Static Output Feedback Fuzzy Controller Design via a Mixed Approach for Regional T-S Fuzzy System

This paper proposes a Takagi-Sugeno (T-S) fuzzy region model to relax the original one. Such switching concept has got rid of Parallel Distributed Compensation (PDC) complicated analysis. By mixing genetic algorithm (GA) and linear matrix inequality (LMI), we present a new hybrid approach about the static output feedback controller design. It is unlike other researches that involve complicated mathematic transformations and system constraints. In this paper, we fix the static output feedback gains by GA to solve the non-convex problem. It is proved that the existence of a set of solvable non-linear matrix inequality (NLMI) suffices to guarantee the stabilization of T-S fuzzy region system. Numerical examples are given to illustrate the effectiveness of the algorithm and validate the new method.

[1]  Sushil J. Louis,et al.  Robust stability analysis of discrete-time systems using genetic algorithms , 1999, IEEE Trans. Syst. Man Cybern. Part A.

[2]  Wen-Jer Chang,et al.  LMI-based fuzzy controller design with minimum upper bound input energy and state variance constraints for discrete fuzzy stochastic systems , 2004, J. Intell. Fuzzy Syst..

[3]  Chein-Chung Sun,et al.  GA-based robust H/sub 2/ controller design approach for active suspension systems , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[4]  Kazuo Tanaka,et al.  Switching control of an R/C hovercraft: stabilization and smooth switching , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[5]  Kazuo Tanaka,et al.  Stability analysis and design of fuzzy control systems , 1992 .

[6]  Bor-Sen Chen,et al.  Mixed Fuzzy Output Feedback Control Design for Nonlinear Dynamic Systems: An LMI Approach , 2000 .

[7]  Bor-Sen Chen,et al.  Mixed H2/H∞ fuzzy output feedback control design for nonlinear dynamic systems: an LMI approach , 2000, IEEE Trans. Fuzzy Syst..

[8]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[9]  Ning Zhang,et al.  H2 Control design for fuzzy dynamic systems via LMI , 2000, J. Intell. Fuzzy Syst..

[10]  Wen-June Wang,et al.  Relaxed stability condition for T-S fuzzy discrete system , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[11]  Robert F. Stengel,et al.  Robust control system design using random search and genetic algorithms , 1997, IEEE Trans. Autom. Control..