Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks

Abstract This letter presents a new intelligent control scheme for the accurate trajectory tracking of flexible link manipulators. The proposed approach is mainly based on a sliding mode controller for underactuated systems with an embedded artificial neural network to deal with modelling inaccuraci...

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Autores principales:	Gabriel da Silva Lima, Diego Rolim Porto, Adilson José de Oliveira, Wallace Moreira Bessa
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/785a65b6014c42e3bc8733698cf72825
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spelling	oai:doaj.org-article:785a65b6014c42e3bc8733698cf728252021-11-05T05:26:52ZIntelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks1350-911X0013-519410.1049/ell2.12300https://doaj.org/article/785a65b6014c42e3bc8733698cf728252021-11-01T00:00:00Zhttps://doi.org/10.1049/ell2.12300https://doaj.org/toc/0013-5194https://doaj.org/toc/1350-911XAbstract This letter presents a new intelligent control scheme for the accurate trajectory tracking of flexible link manipulators. The proposed approach is mainly based on a sliding mode controller for underactuated systems with an embedded artificial neural network to deal with modelling inaccuracies. The adopted neural network only needs a single input and one hidden layer, which drastically reduces the computational complexity of the control law and allows its implementation in low‐power microcontrollers. Online learning, rather than supervised offline training, is chosen to allow the weights of the neural network to be adjusted in real time during the tracking. Therefore, the resulting controller is able to cope with the underactuating issues and to adapt itself by learning from experience, which grants the capacity to deal with plant dynamics properly. The boundedness and convergence properties of the tracking error are proved by evoking Barbalat's lemma in a Lyapunov‐like stability analysis. Experimental results obtained with a small single‐link flexible manipulator show the efficacy of the proposed control scheme, even in the presence of a high level of uncertainty and noisy signals.Gabriel da Silva LimaDiego Rolim PortoAdilson José de OliveiraWallace Moreira BessaWileyarticleElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENElectronics Letters, Vol 57, Iss 23, Pp 869-872 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Electrical engineering. Electronics. Nuclear engineering TK1-9971 Gabriel da Silva Lima Diego Rolim Porto Adilson José de Oliveira Wallace Moreira Bessa Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
description	Abstract This letter presents a new intelligent control scheme for the accurate trajectory tracking of flexible link manipulators. The proposed approach is mainly based on a sliding mode controller for underactuated systems with an embedded artificial neural network to deal with modelling inaccuracies. The adopted neural network only needs a single input and one hidden layer, which drastically reduces the computational complexity of the control law and allows its implementation in low‐power microcontrollers. Online learning, rather than supervised offline training, is chosen to allow the weights of the neural network to be adjusted in real time during the tracking. Therefore, the resulting controller is able to cope with the underactuating issues and to adapt itself by learning from experience, which grants the capacity to deal with plant dynamics properly. The boundedness and convergence properties of the tracking error are proved by evoking Barbalat's lemma in a Lyapunov‐like stability analysis. Experimental results obtained with a small single‐link flexible manipulator show the efficacy of the proposed control scheme, even in the presence of a high level of uncertainty and noisy signals.
format	article
author	Gabriel da Silva Lima Diego Rolim Porto Adilson José de Oliveira Wallace Moreira Bessa
author_facet	Gabriel da Silva Lima Diego Rolim Porto Adilson José de Oliveira Wallace Moreira Bessa
author_sort	Gabriel da Silva Lima
title	Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
title_short	Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
title_full	Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
title_fullStr	Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
title_full_unstemmed	Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
title_sort	intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/785a65b6014c42e3bc8733698cf72825
work_keys_str_mv	AT gabrieldasilvalima intelligentcontrolofasinglelinkflexiblemanipulatorusingslidingmodesandartificialneuralnetworks AT diegorolimporto intelligentcontrolofasinglelinkflexiblemanipulatorusingslidingmodesandartificialneuralnetworks AT adilsonjosedeoliveira intelligentcontrolofasinglelinkflexiblemanipulatorusingslidingmodesandartificialneuralnetworks AT wallacemoreirabessa intelligentcontrolofasinglelinkflexiblemanipulatorusingslidingmodesandartificialneuralnetworks
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Intelligent control of a single‐link flexible manipulator using sliding modes and artificial neural networks

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