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Adaptive neural network finite‐time command filter tracking control for nonlinear systems with multiple coupling high‐order terms and disturbances

Adaptive neural network finite‐time command filter tracking control for nonlinear systems with... This paper is devoted to the research of adaptive command filter tracking control for a class of uncertain nonlinear systems. The coexistence of multiple coupling high‐order terms, uncertain external disturbances, and unknown time‐varying coefficients makes the studied system more general compared with the existing results. By skillfully combining adaptive technology, command filter control, and backstepping method, a new type of adaptive command filter tracking control algorithm is designed. This controller not only solves the problem of complex explosion but also introduces compensation signals to achieve a higher precision tracking effect. Ultimately, the validity of the control algorithm is verified by a numerical simulation and a practical application model simulation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal of Control Wiley

Adaptive neural network finite‐time command filter tracking control for nonlinear systems with multiple coupling high‐order terms and disturbances

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References (32)

Publisher
Wiley
Copyright
© 2023 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd
ISSN
1561-8625
eISSN
1934-6093
DOI
10.1002/asjc.3105
Publisher site
See Article on Publisher Site

Abstract

This paper is devoted to the research of adaptive command filter tracking control for a class of uncertain nonlinear systems. The coexistence of multiple coupling high‐order terms, uncertain external disturbances, and unknown time‐varying coefficients makes the studied system more general compared with the existing results. By skillfully combining adaptive technology, command filter control, and backstepping method, a new type of adaptive command filter tracking control algorithm is designed. This controller not only solves the problem of complex explosion but also introduces compensation signals to achieve a higher precision tracking effect. Ultimately, the validity of the control algorithm is verified by a numerical simulation and a practical application model simulation.

Journal

Asian Journal of ControlWiley

Published: Nov 1, 2023

Keywords: command filter; multiple coupling high‐order terms; radial basis function‐neural networks (RBF); tracking control; uncertain nonlinear systems; unknown time‐varying coefficients

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