me677c6 frequencyanalysis t
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Frequency Domain Analysis Lecture Notes by B.Yao
1
Frequency Domain Analysis of Feedback Systems System:
, ( , )
x Ax Buy Cx Du u t y
Assume (A, B) is controllable and (A, C) is observable. Sector Bounded Nonlinearities: A memoryless function : [0, ] p pR R is said to belong to the sector
[0 ∞] if ( , ) 0Ty t y
[ 1K ∞] if 1[ ( , ) ] 0Ty t y K y
2[0 ]K if 2[ ( , ) ] ( , ) 0Tt y K y t y where 2 2 0TK K
1 2[ ]K K with 2 1TK K K K if
1 2[ ( , ) ] [ ( , ) ] 0Tt y K y t y K y
SISO Illustration
-0r )(sG
( )
u y-
0r )(sG
( )
u y
y0
1K y
K
2K y
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Frequency Domain Analysis Lecture Notes by B.Yao
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Absolute Stability: The above system is absolutely stable if the origin is globally uniformly asymptotically stable for any nonlinearity in the given sector. It is absolutely stable with a finite domain if the origin is uniformly asymptotically stable.
Circle Criterion: THEOREM 7.1:
The system is absolutely stable if 1
1 1[ , ) and ( ) [1 ( )]K G s K G s is SPR 1 2 2 1[ , ] with 0TK K K K K K , and 1
2 1[1 ( )][1 ( )]K G s K G s is SPR. If the sector condition is satisfied only on a set pY R then the above conditions ensure that the system is absolutely stable within a finite domain. #
Proof: For simplicity, only prove the theorem for [0, ] . For this case, 1 0K and G(s) is SPR by assumption. Then, by KYP lemma, 0TP P , L, W, and
0 such that T TPA A P L L P
T TPB C L W T TW W D D
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Frequency Domain Analysis Lecture Notes by B.Yao
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Choose 1( ) .2
TV x x Px Then,
1 12 2
T T T T T T T TV x Px x Px x P Ax x P Bu x A Px u B Px
1 ( )2
T T Tx PA A P x x PBu
1 [ ]2 2
T T T T T Tx L Lx x Px x C L W u
( )
1 12 2 T
T T T T T T T
y Du
x L Lx x Px x C u x L Wu
1 12 2
T T T T T T Tx Px x L Lx x L Wu u Du y u
Noting 1 1( )2 2
T T T T Tu Du u D D u u W Wu , the above equation becomes
1 12 21 0, 0, as ( , ) 02
TT T
T T T
V x Px Lx Wu Lx Wu y u
x Px x y u y t y
which indicates that the origin is exponentially stable. #
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Frequency Domain Analysis Lecture Notes by B.Yao
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SISO Systems:
Absolutely stable if 1 2 2 1[ ],k k k k and 2
1
1 ( )( )1 ( )
k G sZ sk G s
is SPR. #
Q: Can we check the SPR of Z(s) based on FR ( )G j only? A: Yes as follows As Z(s) is biproper, Z(s) is SPR if Z(s) is Hurwitz and Re ( ) 0,Z j Case 1: 2 1 0k k
(a) 2 2
1
1
1 ( )1 ( )Re 0 Re 011 ( ) ( )
G jk G j kk G j G j
k
the angle between 2
1 ( )G jk
and 1
1 ( )G jk
is less than 90 , i.e.,
2 1 90 the point ( )G j is outside the disk 1 2( , )D k k
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Frequency Domain Analysis Lecture Notes by B.Yao
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Nyquist plot of ( )G j must be strictly outside the disk 1 2( , )D k k .
0
( )G j
1
1k
2
1k
1 2,D k k
2
1( )G jk
1
1( ) ( )G jk
(b) Z(s) is Hurwitz 1
1
( )1 ( )
k G sk G s
is Hurwitz.
Nyquist plot of ( )G j does not intersect 1
1k
and encircles it exactly
the same number of times pN in the counterclockwise direction as the number of unstable poles of G(s).
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Frequency Domain Analysis Lecture Notes by B.Yao
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(a) + (b)
Absolutely stable if the Nyquist plot of ( )G j does not enter the disk 1 2( , )D k k and encircles it pN times in the counter clock direction.
Case 2: 2 1 0k k 2( ) 1 ( )Z s k G s
(a) ( )Z s is Hurwitz G(s) is Hurwitz.
(b) 2Re ( ) Re 1 ( ) 0Z j k G j 2
1Re{ ( }G jk
Absolutely stable condition for Case 2:
G(s) is Hurwitz and the Nyquist plot lies to the right of the vertical line defined by
2
1Re[ ]sk
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Frequency Domain Analysis Lecture Notes by B.Yao
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Case 3: 1 20k k
The same as Case 1 except with the following changes:
(a) 2
1
1 ( )Re { ( } 0 Re 01 ( )
G jkZ j
G jk
Thus, the absolute stability condition is changed to:
Absolute stable if G(s) is Hurwitz and the Nyquist plot of ( )G j lies in the interior of the disk 1 2( , ).D k k
0
( )G j
1
1k
2
1k
1 2,D k k
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Frequency Domain Analysis Lecture Notes by B.Yao
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Popov Criterion System:
, (A, B) is controllable and (A, C) is observable
( ), 1 , time-invariant nonlinearitiesi i i
x Ax Buy Cxu y i p
Assume [0, ]i ik .
Theorem 7.3: The above system is absolutely stable if, for 1 , [0, ], 0i i ii p k k , and there exist constants 0i with (1 ) 0k i for every eigenvalue k of A such that ( ) ( )M I s G s is SPR where 1diag{ , , }p and
1
1 1diag , ,p
Mk k
. #
Proof:
Construct the following Lyapunov function and apply Lyapunov Theorems:
01
1 ( )2
ip yT
i ii
V x Px d
where 0P is the matrix in KYP Lemma for the SPR TF. #
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Frequency Domain Analysis Lecture Notes by B.Yao
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SISO Case:
Absolutely stable for [0, ]k if 0 with (1 ) 0, ,j j and 1( ) (1 ) ( )Z s s G sk
is SPR.
Z(s) is SPR 1 (a) G(s) is Hurwitz, and
(b) 1 Re 1 ( ) 0, [ , ]j G jk
(b) is equivalent to
1 Re Re{ } Im{ } Re{ } Im{ } 0G j G j G Gk
1 Re { ( )} Im{ ( )} 0G j G jk
which indicates that the system is absolutely stable if the Popov plot stays to the right of the line in the following figure.
1 For simplicity, assume k to avoid the special SPR condition for ( )Z s when its relative degree is not zero.
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Frequency Domain Analysis Lecture Notes by B.Yao
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Popov Plot:
0
1k
Im ( )G j
1slope
For SISO systems, the system is absolutely stable if the Popov plot stays to the right of the line passing through the point 1
k with a slope of 1 .
Note:
When 0 , the Popov Stability Condition reduces to Circle Criterion.
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Frequency Domain Analysis Lecture Notes by B.Yao
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Describing Function Method Goal:
Study the existence of periodic solutions of free response for the following system: where ( ) is a time-invariant, memoryless nonlinearity.
Method of Harmonic Balancing
Idea: represent a periodic solution by a Fourier series and seek a frequency ω and a set of Fourier coefficients that satisfy the system equation.
Assume:
2( ) ( ),y t y t T T
then
( ) j ktk
ky t a e
(D1)
-0r )(sG
( )
u y-
0r )(sG
( )
u y
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Frequency Domain Analysis Lecture Notes by B.Yao
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where
0
1 ( )T jk t
k ka a y t e dtT
As ( ) is time-invariant, ( ( )) ( ( ))y t y t T is also periodic with the same frequency:
( ( )) jk tk
ky t c e
(D2)
where
0
1 ( ( ))
( ), 0, 1, 2,
T jk tk
k i
c y t e dtTc a i
(D3)
Let ( )( )( )
N sG sD s
. Then, for (D1) and (D2) to be a solution of the CL system, it
is required that they satisfy the differential equation as
( ) [ ( )] ( ) [ ]N p y D p y (D4) As
jk tk
k
dp y y a jk edt
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Frequency Domain Analysis Lecture Notes by B.Yao
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[ ( )] [ ( )] jk tk
k
dp x y y c jk edt
(D4) is the same as:
( ) ( )jk t jk tk k
k k
D jk a e N jk c e
(D5)
Use the orthogonality of the basis function jk te for different value of k, i.e.,
1 2 1 2
01 2
011
T jk t jk t k ke e dt
k kT
(D5) is the same as:
( ) ( ) 0,( ) 0 ,
( ) 0 , 0
k k
k k
k k
D jk a N j k c kG jk c a k
G jk c a k
(D6)
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Frequency Domain Analysis Lecture Notes by B.Yao
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Finite Dimension Approximation
Assume G(s) is strictly proper. Then, ( ) 0G j as . So assume that there is an integer q > 0 such that k q , ( ) 0G jk . Then (D6) becomes:
ˆ ˆ( ) 0 , 0,1, 2, ,k kG jk c a k q (D7) which is still a very difficult task to carry out.
Describing Function Approximation
Choose q=1 and neglect all higher harmonies, i.e., assume 0, 0, 2k kc a k . Then (D7) becomes:
0 0 1 0
1 0 1 1
ˆ ˆ ˆ ˆ(0) , 0
ˆ ˆ ˆ ˆ( ) , 0
G c a a a
G j c a a a
(D8)
which has four unknowns: 1ˆ ˆ, , complexoa a , but only three equations. This is reasonable as the time origin of a periodic solution is not defined. So assume that first harmonic of y(t) to be of sinA t :
11ˆ ˆ( ) sin2 2 2 2
j t j t j t j tA A Ay t A t A e e e e aj j j j
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Frequency Domain Analysis Lecture Notes by B.Yao
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Conventionally, we define the describing function of a nonlinearity ( ) as:2
01
1
0
0 0
1 sinˆ( )
ˆ2
2 sin cos( ) sin
2 2 sin sin sin cos
T j t
T
T T
A t e dtc TN A Aaj
j A t t j t dtTA
jA t t dt A t t dtTA TA
Let t :
2 2
0 0
1 1( ) sin sin sin cosN A A d j A dA A
(D9)
With the above definition, (D8) becomes:
( ) ( ) 1 0G j N A (D10)
2 This equivalent gain concept (or equivalent linearization) can be generalized to general time-varying nonlinearities with memory, like hysteresis, in which the describing function might be complex and dependent on both Aand , i.e., ( , )N A
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Frequency Domain Analysis Lecture Notes by B.Yao
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Odd Nonlinearities:
0ˆ( ) ( ) 0y y c
From (D8), 0ˆ 0a . Furthermore, ( )N A is real given by:
0
2( ) sin sinN A A dA
(D10) becomes: 1( ) ( ) 1 0 ( )( )
G j N A G jN A
(D11)
which can be solved graphically:
0
( )G j 1
N A
A 0A
s
sA A
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Frequency Domain Analysis Lecture Notes by B.Yao
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0
1k
2k
0
0 t
sin( )y A t
Ex 7.7: Describing Function of Piece-wise Linear Function.
sinA 1sinA
0
2( ) ( sin )sinN A A dA
10
22 1
2 sin sin2
2 sin sin
k A d
A k A k d
1 22
211 2
2
2( ) cos
2( ) sin 1
k k kA
k k kA A A
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Frequency Domain Analysis Lecture Notes by B.Yao
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For saturation nonlinearity:
When 1 21 , 0k k :
2
1
1
2 sin 1 , for ( )
1, for
AN A A A A
k A
(D14)
For a dead-zone nonlinearity:
212
2
1
( )
2 sin 1 , for
0, for
N A
k k AA A A
k A
(D15)
0 1 0k
2k
0
1k
2 0k
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Frequency Domain Analysis Lecture Notes by B.Yao
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Ex 7.10
2( )0.8 8
sG ss s
2 2
2 2
0.8 (8 )( )0.64 (8 )
jG j
For odd nonlinearities, N(A) is real. Then, (D11) can be satisfied only for
2 2s
and 1 1( ) 0.8
( ) 1.25s
N AG j
If is the saturation nonlinearity with 1 , then, from (D14): 1.455A
If is a dead-zone non linearity with 2 0.5, 1k , then from (D15), no solution is found. This indicates that “probably” no periodic solution. This statement can be proved using the Circle Criterion as follows:
-1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1Nyquist Diagram
Real Axis
Imag
inar
y Ax
is
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Frequency Domain Analysis Lecture Notes by B.Yao
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Re ( ) 1.25,G j
The system is absolutely stable for any nonlinearity within the
sector 10, 0.8
1.25
.
As the dead-zone nonlinearity is within this sector, the origin is globally uniformly asymptotically stable. Therefore, no periodic solution exists.
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Frequency Domain Analysis Lecture Notes by B.Yao
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Ex 7.11 Consider Raleigh’s equation:
21 0v v v v
2( )1
sG ss s
, 2
2 2 2 2
(1 )( )
(1 )j
G j
3 3
0
22 2
0
2, ( ) ( sin ) sin
3 1 cos(2 )2 4
y y N A A dA
A d A
For odd nonlinearities, N(A) is real. Then, (D11) can be satisfied only for
1s and
1 1( ) 1( ) 1s
N AG j
2 / 3A
Thus, we expect that Raleigh’s equation has a periodic solution of frequency near 1 rad/sec and amplitude of oscillation in v around 2 / 3 .