Multiscale Chebyshev neural network identification and adaptive control for backlash-like hysteresis system
type: Item
instance of: scholarly article
title: Multiscale Chebyshev neural network identification and adaptive control for backlash-like hysteresis system
zbMATH Open document ID: 1405.93077
DOI: 10.1155/2018/1872493
author: Xuehui Gao
author: Ruiguo Liu
published in: Complexity
publication date: 2018-12-17T00:00:00Z
review text: Summary: An adaptive control based on a new Multiscale Chebyshev Neural Network (MSCNN) identification is proposed for the backlash-like hysteresis nonlinearity system in this paper. Firstly, a MSCNN is introduced to approximate the backlash-like nonlinearity of the system, and then, the Lyapunov theorem assures the identification approach is effective. Afterward, to simplify the control design, tracking error is transformed into a scalar error with Laplace transformation. Therefore, an adaptive control strategy based on the transformed scalar error is proposed, and all the signals of the closed-loop system are uniformly ultimately bounded (UUB). Finally, simulation results have demonstrated the performance of the proposed control scheme.
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93C40
Mathematics Subject Classification ID: 93C15
Mathematics Subject Classification ID: 93A14
zbMATH DE Number: 6994148
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/1872493
OpenAlex ID: W2894792450
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description: scientific article; zbMATH DE number 6994148