Adaptive Fuzzy Decentralized Dynamic Surface Control for Fractional-Order Nonlinear Large-Scale Systems

The aim of this article is to study a fuzzy-based decentralized adaptive control strategy for the nonstrict-feedback fractional-order nonlinear large-scale systems with unknown control directions. In each step of the recursive processes, the fuzzy logic systems are employed to identify unknown nonli...

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Bibliographic Details
Published inIEEE transactions on fuzzy systems Vol. 30; no. 8; pp. 3373 - 3383
Main Authors Zhan, Yongliang, Sui, Shuai, Tong, Shaocheng
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive backstepping control design
Adaptive control
adaptive fuzzy decentralized control
Algorithms
Backstepping
Control design
Decentralized control
dynamic surface control (DSC)
fractional-order nonlinear large-scale systems
Fuzzy control
Fuzzy logic
Fuzzy systems
Large-scale systems
Liapunov functions
Nonlinear control
Nonlinear systems
Process control
Tracking errors
unknown control direction
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Summary:The aim of this article is to study a fuzzy-based decentralized adaptive control strategy for the nonstrict-feedback fractional-order nonlinear large-scale systems with unknown control directions. In each step of the recursive processes, the fuzzy logic systems are employed to identify unknown nonlinear functions. To handle the difficulties caused by unknown control directions, a Nussbaum function technique is adopted. Furthermore, by introducing the dynamic surface control technique into the adaptive backstepping recursive design algorithm, a fuzzy-based decentralized adaptive control strategy is formulated. Both the stability of the controlled system and the convergence of the tracking errors are proved by constructing the fractional-order Lyapunov functions. Finally, the validity and effectiveness of the designed decentralized control scheme are confirmed via two simulation examples.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2021.3114746