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Neural Computing and Applications
Published in: Neural Computing and Applications 5/2023

19-10-2022 | Original Article

Disturbance-observer-based adaptive dynamic surface control for nonlinear systems with input dead-zone and delay using neural networks

Authors: Junchang Zhai, Huanqing Wang, Jiaqing Tao

Published in: Neural Computing and Applications | Issue 5/2023

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Abstract

Disturbance-observer-based adaptive neural control approach is proposed for nonlinear systems. Considering the effect caused by long input delay and dead-zone, a novel auxiliary system has been introduced to degrade the design difficult. Based on the auxiliary system, a novel disturbance observer is developed to estimate the unknown time-varying external disturbance and the approximation error. What is more, the priori knowledge on the boundary of the disturbance and approximation error is not required for the disturbance observer. The “explosion of complexity” problem has been overcome by using dynamic surface control (DSC) scheme. By combing DSC scheme with backstepping technique, an adaptive neural dynamic surface controller is correctly devised to improve the disturbance rejection performance of the closed-loop system. Finally, the simulations of two examples show the superiority of the proposed scheme.
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Metadata
Title
Disturbance-observer-based adaptive dynamic surface control for nonlinear systems with input dead-zone and delay using neural networks
Authors
Junchang Zhai
Huanqing Wang
Jiaqing Tao
Publication date
19-10-2022
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2023
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-022-07865-3

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