A Simplified Fuzzy Wavelet Neural Control for Nonlinear Systems With Quantized Inputs and Deferred Constraints

This article investigates a finite-time fuzzy quantized control problem for a class of nonlinear systems considering deferred constraints. Instead of the tracking errors themselves, the auxiliary error variables constructed via the shifting function are employed into nonlogarithm barrier Lyapunov fu...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on fuzzy systems Jg. 32; H. 3; S. 1504 - 1514
Hauptverfasser: Yue, Xiaohui, Zhang, Huaguang, Sun, Jiayue, Liu, Xin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.03.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Actuators
Adaptive systems
Artificial neural networks
Backstepping
Bandwidth
Constraints
Deferred constraints
Fuzzy control
Fuzzy logic
fuzzy/neural approximators
Liapunov functions
Neural networks
Nonlinear control
Nonlinear systems
Nonlinearity
Quantization (signal)
quantized control
Robust control
Scalars
Subsystems
Tracking errors
ISSN:1063-6706, 1941-0034
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This article investigates a finite-time fuzzy quantized control problem for a class of nonlinear systems considering deferred constraints. Instead of the tracking errors themselves, the auxiliary error variables constructed via the shifting function are employed into nonlogarithm barrier Lyapunov function to perform error constraints, not only making the restrictive conditions in initial phase be removed but also ensuring tracking errors to evolve within the preassigned regions after a given time. Then, to allow for a reduced computational cost concerning fuzzy/neural approximators, a single parameter updating based fuzzy wavelet neural network is devised to approximate the unknown nonlinearity acting on every subsystem. Furthermore, by using hysteresis quantizer to convert continuous control inputs into discrete scalars, a robust fuzzy quantized controller is synthesized with the aid of a novel quantization decomposition scheme, where the problem of constrained data bandwidth is successfully handled without involving chattering in control signals. Finally, simulations confirm the benefits and efficiency of the proposed method.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2023.3325450