Genetic planning of control actions for a high maneuvrability AUV

For certain operations the control of AUV motions is subject to difficulties, due to motion coupling. In this paper a high manoeuvrability AUV is considered, with only thrusters for motion control. A Genetic planning of the control actions has been devised, considering a multiobjective optimisation...

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Detalles Bibliográficos
Autores: Fernández-Prisuelos, J., Andrés Toro, Bonifacio de, Girón Sierra, José María Ricardo, Cruz García, Jesús Manuel de la, Riola, J. M.
Tipo de recurso: capítulo de libro
Fecha de publicación:2005
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/53331
Acceso en línea:https://hdl.handle.net/20.500.14352/53331
Access Level:acceso abierto
Palabra clave:004
Underwater Vehicles
Informática (Informática)
1203.17 Informática
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spelling Genetic planning of control actions for a high maneuvrability AUVFernández-Prisuelos, J.Andrés Toro, Bonifacio deGirón Sierra, José María RicardoCruz García, Jesús Manuel de laRiola, J. M.004Underwater VehiclesInformática (Informática)1203.17 InformáticaFor certain operations the control of AUV motions is subject to difficulties, due to motion coupling. In this paper a high manoeuvrability AUV is considered, with only thrusters for motion control. A Genetic planning of the control actions has been devised, considering a multiobjective optimisation problem, which includes energy and time saving, and smooth operation with realistic control actions. Since the inertia of the submergible filters out control brisk changes, it turns out that there are many almost equivalent control strategies obtaining similar trajectories. This is why the characteristics of the control actions have been included as part of the multiobjective optimisation. Several diving scenarios have been specified, including obstacles. The paper begins with a description of the AUV and the control problem, then it focus on the multiobjective optimisation problem and the genetic planning to solve the problem, then it considers several scenarios and present optimal results; finally, the paper comes to conclusions and future research, which will be experimental.IEEEUniversidad Complutense de Madrid20052005-01-0120052005-01-01book parthttp://purl.org/coar/resource_type/c_3248info:eu-repo/semantics/bookPartapplication/pdfhttps://hdl.handle.net/20.500.14352/53331reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/533312026-06-02T12:44:21Z
dc.title.none.fl_str_mv Genetic planning of control actions for a high maneuvrability AUV
title Genetic planning of control actions for a high maneuvrability AUV
spellingShingle Genetic planning of control actions for a high maneuvrability AUV
Fernández-Prisuelos, J.
004
Underwater Vehicles
Informática (Informática)
1203.17 Informática
title_short Genetic planning of control actions for a high maneuvrability AUV
title_full Genetic planning of control actions for a high maneuvrability AUV
title_fullStr Genetic planning of control actions for a high maneuvrability AUV
title_full_unstemmed Genetic planning of control actions for a high maneuvrability AUV
title_sort Genetic planning of control actions for a high maneuvrability AUV
dc.creator.none.fl_str_mv Fernández-Prisuelos, J.
Andrés Toro, Bonifacio de
Girón Sierra, José María Ricardo
Cruz García, Jesús Manuel de la
Riola, J. M.
author Fernández-Prisuelos, J.
author_facet Fernández-Prisuelos, J.
Andrés Toro, Bonifacio de
Girón Sierra, José María Ricardo
Cruz García, Jesús Manuel de la
Riola, J. M.
author_role author
author2 Andrés Toro, Bonifacio de
Girón Sierra, José María Ricardo
Cruz García, Jesús Manuel de la
Riola, J. M.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004
Underwater Vehicles
Informática (Informática)
1203.17 Informática
topic 004
Underwater Vehicles
Informática (Informática)
1203.17 Informática
description For certain operations the control of AUV motions is subject to difficulties, due to motion coupling. In this paper a high manoeuvrability AUV is considered, with only thrusters for motion control. A Genetic planning of the control actions has been devised, considering a multiobjective optimisation problem, which includes energy and time saving, and smooth operation with realistic control actions. Since the inertia of the submergible filters out control brisk changes, it turns out that there are many almost equivalent control strategies obtaining similar trajectories. This is why the characteristics of the control actions have been included as part of the multiobjective optimisation. Several diving scenarios have been specified, including obstacles. The paper begins with a description of the AUV and the control problem, then it focus on the multiobjective optimisation problem and the genetic planning to solve the problem, then it considers several scenarios and present optimal results; finally, the paper comes to conclusions and future research, which will be experimental.
publishDate 2005
dc.date.none.fl_str_mv 2005
2005-01-01
2005
2005-01-01
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/53331
url https://hdl.handle.net/20.500.14352/53331
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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