An optimal T-S model for the estimation and identification of nonlinear functions
WSEAS Transactions on Systems and Control
Quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems
Expert Systems with Applications: An International Journal
New optimal approach for the identification of Takagi-Sugeno fuzzy model
CONTROL'08 Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control
Improved global asymptotical synchronization of chaotic Lur'e systems with sampled-data control
IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE Transactions on Fuzzy Systems
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This paper presents an adaptive approach for synchronization of Takagi-Sugeno (T-S) fuzzy chaotic systems. T-S fuzzy model can represent a general class of nonlinear system and we employ it for fuzzy modeling of the chaotic drive system. Since the output of the drive system is only available for synchronization, the response system is designed based on fuzzy adaptive observer for uncertain parameters and parameter mismatch cases. We analyze the stability of the overall fuzzy synchronization system by applying Lyapunov stability theory and derive stability conditions by solving linear matrix inequalities (LMIs) problem. The adaptive law is derived to estimate the uncertain parameters or parameter mismatch. Numerical examples are given to demonstrate the validity of the proposed fuzzy adaptive synchronization approach.