Synchronization of Chaotic Systems Using Time-Delayed Fuzzy State-Feedback Controller

This paper presents the fuzzy-model-based control approach to synchronize two chaotic systems subject to parameter uncertainties. A fuzzy state-feedback controller using the system state of response chaotic system and the time-delayed system state of drive chaotic system is employed to realize the s...

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Bibliographic Details
Published inIEEE transactions on circuits and systems. I, Regular papers Vol. 55; no. 3; pp. 893 - 903
Main Authors Lam, H.K., Ling, Wing-Kuen, Iu, Herbert Ho-Ching, Ling, Steve S.H.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.04.2008
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Chaos
Chaos theory
Chaotic communication
Chaotic synchronization
Communication system control
Control systems
Delay effects
Dynamical systems
Dynamics
Fuzzy
Fuzzy control
Fuzzy logic
Fuzzy set theory
Fuzzy systems
Mathematical models
Programmable control
Stability
Studies
Systems stability
Takagi-Sugeno (T-S) fuzzy model
Uncertain systems
Chaotic Synchronization
Fuzzy Control
T-S Fuzzy Model transmission
Stability
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ISSN1549-8328
1558-0806
DOI10.1109/TCSI.2008.916430

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Summary:This paper presents the fuzzy-model-based control approach to synchronize two chaotic systems subject to parameter uncertainties. A fuzzy state-feedback controller using the system state of response chaotic system and the time-delayed system state of drive chaotic system is employed to realize the synchronization. The time delay which complicates the system dynamics makes the analysis difficult. To investigate the system stability and facilitate the design of fuzzy controller, Takagi-Sugeno (T-S) fuzzy models are employed to represent the system dynamics of the chaotic systems. Furthermore, the membership grades of the T-S fuzzy models become uncertain due to the existence of parameter uncertainties which further complicates the system analysis. To ease the stability analysis and produce less conservative analysis result, the membership functions of both T-S fuzzy models and fuzzy controller are considered. Stability conditions are derived using Lyapunov-based approach to aid the design of fuzzy state-feedback controller to synchronize the chaotic systems. Simulation examples are presented to illustrate the merits of the proposed approach.
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ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2008.916430