Low Effort Control for Chaotic Systems via a Fuzzy Model-Based Approach

Authors:	Lian Kuang-Yow, Chung-Yuan Christian University, Taiwan Liou Jeih-Jang, Chung-Yuan Christian University, Taiwan
Topic:	3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.)
Session:	Soft Computing for Control
Keywords:	Low effort control, T-S fuzzy model, Chaotic systems

Abstract

In this paper, we propose a low effort control scheme for chaotic systems by using fuzzy model-based design method. First, we represent nonlinear systems into T-S fuzzy models in a working region covering the point to be regulated. The stability condition of the overall system is formulated into linear matrix inequalities (LMIs). Then, the control gains are obtained by solving a set of LMIs. To guarantee the stability, the region of attraction is also investigated. According to topologically transitive property for chaotic systems, the feedback control force is activated only when the trajectory passes through the neighboring region of the regulated point. Compared to purely fuzzy model-based controller, the control force for the fuzzy-chaos hybrid controller is extremely low.