Adaptive Approximation-Based Tracking Control for a Class of Unknown High-Order Nonlinear Systems With Unknown Powers

In this article, the problem of adaptive tracking control is tackled for a class of high-order nonlinear systems. In contrast to existing results, the considered system contains not only unknown nonlinear functions but also unknown rational powers. By utilizing the fuzzy approximation approach toget...

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Bibliographic Details
Published in:IEEE transactions on cybernetics 2022-06, Vol.52 (6), p.4559-4573
Main Authors: Liu, Yong-Hua, Liu, Yang, Liu, Yu-Fa, Su, Chun-Yi, Zhou, Qi, Lu, Renquan
Format: Article
Language:English
Subjects:
Adaptive approximation-based control
Adaptive control
Approximation
Artificial neural networks
barrier Lyapunov function (BLF)
Control systems
Fuzzy logic
global stability
high-order nonlinear systems
Liapunov functions
Lyapunov methods
Mathematical analysis
Nonlinear systems
Tracking control
unknown powers
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Summary:In this article, the problem of adaptive tracking control is tackled for a class of high-order nonlinear systems. In contrast to existing results, the considered system contains not only unknown nonlinear functions but also unknown rational powers. By utilizing the fuzzy approximation approach together with the barrier Lyapunov functions (BLFs), we present a new adaptive tracking control strategy. Remarkably, the BLFs are employed to determine a priori the compact set for maintaining the validity of fuzzy approximation. The primary advantage of this article is that the developed controller is independent of the powers and can be capable of ensuring global stability. Finally, two illustrative examples are given to verify the effectiveness of the theoretical findings.
ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2020.3030310