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Adaptive fuzzy output‐feedback tracking control for switched stochastic pure‐feedback nonlinear systems
Author(s) -
Chang Yi,
Wang Yuanqing,
Alsaadi Fuad E.,
Zong Guangdeng
Publication year - 2019
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3052
Subject(s) - control theory (sociology) , backstepping , observer (physics) , nonlinear system , fuzzy logic , tracking error , mathematics , fuzzy control system , bounded function , lyapunov function , adaptive control , computer science , control (management) , artificial intelligence , mathematical analysis , physics , quantum mechanics
Summary This paper considers the problem of adaptive fuzzy output‐feedback tracking control for a class of switched stochastic nonlinear systems in pure‐feedback form. Unknown nonlinear functions and unmeasurable states are taken into account. Fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy observer is designed to estimate the immeasurable states. Based on these methods, an adaptive fuzzy output‐feedback control scheme is developed by combining the backstepping recursive design technique and the common Lyapunov function approach. It is shown that all the signals in the closed‐loop system are semiglobally uniformly ultimately bounded in mean square in the sense of probability, and the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing appropriate parameters. Finally, a simulation result is provided to show the effectiveness of the proposed control method.