Finite-Time Adaptive Fuzzy Output Feedback Dynamic Surface Control for MIMO Nonstrict Feedback Systems

This paper investigates the finite-time adaptive fuzzy control problem for a class of multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems. During the control design process, fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and fuzzy state o...

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Vydáno v:IEEE transactions on fuzzy systems Ročník 27; číslo 1; s. 96 - 110
Hlavní autoři: Li, Yongming, Li, Kewen, Tong, Shaocheng
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.01.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptive control
Adaptive fuzzy control
Control stability
dynamic surface control (DSC)
finite-time stability
Fuzzy control
Fuzzy logic
Fuzzy systems
MIMO (control systems)
MIMO communication
multi-input and multi-output (MIMO) nonstrict nonlinear systems
Nonlinear systems
Output feedback
Process control
Stability criteria
State observers
Tracking errors
ISSN:1063-6706, 1941-0034
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Shrnutí:This paper investigates the finite-time adaptive fuzzy control problem for a class of multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems. During the control design process, fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and fuzzy state observer is constructed to estimate the unmeasured states. By combining adaptive backstepping with the dynamic surface control (DSC) technique, a finite-time fuzzy adaptive control scheme is presented to overcome the "explosion of complexity" problem. The stability of the close-loop systems can be proved based on the finite-time Lyapunov stability theory. The presented control scheme demonstrates that the closed-loop systems are semiglobal practical finite-time stability, and tracking errors converge to a small neighborhood of the origin in a finite time. Finally, two simulation examples are provided to show the effectiveness of the presented control method.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2018.2868898