numeric oneThis fact can be better observedin Figure 13 where we show the difference in absolute valuebetween the exact solution and the symbolic and numericsolutions Nevertheless it is not the goal of this paper todevelop a numeric tool The symbolic technique we havedeveloped provides an analytical solution which can be used
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
14 Journal of Applied Mathematics
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 10 Comparison of real solution (black) and symbolicsolutions for119898 = 10 (light blue line) and119898 = 100 (yellow line)
minus15
minus1
minus05
0
05
1
15
0 2 4 6 8 10
Figure 11 Comparison of real solution (black) and symbolicsolutions for119898 = 1000 (dark blue line) and119898 = 10000 (green line)
0 2 4 6 8 10minus15
minus1
minus05
0
05
1
15
Figure 12 Exact solution (black) symbolic solution (blue) andnumeric solution (green)
Table 1 Numerical evolution of the symbolic approximation 119909119878(119905)
for119898 = 1000
Step 119905 119909(119905)
1 01 009516653368102 02 018133052249203 03 025948012999554 04 033058564791315 05 039559200286866 06 045541222101157 07 051092181897118 08 056295408367889 09 0612296198681210 10 06596861707192
Table 2 Numerical error in the symbolic (119909119878(119905)) and numeric
(119909119877(119905)) approximations with respect to the exact solution 119909(119905)
119905 |119909119878(119905) minus 119909(119905)| |119909
119877(119905) minus 119909(119905)|
01 00000047853239 0000000167203104 00000712453497 0000035875126707 00002074165163 0000354460586810 00003710415717 0001430787361713 00004547161744 0003825311783616 00003284030320 0008043689956219 00000622406880 0014419715717422 00006216534547 0023032955185125 00011277539714 0033667545654128 00013572764337 0045813471294231 00012347982225 0058707643120834 00008953272672 0071407807759437 00006002231245 0082889689449740 00005492334199 0092155687292443 00007154938930 0098343146001446 00008300921248 0100820433067849 00005487250652 0099260855115152 00002963137375 0093686827986155 00015298326576 0084479859363158 00026838757810 0072355393614361 00032571351779 0058304626062764 00030289419613 0043509187995267 00022189180928 0029236498885170 00013691340100 0016725709670673 00010043530807 0007075055562276 00012821439144 0001140917647379 00018689726696 0000541733952482 00021436005756 0002189733032385 00016148602301 0009108229122588 00002869277587 0019614707845191 00012796703448 0032789720352394 00022771057968 0047474001777797 00021518593816 00623710756305100 00009803998394 00761625070468
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Journal of Applied Mathematics 15
0 2 4 6 8 100
002
004
006
008
01
012
Figure 13 Error in the symbolic (black) and numeric (blue)approximations
as a kernel to apply perturbation methods to compute thesolution to a perturbed differential equation depending on asmall parameter
5 Conclusions
Wehave developed a symbolic processor as well as a symbolictechnique in order to deal with the solution to a linearordinary differential equation with constant coefficients oforder 119899The solution to this equation is computed completelyin a symbolic way that is the solution is expressed as afunction of 119905 This function can be of great interest to facea perturbed differential equation by means of a perturbationmethod The aim of this work is not to develop a numericmethod However we have compared the symbolic solutionobtained via our symbolic processor with a numeric solutioncomputed with a Runge-Kutta method in order to show howour solution is closer to the exact solution
References
[1] H Poincare Les Methodes Nouvelles de la Mecanique Celeste IGauthiers-Villars Paris France 1892
[2] J Henrard ldquoA survey of Poisson series processorsrdquo CelestialMechanics vol 45 no 1ndash3 pp 245ndash253 1989
[3] A Deprit J Henrard and A Rom ldquoLa theorie de la lune deDelaunay et son prolongementrdquo Comptes Rendus de lrsquoAcademiedes Sciences vol 271 pp 519ndash520 1970
[4] A Deprit J Henrard and A Rom ldquoAnalytical LunarEphemeris Delaunayrsquos theoryrdquo The Astronomical Journalvol 76 pp 269ndash272 1971
[5] J Henrard ldquoA new solution to the Main Problem of LunarTheoryrdquo Celestial Mechanics vol 19 no 4 pp 337ndash355 1979
[6] M Chapront-Touze ldquoLa solution ELP du probleme central dela Lunerdquo Astronomy amp Astrophysics vol 83 pp 86ndash94 1980
[7] M Chapront-Touze ldquoProgress in the analytical theories for theorbital motion of the Moonrdquo Celestial Mechanics vol 26 no 1pp 53ndash62 1982
[8] J F Navarro and J M Ferrandiz ldquoA new symbolic processorfor the Earth rotation theoryrdquo Celestial Mechanics amp DynamicalAstronomy vol 82 no 3 pp 243ndash263 2002
[9] J F Navarro ldquoOn the implementation of the Poincare-Lindstedttechniquerdquo Applied Mathematics and Computation vol 195 no1 pp 183ndash189 2008
[10] J F Navarro ldquoComputation of periodic solutions in perturbedsecond-order ODEsrdquo Applied Mathematics and Computationvol 202 no 1 pp 171ndash177 2008
[11] J F Navarro ldquoOn the symbolic computation of the solution to adifferential equationrdquo Advances and Applications in Mathemat-ical Sciences vol 1 no 1 pp 1ndash21 2009
[12] J F Navarro and A Perez ldquoPrincipal matrix of a linear systemsymbolically computedrdquo in Proceedings of the InternationalConference on Numerical Analysis and Applied Mathematics(ICNAAM rsquo08) pp 400ndash402 September 2008
[13] C Moler and C van Loan ldquoNineteen dubious ways to computethe exponential of a matrix twenty-five years laterrdquo SIAMReview vol 45 no 1 pp 3ndash49 2003
[14] J F Navarro and A Perez ldquoSymbolic computation of thesolution to an homogeneous ODE with constant coefficientsrdquoin Proceedings of the International Conference on NumericalAnalysis and AppliedMathematics (ICNAAM rsquo09) pp 400ndash4022009
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of