Identification and control of the AWS using neural network models

Detalhes bibliográficos
Autor(a) principal: Valério, Duarte
Data de Publicação: 2008
Outros Autores: Mendes, Mário J. G. C., Beirão, Pedro, Costa, José Sá da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/10785
Resumo: The Archimedes Wave Swing (AWS) is a a fully-submerged Wave Energy Converter (WEC), that is to say, a device that converts the energy of sea waves into electricity. A first prototype of the AWS has already been built and tested. In this paper, neural network (NN) models for this AWS prototype are developed. NNs are then used together with proven control strategies (phase and amplitude control, internal model control and switching control) to maximise energy production. Simulations show an yearly average electricity production increase of 160% over the performance of the original AWS controller.
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spelling Identification and control of the AWS using neural network modelsWave energyArchimedes wave swingPhase and amplitude controlNeural networksInternal model controlSwitching controlThe Archimedes Wave Swing (AWS) is a a fully-submerged Wave Energy Converter (WEC), that is to say, a device that converts the energy of sea waves into electricity. A first prototype of the AWS has already been built and tested. In this paper, neural network (NN) models for this AWS prototype are developed. NNs are then used together with proven control strategies (phase and amplitude control, internal model control and switching control) to maximise energy production. Simulations show an yearly average electricity production increase of 160% over the performance of the original AWS controller.ElsevierRCIPLValério, DuarteMendes, Mário J. G. C.Beirão, PedroCosta, José Sá da2019-12-03T10:01:45Z2008-072008-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/10785engVALÉRIO, Duarte; [et al] – Identification and control of the AWS using neural network models. Applied Ocean Research. ISSN 0141-1187. Vol. 30, N.º 3 (2008), pp. 178-1880141-1187https://doi.org/10.1016/j.apor.2008.11.002metadata only accessinfo: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:RCAAP2023-08-03T10:01:13Zoai:repositorio.ipl.pt:10400.21/10785Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:19:08.075320Repositório 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 Identification and control of the AWS using neural network models
title Identification and control of the AWS using neural network models
spellingShingle Identification and control of the AWS using neural network models
Valério, Duarte
Wave energy
Archimedes wave swing
Phase and amplitude control
Neural networks
Internal model control
Switching control
title_short Identification and control of the AWS using neural network models
title_full Identification and control of the AWS using neural network models
title_fullStr Identification and control of the AWS using neural network models
title_full_unstemmed Identification and control of the AWS using neural network models
title_sort Identification and control of the AWS using neural network models
author Valério, Duarte
author_facet Valério, Duarte
Mendes, Mário J. G. C.
Beirão, Pedro
Costa, José Sá da
author_role author
author2 Mendes, Mário J. G. C.
Beirão, Pedro
Costa, José Sá da
author2_role author
author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Valério, Duarte
Mendes, Mário J. G. C.
Beirão, Pedro
Costa, José Sá da
dc.subject.por.fl_str_mv Wave energy
Archimedes wave swing
Phase and amplitude control
Neural networks
Internal model control
Switching control
topic Wave energy
Archimedes wave swing
Phase and amplitude control
Neural networks
Internal model control
Switching control
description The Archimedes Wave Swing (AWS) is a a fully-submerged Wave Energy Converter (WEC), that is to say, a device that converts the energy of sea waves into electricity. A first prototype of the AWS has already been built and tested. In this paper, neural network (NN) models for this AWS prototype are developed. NNs are then used together with proven control strategies (phase and amplitude control, internal model control and switching control) to maximise energy production. Simulations show an yearly average electricity production increase of 160% over the performance of the original AWS controller.
publishDate 2008
dc.date.none.fl_str_mv 2008-07
2008-07-01T00:00:00Z
2019-12-03T10:01:45Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/10785
url http://hdl.handle.net/10400.21/10785
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv VALÉRIO, Duarte; [et al] – Identification and control of the AWS using neural network models. Applied Ocean Research. ISSN 0141-1187. Vol. 30, N.º 3 (2008), pp. 178-188
0141-1187
https://doi.org/10.1016/j.apor.2008.11.002
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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
repository.mail.fl_str_mv
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