Chaos Control Part II Amir massoud Farahmand [email protected].
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Transcript of Chaos Control Part II Amir massoud Farahmand [email protected].
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Chaos ControlChaos ControlPart IIPart II
Chaos ControlChaos ControlPart IIPart II
Amir massoud FarahmandAmir massoud [email protected]@SoloGen.net
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Review• Why Chaos control?!
– THE BEGINNING WAS CHAOS!– Chaos is Fascinating!– Chaos is Everywhere!– Chaos is Important!– Chaos is a new paradigm shift in
science!
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Review IIWhat is it?!
• Nonlinear dynamics• Deterministic but looks stochastic• Sensitive to initial conditions (positive Bol
(Lyapunov) exponents)
• Strange attractors• Dense set of unstable periodic orbits
(UPO)• Continuous spectrum
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Review IIIChaos Control: Goals
• Stabilizing Fixed points• Stabilizing Unstable Periodic Orbits• Synchronizing of two chaotic
dynamics• Anti-control of chaos• Bifurcation control
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Review IVChaos Control: Methods
• Linearization of Poincare Map– OGY (Ott-Grebogi-York)
• Time Delayed Feedback Control• Impulsive Control
– OPF (Occasional Proportional Feedback)• Open-loop Control• Conventional control methods
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Chaos ControlConventional control
• Back-stepping– A. Harb, A. Zaher, and M. Zohdy, “Nonlinear recursive
chaos control,” ACC2002.
• Frequency domain methods– Circle-like criterion to ensure L2 stability of a
T-periodic solution subject to the family of T-periodic forcing inputs.
– M. Basso, R. Genesio, and L. Giovanardi, A. Tesi, “Frequency domain methods for chaos control,” 2000.
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Chaos ControlConventional + Chaotic• Taking advantage of inherit properties of
chaotic systems• Periodic Chaotic systems are dense (according
to Devaney definition)• Waiting for the sufficient time, every point of
the attractor will be visited.• If we are sufficiently close to the goal, turn-on
the conventional controller, else do nothing!– T. Vincent, “Utilizing chaos in control system design,”
2000.
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Chaos ControlConventional + Chaotic• Henon map• Stabilizing to the unstable fixed point• Locally optimal LQR design• Farahmand, Jabehdar, “Stabilizing Chaotic Systems with Small
Control Signal”, unpublished
12
2211
3.0)1(
14.1)1(
xkx
uxxkx
otherwise 0
x-x(k) )()(
* kKxku
Figure 1 Henon map
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Chaos ControlConventional + Chaotic
0 50 100-0.5
0
0.5
1
k
sta
tes
threshold = 1.0
0 50 100-1.5
-1
-0.5
0
0.5
k
contr
ol eff
ort
threshold = 1.0
0 50 100-2
-1
0
1
2
k
sta
tes
threshold = 0.1
0 50 100-0.02
-0.01
0
0.01
0.02
0.03
k
contr
ol eff
ort
threshold = 0.1
x1
x2
x1
x2
Figure 2. Sample response for two different attraction threshold
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 110
20
30
40
50
60
70
80
90
100
theta
Sett
ling t
ime
Figure 5. Settling time for different theta
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Chaos ControlConventional + Chaotic
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.05
0.1
0.15
0.2
0.25
0.3
0.35
theta
peak o
f u(t
)
Figure 3. Peak of control signal for different theta
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
thetaenerg
y o
f u(t
)
Figure 4. Controlling energy for different theta
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Chaos Control• Impulsive control of periodically forced chaotic
system• Z. Guan, G. Chen, T. Ueta, “On impulsive control of
periodically forced pendulum system,” IEEE T-AC, 2000.
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Anti-Control of ChaosDefinitions and Applications
(I)• Anti-control of chaos
(Chaotification) is– Making a non-chaotic system,
chaotic.– Enhancing chaotic properties of a
chaotic system.
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Anti-Control of Chaos Definition and Applications (II)
• Stability is the main focus of traditional control theory.
• There are some situations that chaotic behavior is desirable– Brain and heart regulation– Liquid mixing– Secure communication– Small control (Chaotification of non-chaotic
system chaos control method (small control) conventional methods )
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Anti-Control of Chaos Discrete case (I)
Suppose we have a LTI system. If we change its dynamic with a proper feedback such that it
1. is bounded2. has positive Lyapunov exponent
then we may have made it chaotic.
We may use Marotto theorem to prove the existence of chaos in the sense of Li and Yorke.
X. Wang and G. Chen, “Chaotification via arbitrarily small feedback controls: theory, methods, and applications,” 2000.
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Anti-Control of Chaos Discrete case (II)
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Anti-Control of Chaos Discrete case (III)
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Anti-Control of ChaosContinuous case (I)
• Approximating a continuous system by its time-delayed version (Discrete map).
• Making a discrete dynamics chaotic is easy.
• It has not been proved yet!• X. Wang, G. Chen, X. Yu, “Anticontrol of chaos in
continuous-time systems via time-delayed feedback,” 2000.
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Anti-Control of ChaosContinuous case (II)
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• Carrier Clock, Secure communication, Power systems and …
• Formulation:
• Synchronization– Unidirectional (Model Reference Control)– Mutual
Synchronization(I)
k1,...,i ,),,...,,(x : 21i txxxFS kii
k1,...,i ,0),,...,( 11txxQ ki k k1,...,i ,0),,...,(lim 11
txxQ kit k
)()(),( 2121 txtxxxQ
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Synchronization(II)
• Linear coupling
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Synchronization(III)
• Drive-Response concept of Pecora-Carroll
• L.M. Pecora and T.L. Carol, “Synchronization in chaotic systems,” 1990.
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Synchronization of Semipassive systems
(I)• A. Pogromsky, “Synchronization and adaptive
synchronization in semipassive systems,” 1997.
• Semipassive Systems
t
t
dxHyuttxVttxV0
))(()(),(),(),( 00
0)(x ;0 xH
Isidori normal form 1,2i ),(
),(),(
iii
iiiiiii
yzqz
uyzbyzay
• Control Signal
211 yyu
,
12 uu
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Synchronization of Semipassive systems
(II)• Lemma: Suppose that previous
systems are semipassive with radially unbounded continuous storage function. Then all solutions of the coupled system with following control exist on infinite time interval and are bounded.
0)( yyT
)()( yy
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Synchronization of Semipassive systems
(III)• Theorem I: Assume that
– A1. The functions q, a, b are continuous and locally Lipschitz– A2.The system is semipassive– A3.There exist C2-smooth PD function V0 and … that
– A4.The matrix b1+b2 is PD:
– A5.
then there exist … that goal of synchronization is achieved.
2
211211210 ),(),()( zzyzqyzqzzV T
0,),(),( 222111 mIyzbyzb
2)( yyyT
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Synchronization of Semipassive systems
(IV)• Lorenz system (Turbulent dynamics of the
thermally induced fluid convection in the atmosphere)
0 5 10 15 20 25-600
-500
-400
-300
-200
-100
0
100
T
erro
r(dB
)
0 5 10 15 20 25-100
-80
-60
-40
-20
0
20
40
60
80
100
T
cont
rol e
ffor
t
Figure 1. error and control signal for linearly coupled system