Robust Adaptive Fuzzy Control via State-Dependent Function for Nonlinear Stochastic Large-Scale Systems Subject to Dead Zones

This paper concentrates on the adaptive fuzzy control problem for stochastic nonlinear large-scale systems with constraints and unknown dead zones. By introducing the state-dependent function, the constrained closed-loop system is transformed into a brand-new system without constraints, which can re...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2021; no. 1
Main Authors Zhu, Chang-Qi, Liu, Lei
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 2021
John Wiley & Sons, Inc
Wiley
Subjects
Adaptive control
Algebra
Constraints
Control algorithms
Design
Feedback control
Fuzzy control
Fuzzy logic
Fuzzy systems
Neural networks
Nonlinear systems
Robust control
Tracking errors
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Summary:This paper concentrates on the adaptive fuzzy control problem for stochastic nonlinear large-scale systems with constraints and unknown dead zones. By introducing the state-dependent function, the constrained closed-loop system is transformed into a brand-new system without constraints, which can realize the same control objective. Then, fuzzy logic systems (FLSs) are used to identify the unknown nonlinear functions, the dead zone inverse technique is utilized to compensate for the dead zone effect, and a robust adaptive fuzzy control scheme is developed under the backstepping frame. Based on the Lyapunov stability theory, it is proved ultimately that all signals in the closed-loop system are bounded and the tracking errors converge to a small neighborhood of the origin. Finally, an example based on an actual system is given to verify the effectiveness of the proposed control scheme.
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ISSN:1076-2787
1099-0526
DOI:10.1155/2021/1491995