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TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints

This paper proposes an adaptive control scheme based on terminal sliding mode (TSM) for robotic manipulators with output constraints and unknown disturbances. The fuzzy logic system (FLS) is developed to approximate unknown dynamics of robotic manipulators. An error transformation technique is used...

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Detalles Bibliográficos
Autores principales: Yan, Fei, Wang, Shubo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295000/
https://www.ncbi.nlm.nih.gov/pubmed/34335720
http://dx.doi.org/10.1155/2021/5812584
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author Yan, Fei
Wang, Shubo
author_facet Yan, Fei
Wang, Shubo
author_sort Yan, Fei
collection PubMed
description This paper proposes an adaptive control scheme based on terminal sliding mode (TSM) for robotic manipulators with output constraints and unknown disturbances. The fuzzy logic system (FLS) is developed to approximate unknown dynamics of robotic manipulators. An error transformation technique is used in the process of controller design to ensure that the output constraints are not violated. The advantage of the error transformation compared to traditional barrier Lyapunov functions (BLFs) is that there is no need to design a virtual controller. Thus, the design complexity of the controller is reduced. Through Lyapunov stability analysis, the system state can be proved to converge to the neighborhood near the balanced point in finite time. Extensive simulation results illustrated the validity of the proposed controller.
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spelling pubmed-82950002021-07-31 TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints Yan, Fei Wang, Shubo Comput Intell Neurosci Research Article This paper proposes an adaptive control scheme based on terminal sliding mode (TSM) for robotic manipulators with output constraints and unknown disturbances. The fuzzy logic system (FLS) is developed to approximate unknown dynamics of robotic manipulators. An error transformation technique is used in the process of controller design to ensure that the output constraints are not violated. The advantage of the error transformation compared to traditional barrier Lyapunov functions (BLFs) is that there is no need to design a virtual controller. Thus, the design complexity of the controller is reduced. Through Lyapunov stability analysis, the system state can be proved to converge to the neighborhood near the balanced point in finite time. Extensive simulation results illustrated the validity of the proposed controller. Hindawi 2021-07-13 /pmc/articles/PMC8295000/ /pubmed/34335720 http://dx.doi.org/10.1155/2021/5812584 Text en Copyright © 2021 Fei Yan and Shubo Wang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yan, Fei
Wang, Shubo
TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title_full TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title_fullStr TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title_full_unstemmed TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title_short TSM-Based Adaptive Fuzzy Control of Robotic Manipulators with Output Constraints
title_sort tsm-based adaptive fuzzy control of robotic manipulators with output constraints
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295000/
https://www.ncbi.nlm.nih.gov/pubmed/34335720
http://dx.doi.org/10.1155/2021/5812584
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