Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization

Detalhes bibliográficos
Autor(a) principal: Silva,Valceres V. R. e
Data de Publicação: 2007
Outros Autores: Khatib,Wael, Fleming,Peter J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Sba: Controle & Automação Sociedade Brasileira de Automatica
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592007000400007
Resumo: Multidisciplinary optimization (MDO) is concerned with complex systems exhibiting challenges in terms of organization and scale. Thus, it is well suited to be applied to complex multivariable control design. Collaborative optimization is one approach for dealing with complex multidisciplinary optimization problems. Three MDO architectures, including collaborative optimization, are applied to control system design for a gas turbine engine, in order to improve the design search process by exploring possible solutions with parallel, but independent search strands. The optimization is carried out through a multiobjective genetic algorithm framework.
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spelling Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimizationGenetic algorithmsgas turbinesoptimizationPI controllersMultidisciplinary optimization (MDO) is concerned with complex systems exhibiting challenges in terms of organization and scale. Thus, it is well suited to be applied to complex multivariable control design. Collaborative optimization is one approach for dealing with complex multidisciplinary optimization problems. Three MDO architectures, including collaborative optimization, are applied to control system design for a gas turbine engine, in order to improve the design search process by exploring possible solutions with parallel, but independent search strands. The optimization is carried out through a multiobjective genetic algorithm framework.Sociedade Brasileira de Automática2007-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592007000400007Sba: Controle & Automação Sociedade Brasileira de Automatica v.18 n.4 2007reponame:Sba: Controle & Automação Sociedade Brasileira de Automaticainstname:Sociedade Brasileira de Automática (SBA)instacron:SBA10.1590/S0103-17592007000400007info:eu-repo/semantics/openAccessSilva,Valceres V. R. eKhatib,WaelFleming,Peter J.eng2008-01-21T00:00:00Zoai:scielo:S0103-17592007000400007Revistahttps://www.sba.org.br/revista/PUBhttps://old.scielo.br/oai/scielo-oai.php||revista_sba@fee.unicamp.br1807-03450103-1759opendoar:2008-01-21T00:00Sba: Controle & Automação Sociedade Brasileira de Automatica - Sociedade Brasileira de Automática (SBA)false
dc.title.none.fl_str_mv Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
title Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
spellingShingle Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
Silva,Valceres V. R. e
Genetic algorithms
gas turbines
optimization
PI controllers
title_short Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
title_full Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
title_fullStr Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
title_full_unstemmed Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
title_sort Control system design for a gas turbine engine using evolutionary computing for multidisciplinary optimization
author Silva,Valceres V. R. e
author_facet Silva,Valceres V. R. e
Khatib,Wael
Fleming,Peter J.
author_role author
author2 Khatib,Wael
Fleming,Peter J.
author2_role author
author
dc.contributor.author.fl_str_mv Silva,Valceres V. R. e
Khatib,Wael
Fleming,Peter J.
dc.subject.por.fl_str_mv Genetic algorithms
gas turbines
optimization
PI controllers
topic Genetic algorithms
gas turbines
optimization
PI controllers
description Multidisciplinary optimization (MDO) is concerned with complex systems exhibiting challenges in terms of organization and scale. Thus, it is well suited to be applied to complex multivariable control design. Collaborative optimization is one approach for dealing with complex multidisciplinary optimization problems. Three MDO architectures, including collaborative optimization, are applied to control system design for a gas turbine engine, in order to improve the design search process by exploring possible solutions with parallel, but independent search strands. The optimization is carried out through a multiobjective genetic algorithm framework.
publishDate 2007
dc.date.none.fl_str_mv 2007-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592007000400007
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-17592007000400007
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Automática
publisher.none.fl_str_mv Sociedade Brasileira de Automática
dc.source.none.fl_str_mv Sba: Controle & Automação Sociedade Brasileira de Automatica v.18 n.4 2007
reponame:Sba: Controle & Automação Sociedade Brasileira de Automatica
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institution SBA
reponame_str Sba: Controle & Automação Sociedade Brasileira de Automatica
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repository.name.fl_str_mv Sba: Controle & Automação Sociedade Brasileira de Automatica - Sociedade Brasileira de Automática (SBA)
repository.mail.fl_str_mv ||revista_sba@fee.unicamp.br
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