Adaptive neural dynamic compensator for mobile robots in trajectory tracking control
- Autores
- Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar
- Año de publicación
- 2011
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In the present paper, it will be reported original results concerning the application of Neural Networks (NN) in mobile robot in trajectory tracking control. This work combines a feedback linearization based on a nominal model and an NN adaptive dynamic compensation. In mobile robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematic controller and an inverse dynamic controller. The uncertainty in the nominal dynamic model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The learning laws were deduced by Lyapunovs stability analysis. Finally, the performance of the control system is verified through experiments.
Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Soria, Carlos Miguel. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina - Materia
-
ADAPTIVE INVERSE CONTROL
LYAPUNOV THEORY
MOBILE ROBOT CONTROL
RBF NEURAL NETS
SSUBSPACE
SYSTEM IDENTIFICATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/193439
Ver los metadatos del registro completo
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Adaptive neural dynamic compensator for mobile robots in trajectory tracking controlRossomando, Francisco GuidoSoria, Carlos MiguelCarelli Albarracin, Ricardo OscarADAPTIVE INVERSE CONTROLLYAPUNOV THEORYMOBILE ROBOT CONTROLRBF NEURAL NETSSSUBSPACESYSTEM IDENTIFICATIONhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In the present paper, it will be reported original results concerning the application of Neural Networks (NN) in mobile robot in trajectory tracking control. This work combines a feedback linearization based on a nominal model and an NN adaptive dynamic compensation. In mobile robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematic controller and an inverse dynamic controller. The uncertainty in the nominal dynamic model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The learning laws were deduced by Lyapunovs stability analysis. Finally, the performance of the control system is verified through experiments.Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soria, Carlos Miguel. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaInstitute of Electrical and Electronics Engineers2011-09info: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/11336/193439Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Adaptive neural dynamic compensator for mobile robots in trajectory tracking control; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 9; 5; 9-2011; 593-6021548-0992CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/6030965info:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2011.6030965info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:44:22Zoai:ri.conicet.gov.ar:11336/193439instacron: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 10:44:22.861CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
title |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
spellingShingle |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control Rossomando, Francisco Guido ADAPTIVE INVERSE CONTROL LYAPUNOV THEORY MOBILE ROBOT CONTROL RBF NEURAL NETS SSUBSPACE SYSTEM IDENTIFICATION |
title_short |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
title_full |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
title_fullStr |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
title_full_unstemmed |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
title_sort |
Adaptive neural dynamic compensator for mobile robots in trajectory tracking control |
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 |
ADAPTIVE INVERSE CONTROL LYAPUNOV THEORY MOBILE ROBOT CONTROL RBF NEURAL NETS SSUBSPACE SYSTEM IDENTIFICATION |
topic |
ADAPTIVE INVERSE CONTROL LYAPUNOV THEORY MOBILE ROBOT CONTROL RBF NEURAL NETS SSUBSPACE SYSTEM IDENTIFICATION |
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 the present paper, it will be reported original results concerning the application of Neural Networks (NN) in mobile robot in trajectory tracking control. This work combines a feedback linearization based on a nominal model and an NN adaptive dynamic compensation. In mobile robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematic controller and an inverse dynamic controller. The uncertainty in the nominal dynamic model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The learning laws were deduced by Lyapunovs stability analysis. Finally, the performance of the control system is verified through experiments. Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Soria, Carlos Miguel. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina |
description |
In the present paper, it will be reported original results concerning the application of Neural Networks (NN) in mobile robot in trajectory tracking control. This work combines a feedback linearization based on a nominal model and an NN adaptive dynamic compensation. In mobile robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematic controller and an inverse dynamic controller. The uncertainty in the nominal dynamic model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The learning laws were deduced by Lyapunovs stability analysis. Finally, the performance of the control system is verified through experiments. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-09 |
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/11336/193439 Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Adaptive neural dynamic compensator for mobile robots in trajectory tracking control; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 9; 5; 9-2011; 593-602 1548-0992 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/193439 |
identifier_str_mv |
Rossomando, Francisco Guido; Soria, Carlos Miguel; Carelli Albarracin, Ricardo Oscar; Adaptive neural dynamic compensator for mobile robots in trajectory tracking control; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 9; 5; 9-2011; 593-602 1548-0992 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/6030965 info:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2011.6030965 |
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 |
Institute of Electrical and Electronics Engineers |
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Institute of Electrical and Electronics Engineers |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.070432 |