Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID

Autores
Rossomando, Francisco Guido; Soria, Carlos Miguel
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, original results, concerning the application of a discrete-time adaptive PID neural controller in mobile robots for trajectory tracking control, are reported. In this control strategy, the exact dynamical model of the robot does not need to be known, but a neural network is used to identify the dynamic model. To implement this strategy, two controllers are implemented separately: a kinematic controller and an adaptive neural PID controller. The uncertainty and variations in the robot dynamics are compensated by an adaptive neural PID controller. It is efficient and robust in order to achieve a good tracking performance. The stability of the proposed technique, based on the discrete-time Lyapunov's theory, is proven. Finally, experiments on the mobile robot have been developed to show the performance of the proposed technique, including the comparison with a classical PID.
Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; Argentina
Fil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; Argentina
Materia
Mimo System
Neural Networks
Nonlinear Control
Adaptive Control
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/4916
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/4916
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PIDRossomando, Francisco GuidoSoria, Carlos MiguelMimo SystemNeural NetworksNonlinear ControlAdaptive Controlhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this work, original results, concerning the application of a discrete-time adaptive PID neural controller in mobile robots for trajectory tracking control, are reported. In this control strategy, the exact dynamical model of the robot does not need to be known, but a neural network is used to identify the dynamic model. To implement this strategy, two controllers are implemented separately: a kinematic controller and an adaptive neural PID controller. The uncertainty and variations in the robot dynamics are compensated by an adaptive neural PID controller. It is efficient and robust in order to achieve a good tracking performance. The stability of the proposed technique, based on the discrete-time Lyapunov's theory, is proven. Finally, experiments on the mobile robot have been developed to show the performance of the proposed technique, including the comparison with a classical PID.Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; ArgentinaSpringer2014-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/4916Rossomando, Francisco Guido; Soria, Carlos Miguel; Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID; Springer; Neural Computing And Applications; 26; 5; 12-2014; 1179-11910941-0643enginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00521-014-1805-8info:eu-repo/semantics/altIdentifier/doi/10.1007/s00521-014-1805-8info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:11:15Zoai:ri.conicet.gov.ar:11336/4916instacron: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:34982025-09-29 10:11:15.788CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
title Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
spellingShingle Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
Rossomando, Francisco Guido
Mimo System
Neural Networks
Nonlinear Control
Adaptive Control
title_short Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
title_full Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
title_fullStr Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
title_full_unstemmed Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
title_sort Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID
dc.creator.none.fl_str_mv Rossomando, Francisco Guido
Soria, Carlos Miguel
author Rossomando, Francisco Guido
author_facet Rossomando, Francisco Guido
Soria, Carlos Miguel
author_role author
author2 Soria, Carlos Miguel
author2_role author
dc.subject.none.fl_str_mv Mimo System
Neural Networks
Nonlinear Control
Adaptive Control
topic Mimo System
Neural Networks
Nonlinear Control
Adaptive Control
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this work, original results, concerning the application of a discrete-time adaptive PID neural controller in mobile robots for trajectory tracking control, are reported. In this control strategy, the exact dynamical model of the robot does not need to be known, but a neural network is used to identify the dynamic model. To implement this strategy, two controllers are implemented separately: a kinematic controller and an adaptive neural PID controller. The uncertainty and variations in the robot dynamics are compensated by an adaptive neural PID controller. It is efficient and robust in order to achieve a good tracking performance. The stability of the proposed technique, based on the discrete-time Lyapunov's theory, is proven. Finally, experiments on the mobile robot have been developed to show the performance of the proposed technique, including the comparison with a classical PID.
Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; Argentina
Fil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Instituto de Automática; Argentina
description In this work, original results, concerning the application of a discrete-time adaptive PID neural controller in mobile robots for trajectory tracking control, are reported. In this control strategy, the exact dynamical model of the robot does not need to be known, but a neural network is used to identify the dynamic model. To implement this strategy, two controllers are implemented separately: a kinematic controller and an adaptive neural PID controller. The uncertainty and variations in the robot dynamics are compensated by an adaptive neural PID controller. It is efficient and robust in order to achieve a good tracking performance. The stability of the proposed technique, based on the discrete-time Lyapunov's theory, is proven. Finally, experiments on the mobile robot have been developed to show the performance of the proposed technique, including the comparison with a classical PID.
publishDate 2014
dc.date.none.fl_str_mv 2014-12
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/11336/4916
Rossomando, Francisco Guido; Soria, Carlos Miguel; Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID; Springer; Neural Computing And Applications; 26; 5; 12-2014; 1179-1191
0941-0643
url http://hdl.handle.net/11336/4916
identifier_str_mv Rossomando, Francisco Guido; Soria, Carlos Miguel; Identification and control of nonlinear dynamics of a mobile robot in discrete time using an adaptive technique based on neural PID; Springer; Neural Computing And Applications; 26; 5; 12-2014; 1179-1191
0941-0643
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%2Fs00521-014-1805-8
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00521-014-1805-8
info:eu-repo/semantics/altIdentifier/doi/
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
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
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
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 13.070432

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