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Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation
A bilateral neural network adaptive controller is designed for a class of teleoperation systems with constant time delay, external disturbance and internal friction. The stability of the teleoperation force feedback system with constant communication channel delay and nonlinear, complex, and uncerta...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623693/ https://www.ncbi.nlm.nih.gov/pubmed/34833523 http://dx.doi.org/10.3390/s21227443 |
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author | Wang, Yaxiang Tian, Jiawei Liu, Yan Yang, Bo Liu, Shan Yin, Lirong Zheng, Wenfeng |
author_facet | Wang, Yaxiang Tian, Jiawei Liu, Yan Yang, Bo Liu, Shan Yin, Lirong Zheng, Wenfeng |
author_sort | Wang, Yaxiang |
collection | PubMed |
description | A bilateral neural network adaptive controller is designed for a class of teleoperation systems with constant time delay, external disturbance and internal friction. The stability of the teleoperation force feedback system with constant communication channel delay and nonlinear, complex, and uncertain constant time delay is guaranteed, and its tracking performance is improved. In the controller design process, the neural network method is used to approximate the system model, and the unknown internal friction and external disturbance of the system are estimated by the adaptive method, so as to avoid the influence of nonlinear uncertainties on the system. |
format | Online Article Text |
id | pubmed-8623693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86236932021-11-27 Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation Wang, Yaxiang Tian, Jiawei Liu, Yan Yang, Bo Liu, Shan Yin, Lirong Zheng, Wenfeng Sensors (Basel) Article A bilateral neural network adaptive controller is designed for a class of teleoperation systems with constant time delay, external disturbance and internal friction. The stability of the teleoperation force feedback system with constant communication channel delay and nonlinear, complex, and uncertain constant time delay is guaranteed, and its tracking performance is improved. In the controller design process, the neural network method is used to approximate the system model, and the unknown internal friction and external disturbance of the system are estimated by the adaptive method, so as to avoid the influence of nonlinear uncertainties on the system. MDPI 2021-11-09 /pmc/articles/PMC8623693/ /pubmed/34833523 http://dx.doi.org/10.3390/s21227443 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Yaxiang Tian, Jiawei Liu, Yan Yang, Bo Liu, Shan Yin, Lirong Zheng, Wenfeng Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title | Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title_full | Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title_fullStr | Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title_full_unstemmed | Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title_short | Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation |
title_sort | adaptive neural network control of time delay teleoperation system based on model approximation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623693/ https://www.ncbi.nlm.nih.gov/pubmed/34833523 http://dx.doi.org/10.3390/s21227443 |
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