Reduced Adaptive Fuzzy Tracking Control for High-Order Stochastic Nonstrict Feedback Nonlinear System With Full-State Constraints

This paper focuses on the design of a reduced adaptive fuzzy tracking controller for a class of high-order stochastic nonstrict feedback nonlinear systems with full-state constraints. In the proposed approach, reduced fuzzy systems are used to approximate uncertain functions which involve all state...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2021-03, Vol.51 (3), p.1496-1506
Main Authors: Sun, Wei, Su, Shun-Feng, Dong, Guowei, Bai, Weiwei
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive systems
Backstepping
Barrier Lyapunov function (BLF)
Control design
Feedback
full-state constraints
Fuzzy control
Fuzzy systems
high-order stochastic nonlinear system
Liapunov functions
Mathematical analysis
Nonlinear systems
nonstrict feedback
reduced adaptive fuzzy control
Tracking control
Tracking errors
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Summary:This paper focuses on the design of a reduced adaptive fuzzy tracking controller for a class of high-order stochastic nonstrict feedback nonlinear systems with full-state constraints. In the proposed approach, reduced fuzzy systems are used to approximate uncertain functions which involve all state variables and a high-order tan-type barrier Lyapunov function (BLF) is considered to deal with full-state constraints of the controlled system. With this BLF and a combination of the reduced fuzzy control and adding a power integrator, a novel control scheme is constructed to ensure that tracking error is within a very small range of the origin almost surely, meanwhile, the constraints on the system states are not breached almost surely during the operation. Two examples are proposed to show the effectiveness of the design scheme.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2019.2898204