Novel Adaptive Fuzzy Control for Output Constrained Stochastic Nonstrict Feedback Nonlinear Systems

A novel adaptive fuzzy control scheme is designed in this article for a class of stochastic nonstrict feedback nonlinear systems with output constraint and unknown control coefficients. A reduced adaptive fuzzy system is proposed to approximate the unknown function which contains all state variables...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2021-05, Vol.29 (5), p.1188-1197
Main Authors: Sun, Wei, Su, Shun-Feng, Wu, Yuqiang, Xia, Jianwei
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive systems
Constraints
Control design
Control methods
Design
Feedback
Fuzzy control
Liapunov functions
Mathematical analysis
MIMO communication
Nonlinear systems
Nonstrict feedback nonlinear systems
output constraint
Probability theory
stochastic systems
Tracking errors
unknown control coefficients
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Summary:A novel adaptive fuzzy control scheme is designed in this article for a class of stochastic nonstrict feedback nonlinear systems with output constraint and unknown control coefficients. A reduced adaptive fuzzy system is proposed to approximate the unknown function which contains all state variables of the whole system and ensures that the backstepping design method works normally for nonstrict feedback nonlinear systems. With the use of this reduced adaptive fuzzy control method and a combination of Barrier Lyapunov Function control design and Nussbaum gain technique, a novel adaptive fuzzy controller is proposed to guarantee that the output tracking error always meets the given constraint requirement in a sense of probability and the resulting closed-loop states are bounded in probability. Finally, an example is presented to confirm the effectiveness of the designed method.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.2969909