A swarm intelligence-based tuning method for the sliding mode generalized predictive control

Detalhes bibliográficos
Autor(a) principal: Josenalde Barbosa Oliveira
Data de Publicação: 2014
Outros Autores: José Boaventura, Paulo Moura Oliveira, Hélio Alves Freire
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/5016
http://dx.doi.org/10.1016/j.isatra.2014.06.007
Resumo: This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.
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spelling A swarm intelligence-based tuning method for the sliding mode generalized predictive controlThis work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.2017-12-28T02:20:13Z2014-01-01T00:00:00Z2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/5016http://dx.doi.org/10.1016/j.isatra.2014.06.007engJosenalde Barbosa OliveiraJosé BoaventuraPaulo Moura OliveiraHélio Alves Freireinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:40Zoai:repositorio.inesctec.pt:123456789/5016Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:28.537246Repositório 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 swarm intelligence-based tuning method for the sliding mode generalized predictive control
title A swarm intelligence-based tuning method for the sliding mode generalized predictive control
spellingShingle A swarm intelligence-based tuning method for the sliding mode generalized predictive control
Josenalde Barbosa Oliveira
title_short A swarm intelligence-based tuning method for the sliding mode generalized predictive control
title_full A swarm intelligence-based tuning method for the sliding mode generalized predictive control
title_fullStr A swarm intelligence-based tuning method for the sliding mode generalized predictive control
title_full_unstemmed A swarm intelligence-based tuning method for the sliding mode generalized predictive control
title_sort A swarm intelligence-based tuning method for the sliding mode generalized predictive control
author Josenalde Barbosa Oliveira
author_facet Josenalde Barbosa Oliveira
José Boaventura
Paulo Moura Oliveira
Hélio Alves Freire
author_role author
author2 José Boaventura
Paulo Moura Oliveira
Hélio Alves Freire
author2_role author
author
author
dc.contributor.author.fl_str_mv Josenalde Barbosa Oliveira
José Boaventura
Paulo Moura Oliveira
Hélio Alves Freire
description This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01T00:00:00Z
2014
2017-12-28T02:20:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/5016
http://dx.doi.org/10.1016/j.isatra.2014.06.007
url http://repositorio.inesctec.pt/handle/123456789/5016
http://dx.doi.org/10.1016/j.isatra.2014.06.007
dc.language.iso.fl_str_mv eng
language eng
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