Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots

In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback li...

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Detalles Bibliográficos
Autores: Rossomando, Francisco Guido, Soria, Carlos Miguel, Carelli Albarracin, Ricardo Oscar
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/3856
Acceso en línea:http://hdl.handle.net/11336/3856
Access Level:acceso abierto
Palabra clave:Mobile Robots
Nonlinear Systems
Adaptive Neural Control
Sliding Mode Control
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
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spelling Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile RobotsRossomando, Francisco GuidoSoria, Carlos MiguelCarelli Albarracin, Ricardo OscarMobile RobotsNonlinear SystemsAdaptive Neural ControlSliding Mode Controlhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.Fil: Rossomando, Francisco Guido. Gobierno de San Juan. Ministerio de Producción y Desarrollo Económico. Subsecretaría de Ciencia y Técnica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; ArgentinaSpringer2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/3856Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots; Springer; Journal of Intelligent & Robotic Systems; 74; 3-4; 6-2013; 931-9440921-0296enginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs10846-013-9843-5info:eu-repo/semantics/altIdentifier/doi/10.1007/s10846-013-9843-5info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2024-05-08T13:43:20Zoai:ri.conicet.gov.ar:11336/3856instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982024-05-08 13:43:20.343CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
title Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
spellingShingle Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
Rossomando, Francisco Guido
Mobile Robots
Nonlinear Systems
Adaptive Neural Control
Sliding Mode Control
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
title_short Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
title_full Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
title_fullStr Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
title_full_unstemmed Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
title_sort Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots
dc.creator.none.fl_str_mv Rossomando, Francisco Guido
Soria, Carlos Miguel
Carelli Albarracin, Ricardo Oscar
author Rossomando, Francisco Guido
author_facet Rossomando, Francisco Guido
Soria, Carlos Miguel
Carelli Albarracin, Ricardo Oscar
author_role author
author2 Soria, Carlos Miguel
Carelli Albarracin, Ricardo Oscar
author2_role author
author
dc.subject.none.fl_str_mv Mobile Robots
Nonlinear Systems
Adaptive Neural Control
Sliding Mode Control
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
topic Mobile Robots
Nonlinear Systems
Adaptive Neural Control
Sliding Mode Control
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
description In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/3856
Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots; Springer; Journal of Intelligent & Robotic Systems; 74; 3-4; 6-2013; 931-944
0921-0296
url http://hdl.handle.net/11336/3856
identifier_str_mv Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots; Springer; Journal of Intelligent & Robotic Systems; 74; 3-4; 6-2013; 931-944
0921-0296
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs10846-013-9843-5
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10846-013-9843-5
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 15,811543

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