Combined adaptive fuzzy control for uncertain MIMO nonlinear systems

Authors:
Ya-Qin Zheng;Yan-Jun Liu;Shao-Cheng Tong;Tie-Shan Li
Affiliations:
Department of Mathematics and Physics, Liaoning University of Technology, Jinzhou, China;Department of Mathematics and Physics, Liaoning University of Technology, Jinzhou, China;Department of Mathematics and Physics, Liaoning University of Technology, Jinzhou, China;Navigation College, Dalian Maritime University, Dalian, China and School of Naval Architecture, Ocean and Civil Engineering, Shanghai JiaoTong University, Shanghai, China
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

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Abstract

A combined adaptive fuzzy control method of a class of uncertain MIMO nonlinear systems is studied in this paper. In this method, the proposed controllers consist of two parts: the direct and indirect adaptive control terms. Compared with existing methods for controlling MIMO systems, this novel method can trade off fuzzy descriptions for control rules at the same time to achieve better adaptation properties and improve control effect. In addition, most methods need to assume that the minimum approximation error is required to satisfy the square-integrable condition. The method proposed in this paper doesn't need this assumption, and the effect of minimum approximation error could be removed by the adaptive compensation term. Based on Lyapunov stability theory, it can be ensured that all signals of closed-loop system are bounded, and the tracking errors converge to a small neighborhood around zero. Simulation results indicate the validity of the proposed method.