Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots

Abstract By relying on the input–output feedback linearization approach, a novel adaptive controller for flexible joint robots is proposed in this work. First, a model‐based controller is developed to get a structure that is useful in the development of the adaptive controller. The adaptive version...

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Autores principales:	Jorge Montoya‐Cháirez, Javier Moreno‐Valenzuela, Víctor Santibáñez, Ricardo Carelli, Fracisco G. Rossomando, Ricardo Pérez‐Alcocer
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2022
Materias:	Control engineering systems. Automatic machinery (General) TJ212-225
Acceso en línea:	https://doaj.org/article/fc0a2d8ad40545188012d18ff3f754f6
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spelling	oai:doaj.org-article:fc0a2d8ad40545188012d18ff3f754f62021-12-02T15:00:29ZCombined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots1751-86521751-864410.1049/cth2.12202https://doaj.org/article/fc0a2d8ad40545188012d18ff3f754f62022-01-01T00:00:00Zhttps://doi.org/10.1049/cth2.12202https://doaj.org/toc/1751-8644https://doaj.org/toc/1751-8652Abstract By relying on the input–output feedback linearization approach, a novel adaptive controller for flexible joint robots is proposed in this work. First, a model‐based controller is developed to get a structure that is useful in the development of the adaptive controller. The adaptive version is developed by using two techniques. To stabilize the output function, an adaptive neural network controller is used, which approximates the non‐linear function that contains the uncertainties. The desired rotor position required by the input–output feedback linearization controller is defined with the structure of a link dynamics adaptive regressor‐based controller. The main reason to adopt the mentioned structure in the definition of the desired rotor link position is to guarantee its differentiability. Real‐time experiment comparisons among the model‐based controller, a model‐based controller with desired compensation, an adaptive controller based on joint torque feedback, and an adaptive neural network‐based controller are carried out. Experimental results support the theory reported in this document and the accuracy of the proposed approach.Jorge Montoya‐CháirezJavier Moreno‐ValenzuelaVíctor SantibáñezRicardo CarelliFracisco G. RossomandoRicardo Pérez‐AlcocerWileyarticleControl engineering systems. Automatic machinery (General)TJ212-225ENIET Control Theory & Applications, Vol 16, Iss 1, Pp 31-50 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Control engineering systems. Automatic machinery (General) TJ212-225
spellingShingle	Control engineering systems. Automatic machinery (General) TJ212-225 Jorge Montoya‐Cháirez Javier Moreno‐Valenzuela Víctor Santibáñez Ricardo Carelli Fracisco G. Rossomando Ricardo Pérez‐Alcocer Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
description	Abstract By relying on the input–output feedback linearization approach, a novel adaptive controller for flexible joint robots is proposed in this work. First, a model‐based controller is developed to get a structure that is useful in the development of the adaptive controller. The adaptive version is developed by using two techniques. To stabilize the output function, an adaptive neural network controller is used, which approximates the non‐linear function that contains the uncertainties. The desired rotor position required by the input–output feedback linearization controller is defined with the structure of a link dynamics adaptive regressor‐based controller. The main reason to adopt the mentioned structure in the definition of the desired rotor link position is to guarantee its differentiability. Real‐time experiment comparisons among the model‐based controller, a model‐based controller with desired compensation, an adaptive controller based on joint torque feedback, and an adaptive neural network‐based controller are carried out. Experimental results support the theory reported in this document and the accuracy of the proposed approach.
format	article
author	Jorge Montoya‐Cháirez Javier Moreno‐Valenzuela Víctor Santibáñez Ricardo Carelli Fracisco G. Rossomando Ricardo Pérez‐Alcocer
author_facet	Jorge Montoya‐Cháirez Javier Moreno‐Valenzuela Víctor Santibáñez Ricardo Carelli Fracisco G. Rossomando Ricardo Pérez‐Alcocer
author_sort	Jorge Montoya‐Cháirez
title	Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
title_short	Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
title_full	Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
title_fullStr	Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
title_full_unstemmed	Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
title_sort	combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
publisher	Wiley
publishDate	2022
url	https://doaj.org/article/fc0a2d8ad40545188012d18ff3f754f6
work_keys_str_mv	AT jorgemontoyachairez combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots AT javiermorenovalenzuela combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots AT victorsantibanez combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots AT ricardocarelli combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots AT fraciscogrossomando combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots AT ricardoperezalcocer combinedadaptiveneuralnetworkandregressorbasedtrajectorytrackingcontrolofflexiblejointrobots
_version_	1718389178141507584

Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots

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