Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms

Autores
Skrjanc, Igor; Lepetic, Marko; Figueroa, Jose Luis; Brazic, Saso
Año de publicación
2004
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In the paper a comparison of different nonlinear model-based predictive control algorithms is presented as a case study for a continuous stirred reactor. The focus is given to the fuzzy predictive control approach which is compared to Wiener based model predictive control and nonlinear model predictive control based on optimization. It has been shown that fuzzy predictive control law which is given in analytical form gives very promising results in comparison to other two approaches which are both based on optimization. All the proposed approaches are potentially interesting in the case of batch reactors, heat-exchangers, furnaces and all the processes with strong nonlinear dynamics.
Fil: Skrjanc, Igor. University of Ljubljana; Eslovenia
Fil: Lepetic, Marko. University of Ljubljana; Eslovenia
Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur; Argentina
Fil: Brazic, Saso. University of Ljubljana; Eslovenia
Materia
NONLINEAR PREDICTIVE CONTROL
FUZZY IDENTIFICATION
FUZZY MODEL PREDICTIVE CONTROL
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/104545
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithmsSkrjanc, IgorLepetic, MarkoFigueroa, Jose LuisBrazic, SasoNONLINEAR PREDICTIVE CONTROLFUZZY IDENTIFICATIONFUZZY MODEL PREDICTIVE CONTROLhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In the paper a comparison of different nonlinear model-based predictive control algorithms is presented as a case study for a continuous stirred reactor. The focus is given to the fuzzy predictive control approach which is compared to Wiener based model predictive control and nonlinear model predictive control based on optimization. It has been shown that fuzzy predictive control law which is given in analytical form gives very promising results in comparison to other two approaches which are both based on optimization. All the proposed approaches are potentially interesting in the case of batch reactors, heat-exchangers, furnaces and all the processes with strong nonlinear dynamics.Fil: Skrjanc, Igor. University of Ljubljana; EsloveniaFil: Lepetic, Marko. University of Ljubljana; EsloveniaFil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur; ArgentinaFil: Brazic, Saso. University of Ljubljana; EsloveniaWorld Scientific and Engineering Academy and Society2004-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/104545Skrjanc, Igor; Lepetic, Marko; Figueroa, Jose Luis; Brazic, Saso; Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms; World Scientific and Engineering Academy and Society; Wseas Transactions on Systems; 3; 2; 4-2004; 789-7941109 27772224-2678CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.worldses.org/journals/systems/old.htminfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:24:16Zoai:ri.conicet.gov.ar:11336/104545instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:24:16.5CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
title Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
spellingShingle Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
Skrjanc, Igor
NONLINEAR PREDICTIVE CONTROL
FUZZY IDENTIFICATION
FUZZY MODEL PREDICTIVE CONTROL
title_short Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
title_full Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
title_fullStr Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
title_full_unstemmed Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
title_sort Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms
dc.creator.none.fl_str_mv Skrjanc, Igor
Lepetic, Marko
Figueroa, Jose Luis
Brazic, Saso
author Skrjanc, Igor
author_facet Skrjanc, Igor
Lepetic, Marko
Figueroa, Jose Luis
Brazic, Saso
author_role author
author2 Lepetic, Marko
Figueroa, Jose Luis
Brazic, Saso
author2_role author
author
author
dc.subject.none.fl_str_mv NONLINEAR PREDICTIVE CONTROL
FUZZY IDENTIFICATION
FUZZY MODEL PREDICTIVE CONTROL
topic NONLINEAR PREDICTIVE CONTROL
FUZZY IDENTIFICATION
FUZZY MODEL PREDICTIVE CONTROL
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In the paper a comparison of different nonlinear model-based predictive control algorithms is presented as a case study for a continuous stirred reactor. The focus is given to the fuzzy predictive control approach which is compared to Wiener based model predictive control and nonlinear model predictive control based on optimization. It has been shown that fuzzy predictive control law which is given in analytical form gives very promising results in comparison to other two approaches which are both based on optimization. All the proposed approaches are potentially interesting in the case of batch reactors, heat-exchangers, furnaces and all the processes with strong nonlinear dynamics.
Fil: Skrjanc, Igor. University of Ljubljana; Eslovenia
Fil: Lepetic, Marko. University of Ljubljana; Eslovenia
Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur; Argentina
Fil: Brazic, Saso. University of Ljubljana; Eslovenia
description In the paper a comparison of different nonlinear model-based predictive control algorithms is presented as a case study for a continuous stirred reactor. The focus is given to the fuzzy predictive control approach which is compared to Wiener based model predictive control and nonlinear model predictive control based on optimization. It has been shown that fuzzy predictive control law which is given in analytical form gives very promising results in comparison to other two approaches which are both based on optimization. All the proposed approaches are potentially interesting in the case of batch reactors, heat-exchangers, furnaces and all the processes with strong nonlinear dynamics.
publishDate 2004
dc.date.none.fl_str_mv 2004-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/104545
Skrjanc, Igor; Lepetic, Marko; Figueroa, Jose Luis; Brazic, Saso; Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms; World Scientific and Engineering Academy and Society; Wseas Transactions on Systems; 3; 2; 4-2004; 789-794
1109 2777
2224-2678
CONICET Digital
CONICET
url http://hdl.handle.net/11336/104545
identifier_str_mv Skrjanc, Igor; Lepetic, Marko; Figueroa, Jose Luis; Brazic, Saso; Fuzzy model-based predictive control for a CSTR with multiple steady state: A simulation study and a comparison with other nonlinear MBPC control algorithms; World Scientific and Engineering Academy and Society; Wseas Transactions on Systems; 3; 2; 4-2004; 789-794
1109 2777
2224-2678
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.worldses.org/journals/systems/old.htm
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv World Scientific and Engineering Academy and Society
publisher.none.fl_str_mv World Scientific and Engineering Academy and Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.48226

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