Adaptive Fuzzy Control for a Class of Stochastic Strict Feedback High-Order Nonlinear Systems With Full-State Constraints

In this article, the problem of adaptive fuzzy control for stochastic high-order nonlinear systems with full-state constraints of the strict-feedback structure was investigated. The unknown nonlinear functions are approximated by using fuzzy logic systems (FLSs) at each step. By introducing the barr...

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Bibliographic Details
Published inIEEE transactions on systems, man, and cybernetics. Systems Vol. 52; no. 1; pp. 205 - 213
Main Authors Wang, Nan, Tao, Fazhan, Fu, Zhumu, Song, Shuzhong
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive control
Adaptive fuzzy control
Adaptive systems
Backstepping
Constraint modelling
Feedback
Fuzzy control
Fuzzy logic
fuzzy logic system (FLS)
Fuzzy systems
Nonlinear dynamical systems
Nonlinear systems
stochastic nonlinear systems
Stochastic systems
Suspensions (mechanical systems)
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Summary:In this article, the problem of adaptive fuzzy control for stochastic high-order nonlinear systems with full-state constraints of the strict-feedback structure was investigated. The unknown nonlinear functions are approximated by using fuzzy logic systems (FLSs) at each step. By introducing the barrier Lyapunov functional candidate, a novel adaptive fuzzy backstepping control strategy is proposed to solve the control problem of stochastic nonlinear systems with full-state constraints. Finally, a numerical simulation example is given to show the effectiveness of the proposed control strategy.
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2020.2996635