A Hybrid Systems Model Predictive Control Framework for AUV Motion Control

Detalhes bibliográficos
Autor(a) principal: Rui Gomes
Data de Publicação: 2018
Outros Autores: Fernando Lobo Pereira
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/115904
Resumo: A computationally efficient architecture to control formations of Autonomous Underwater Vehicles (AUVs) is presented and discussed in this article. The proposed control structure enables the articulation of resources optimization with state feedback control while keeping the onboard computational burden very low. These properties are critical for AUVs systems as they operate in contexts of scarce resources and high uncertainty or variability. The hybrid nature of the controller enables different modes of operation, notably, in dealing with unanticipated obstacles. Optimization and feedback control are brought in by a novel Model Control Predictive (MPC) scheme constructed in such a way that time-invariant information is used as much as possible in a priori off-line computation.
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spelling A Hybrid Systems Model Predictive Control Framework for AUV Motion ControlA computationally efficient architecture to control formations of Autonomous Underwater Vehicles (AUVs) is presented and discussed in this article. The proposed control structure enables the articulation of resources optimization with state feedback control while keeping the onboard computational burden very low. These properties are critical for AUVs systems as they operate in contexts of scarce resources and high uncertainty or variability. The hybrid nature of the controller enables different modes of operation, notably, in dealing with unanticipated obstacles. Optimization and feedback control are brought in by a novel Model Control Predictive (MPC) scheme constructed in such a way that time-invariant information is used as much as possible in a priori off-line computation.2018-06-122018-06-12T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/115904engRui GomesFernando Lobo Pereirainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:55:57Zoai:repositorio-aberto.up.pt:10216/115904Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:11:52.015925Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
title A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
spellingShingle A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
Rui Gomes
title_short A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
title_full A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
title_fullStr A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
title_full_unstemmed A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
title_sort A Hybrid Systems Model Predictive Control Framework for AUV Motion Control
author Rui Gomes
author_facet Rui Gomes
Fernando Lobo Pereira
author_role author
author2 Fernando Lobo Pereira
author2_role author
dc.contributor.author.fl_str_mv Rui Gomes
Fernando Lobo Pereira
description A computationally efficient architecture to control formations of Autonomous Underwater Vehicles (AUVs) is presented and discussed in this article. The proposed control structure enables the articulation of resources optimization with state feedback control while keeping the onboard computational burden very low. These properties are critical for AUVs systems as they operate in contexts of scarce resources and high uncertainty or variability. The hybrid nature of the controller enables different modes of operation, notably, in dealing with unanticipated obstacles. Optimization and feedback control are brought in by a novel Model Control Predictive (MPC) scheme constructed in such a way that time-invariant information is used as much as possible in a priori off-line computation.
publishDate 2018
dc.date.none.fl_str_mv 2018-06-12
2018-06-12T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
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status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/115904
url https://hdl.handle.net/10216/115904
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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