Adaptive fuzzy control of nonlinear systems in pure feedback form based on input-to-state stability

Authors:
Tian-Ping Zhang;Hui Wen;Qing Zhu
Affiliations:
Department of Automation, College of Information Engineering, Yangzhou University, Yangzhou, China;Department of Automation, College of Information Engineering, Yangzhou University, Yangzhou, China;Department of Automation, College of Information Engineering, Yangzhou University, Yangzhou, China
Venue:
IEEE Transactions on Fuzzy Systems
Year:
2010

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Abstract

Using mean value theorem and backstepping technique, a robust adaptive fuzzy control scheme is proposed for a class of pure-feedback nonlinear systems with unknown dead zone and disturbances via input-to-state stability. Takagi-Sugeno (T-S) type fuzzy logic systems are used to approximate the uncertain nonlinear functions and fewer learning parameters need to be adjusted online. Based on small gain theorem, the closed-loop control system is proven to be semiglobally uniformly ultimately bounded, and the tracking error converges to a neighborhood of zero by choosing appropriate parameters. Simulation results demonstrate the effectiveness of the control scheme.