Robust fuzzy tracking control of nonlinear systems with uncertainty via t-s fuzzy model

Authors:
Jian Zhang;Minrui Fei;Taicheng Yang;Yuemei Tan
Affiliations:
Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China;Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China;Department of Engineering, University of Sussex, Brighton, UK;Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China
Venue:
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Year:
2006

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Abstract

This paper presents a novel robust fuzzy tracking control method for uncertain nonlinear systems. The Takagi-Sugeno fuzzy model is employed for fuzzy modeling of uncertain nonlinear system. Based on the fuzzy model, the internal model principle (IMP) is adopted to design the robust fuzzy tracking controller. Then the robust fuzzy observer is designed independently. Sufficient conditions are derived for stabilization of the robust fuzzy tracking controller and the robust fuzzy observer in the sense of Lyapunov asymptotic stability. The main contribution of this paper is the development of the robust fuzzy tracking control based on the internal model principle of uncertain nonlinear systems. A simulation example is given to illustrate the design procedures and asymptotic tracking performance of the proposed method.