Adaptive Fuzzy Finite-Time Tracking Control of Stochastic High-Order Nonlinear Systems With a Class of Prescribed Performance

This article investigates the adaptive fuzzy finite-time control problem for a class of high-order stochastic nonlinear systems with a class of exponential type prescribed performance function. It is assumed that the nonlinear functions in the controlled plant are unknown, in which fuzzy logic syste...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems Vol. 30; no. 1; pp. 88 - 96
Main Authors: Fu, Zhumu, Wang, Nan, Song, Shuzhong, Wang, Tong
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive control
Adaptive fuzzy control
Adaptive systems
Approximation
Backstepping
Continuity (mathematics)
Error signals
Fuzzy control
Fuzzy logic
fuzzy logic systems (FLSs)
Fuzzy systems
Lyapunov methods
Mathematical analysis
Nonlinear systems
stochastic nonlinear systems
Stochastic processes
Stochastic systems
Tracking control
ISSN:1063-6706, 1941-0034
Online Access:Get full text
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Summary:This article investigates the adaptive fuzzy finite-time control problem for a class of high-order stochastic nonlinear systems with a class of exponential type prescribed performance function. It is assumed that the nonlinear functions in the controlled plant are unknown, in which fuzzy logic systems (FLSs) are utilized due to the approximation ability of any unknown continuous functions with arbitrary approximation errors. Based on the FLSs and backstepping design technique, a novel adaptive fuzzy tracking control strategy is proposed to guarantee that the closed-loop nonlinear system is semiglobally finite-time stable in probability via Lyapunov stability theory and It<inline-formula><tex-math notation="LaTeX">\hat{o}</tex-math></inline-formula> formula. Compared with existing results, the transformed error signal was regarded as a stochastic variable. In addition, the expressions of the first and second-order partial derivatives of the transformed error signals are given in this article. Finally, a simulation example with different covariance values is given to show the effectiveness of the proposed control strategy.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.3032776