A unified approach to controlling chaos via an LMI-based fuzzy control system design

This paper presents a unified approach to controlling chaos via a fuzzy control system design based on linear matrix inequalities (LMI's). First, Takagi-Sugeno fuzzy models and some stability results are recalled. To design fuzzy controllers, chaotic systems are represented by Takagi-Sugeno fuzzy models. The concept of parallel distributed compensation is employed to determine structures of fuzzy controllers from the Takagi-Sugeno fuzzy models, LMI-based design problems are defined and employed to find feedback gains of fuzzy controllers satisfying stability, decay rate, and constraints on control input and output of fuzzy control systems. Stabilization, synchronization, and chaotic model following control for chaotic systems are realized via the unified approach based on LMIs. An exact linearization (EL) technique is presented as a main result in the stabilization. The EL technique also plays an important role in the synchronization and the chaotic model following control. Two cases are considered in the synchronization. One is the feasible case of the EL problem. The other is the infeasible case of the EL problem. Furthermore, the chaotic model following control problem, which is more difficult than the synchronization problem, is discussed using the EL technique. Simulation results show the utility of the unified design approach based on LMIs proposed in this paper.

[1]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  L. Chua,et al.  The double scroll family , 1986 .

[3]  E. Ott,et al.  Controlling Chaotic Dynamical Systems , 1991, 1991 American Control Conference.

[4]  S. Kawamoto,et al.  An approach to stability analysis of second order fuzzy systems , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[5]  Kestutis Pyragas Continuous control of chaos by self-controlling feedback , 1992 .

[6]  S. Singh Stability analysis of discrete fuzzy control system , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

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

[8]  Chieh-Li Chen,et al.  Analysis and design of fuzzy control system , 1993 .

[9]  Tadashi Yamashita,et al.  Graphical stability analysis of a fuzzy control system , 1993, Proceedings of IECON '93 - 19th Annual Conference of IEEE Industrial Electronics.

[10]  S. Farinwata,et al.  Stability analysis of the fuzzy logic controller designed by the phase portrait assignment algorithm , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[11]  Guanrong Chen,et al.  From Chaos to Order - Perspectives and Methodologies in Controlling Chaotic Nonlinear Dynamical Systems , 1993 .

[12]  Celso Grebogi,et al.  Using small perturbations to control chaos , 1993, Nature.

[13]  Kazuo Tanaka,et al.  Concept of stability margin for fuzzy systems and design of robust fuzzy controllers , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[14]  Stephen P. Boyd,et al.  Control System Analysis and Synthesis via Linear Matrix Inequalities , 1993, 1993 American Control Conference.

[15]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[16]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[17]  Ying-Cheng Lai,et al.  Controlling chaos , 1994 .

[18]  N. W. Rees,et al.  Analysis and design of fuzzy control systems , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[19]  Hua O. Wang,et al.  Bifurcation control of a chaotic system , 1995, Autom..

[20]  Kazuo Tanaka,et al.  Parallel distributed compensation of nonlinear systems by Takagi-Sugeno fuzzy model , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[21]  Reza Langari,et al.  Building Sugeno-type models using fuzzy discretization and orthogonal parameter estimation techniques , 1995, IEEE Trans. Fuzzy Syst..

[22]  S. Kawamoto,et al.  Nonlinear control and rigorous stability analysis based on fuzzy system for inverted pendulum , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

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

[24]  Kazuo Tanaka,et al.  Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H∞ control theory, and linear matrix inequalities , 1996, IEEE Trans. Fuzzy Syst..

[25]  Stephen Yurkovich,et al.  Fuzzy Control , 1997 .

[26]  Kazuo Tanaka,et al.  Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs , 1998, IEEE Trans. Fuzzy Syst..