predictive functional control - scilab · jean piaget (1896 / 1980) swiss grand father of cognitive...

PREDICTIVE FUNCTIONAL

CONTROL

J.Richalet SCILAB 2014

WHO INVENTED

PREDICTIVE CONTROL ?

ERGONOMY OF FLIGHT CONTROL

n  In the fifties : n  How the pilot manages his aircraft ? n  What operating image ? n  Comparison between: n  Human control and Automatic control : SURPRISE ! ….

Jean Piaget (1896 / 1980)

n  Swiss Grand Father of Cognitive Psychology

n  How the child learns and controls his environment . Four phases ….!

–  OPERATING IMAGE –  TARGET – Sub TARGET –  ACTION –  COMPARISON BETWEEN

PREDICTED AND ACHIEVED RESULT

• NATURAL CONTROL : “ YOU DO NOT DRIVE YOUR CAR WITH A PID SCHEME”

-REFERENCE TRAJECTORY

-STRUCTURATION OF THE MV

-ERROR COMPENSATION

4 PIAGET BASIC PRINCIPLES

-INTERNAL MODEL

PREDICTIVE CONTROL

IS NOT

AN INVENTION

BUT A DISCOVERY ….!

DEFENCE Mine hunter Ariane 5 attitude control Missile autopilot Laser guided missile (t=62 microsecond…) Gun turrets Radar antennas Infra Red camera High speed Infra Red Missile launch Camera mount Radar antennas Laser mirror Tank turret (T. 55) Mine sweeper auto-pilot Aircraft carrier auto-pilot

AUTOMOTIVE Gear box test bench Dynamic test bench engine Fuel injection Idle fuel injection Clutch antistroke Gear box (tank) Hybrid car (electric-fuel) Air conditioning

METALLURGICAL INDUSTRIES Coating lines aluminium Thickness control - Roll eccentricity Mono-multi-stands Rolling mills

Continuous casting (slab) Push-ovens Coke furnace Hot/cold/Thin rolling mills Steam generators Level, temperature, pressure……;

MISCELLANEOUS (Chem reactors and distillation excluded) Bioreactor Melissa ESA Plastic extrusion robot (high speed) Temperature control of gas furnace Temperature control of TGV train carriage River dam level control (T=1 hour ) Powder milk dryer Electric furnace brazing etc….

FEATURES …the oldest MBPC… 1968 A “few” thousands applications in many fields

FIRST INDUSTRIAL APPLICATIONS OF P.F.C.

uy M

Ts + 1e s -G = P ==θ

y(n) = α y(n-1) + (1- α) . u(n-1-r) . G T

Tsamp- e = α

θ = Tsamp . r Trajectory expo. : λ

1 coincidence point: H

1 Base function: step Target : ΔP(n+H) = (C - yPr) (1 - λH)

Processus with delay : yPr (n) = yP (n) + yM (n) - yM(n-r)

Model : Free mode Forced mode (Liebniz 1674)

My (n) HαHu(n) . GM 1 - α

⎛ ⎞⎜ ⎟⎝ ⎠

Model increment :

M MPH H H(C - (n)) (1 - ) (n) + u(n) GM(1 - ) - (n)y y yr λ α α=

Control equation : H)+(nM H)+(nP Δ=Δ

Increment = Free(n+h) + Forced(n+h)- ymodel(n)

The only mathematical problem for trainees …!

ELEMENTARY TUTORIAL EXAMPLE

PrH(C - (n)) (1 - ) (n)yy Mu(n) + H GMGM(1 - )

λ

α=

0 20 40 60 80 100 1200

20

40

60

80

100

120TEMPERATURE DE MASSE

d°

min

92°

Tmax=108.4°

Tinit=42°

Figure 4

ON LINE ESTIMATOR of DISTURBANCES

Pert

R1

R2

Cons1 MV1 P SP

SP* M ≡ P MV2

Cons2=SP

+

+

B

+

+

Pert* -

+

0 10 20 30 40 50 60 70 80

0

20

40

60

80

100

120 ESTIMATION DE L‘EXOTHERMICITE

Tmasse/ Tmasseestimée

TS-TE

TS

EXOTHERMICITE

min

Figure 3

31

Reactant Flow

T1 Reactor

Cooler

Steam

T2

T4

T3 Heat

Exchanger

BASF BASF BASF

B A S F

15

R

T M F i , T i T e

R Reagent

¥

q ( F i ) T M + T M = T i .

1) Fi =ct / MV= Ti CV=TM / level 0 =Ti ? :PFC

2) Ti =ct (!) MV=Fi Parametric Control non linear :PPC

3) MV : Ti and Fi : Enthaplic control (power) :PPC+

4) MV : Pressure of reactor :PFC

4 CONTROL STRATEGIES OF BATCH REACTORS

.

.

❿❿ ❿ ❿ ➗ ❿

➗➗ ➗ ➗ ➗ ➗ ❿ ➗➛ ➛

➖➆ρ Δ➖➦➖➆ρ ρ➖➦

Batch Reactor : MV=Qf / CV= TM

DEGUSSA EVONIK

Qf

Tif

Tof

TM

Control PID Degussa / EVONIK

Datum | Name der Präsentation Seite | 17

time

tem

per

atu

re [

°C]

+/- 2 °C

39 different batches with PID

Control PFC Degussa / EVONIK

Datum | Name der Präsentation Seite | 18

time

tem

pera

ture

[°C]

32 different batches with PPC

+/- 0,2 °C

CONTINUOUS CASTING

Steel ladle 335 t , 1550 °C

tundish 60 t

Mould 850 - 2200 mm, Cool jacket

SP=70% PFC PFC

Steel level

rolling

Setpoint weight

t Stopper PFC

PI

position detection

nozzle A

A

Weight detection

capteur

IDENTIFICATION

- Ultra-low level test signals ! ! …. « I do want to see your test signal on the level ..!« - Set of harmonics signals Eigen function - High level Parallel filtering .- Different metal alloys

3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9

x 104

-20

-10

0

10

20

30

40

50

60

70

BULGING COMPLEX CONTROL

without with

STOPPER

Amp sinus

Bmp cosinus

Frequency reference

N*0.025 sec

3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9

x 104

-20

-10

0

10

20

30

40

50

60

70

3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9

x 104

-20

-10

0

10

20

30

40

50

60

70

BULGING COMPLEX CONTROL

without

BULGING COMPLEX CONTROL

without with

STOPPER

Amp sinus

Bmp cosinus

Frequency reference

N*0.025 sec

COMPLEX ALGEBRA PREDICTIVE CONTROL ?!

Bench test of pump gaskets - Flow : 35000 m3/h ….! ? - Pressure : 17.50 MPa - Temperature : 330 d°

PFC controller

PUMP

CONTROL ENVIRONMENT

Pressuriser

REACTOR

Steam generator

PFC control joints

Engine

Pump

: " Size : 10 m " Mass : 100 tons " Flow: ~35000 m3/h

Support

Bâche tamponROO1

Température T0

Vanne Chaud VC

Vanne Froid VF

TransmetteurPression

Température T5

Banc d’essaiTempérature T51

Surpresseur

T 31

T 30

TransmetteurDébit

TransmetteurDébit

PFC CHAUD

Convexité Echangeur Chaud

TEQ = L x T31 + ( 1 – L ) x T0

Prise en tendance de la température d’entrée

F(T0)

PFC FROIDConvexité Echangeur Froid

TEQ = L x T30 + ( 1 – L ) x T51

Prise en tendance de la température d’entrée

F(T51)

Logique de choix de l’action

(Chaud ou Froid)

T5 T0 T31

T5 T51 T30

Consigne de température

Régulation débit chaud

Régulation débit froid

Débit source chaude

Débit source froide

T0

T51

T5

T31

T30

PID

Essai A2si du 17 avril 2012 (673)

15,0

25,0

35,0

45,0

55,0

65,0

18:14:24 18:21:36 18:28:48 18:36:00 18:43:12 18:50:24 18:57:36 19:04:48

Temps (heures)

Tem

péra

ture

(°C

)po

sitio

n va

nne

(%)

PFC Essai A2si du 18 avril 2012 (676)

0,0

20,0

40,0

60,0

80,0

100,0

14:31:12 14:45:36 15:00:00 15:14:24 15:28:48 15:43:12 15:57:36 16:12:00 16:26:24

Temps (heures)

Tem

péra

ture

(°C)

posi

tion

vann

e (%

)

T Inj

Consigne

retard +3 mn

SANOFI VERTOLAY VITRY sur SEINE ARAMON MONTPELLIER KÖLN ELBEUF Training of staff: Transfer of Know How

SCILAB Process PFC program Control

CODE SCILAB // com_elem_kindergarten tf= 1500; w=1:1:tf; // temps // initialisation u=zeros(1,tf); tech=1; MV=u; CV=u; sm=u; DV=u; SP=u; r=200; // dynamiques du modèle et du processus, // constante de temps, gain : taum=35; am=exp(-tech/taum); bm=1-am; Km=1.7; taup=35; ap=exp(-tech/taup); bp=1-ap; Kp=1.7; TRBF=45; lh=1-exp(-tech*3/TRBF); //----------------------- for ii=2+r:1:tf, if ii<700 then DV(ii)= 0; else DV(ii)=20; end // perturbation SP(ii)=100; // point de consigne CV(ii)=ap*CV(ii-1)+bp*(Kp*MV(ii-1-r)+DV(ii)); // processus sm(ii)=am*sm(ii-1)+bm*Km*MV(ii-1); // modèle spred=CV(ii)+(sm(ii)-sm(ii-r))*1; // prédiction d=(SP(ii)-spred)*lh+sm(ii)*bm; MV(ii)=d/(Km*bm); // variable manipulée // contraintes if MV(ii)>70 then MV(ii)=70; end if MV(ii)>MV(ii-1)+4 then MV(ii)=MV(ii-1)+4; end if MV(ii)<MV(ii-1)-4 then MV(ii)=MV(ii-1)-4; end end //----------------------- scf(1); clf; plot(w,MV,'b',w,CV,'r',w,SP,'r',w,DV,'m'); a=gca(); a.grid=[1,1]; a.tight_limits="on"; a.data_bounds=[1,0;1500,150]; xlabel('sec'); xtitle('MV b, CV et SP r, DV m , R=200 !,.. contraintes : abs=60 / vitesse = 4');

Conclusion

n  Dissemination ? : where is the problem?: n  The technical and economic efficiency of PFC

is clearly demonstrated on many different processes

n  TEACHING PFC: n  Continuous education of : n  Teachers of technical schools n  Industrial operators n  Implementation of PFC in all new PLC’s is to be

continued