Multivariable control structure design based on mixed-integer quadratic programming

Autores
Braccia, Lautaro; Marchetti, Pablo Andres; Luppi, Patricio Alfredo; Zumoffen, David Alejandro Ramon
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work a new approach to address multivariable control structure (MCS) design for medium/large-scale processes is proposed. The classical MCS design methodologies rely on superstructure representations which define sequential and/or bilevel mixed-integer nonlinear programming (MINLP) problems. The main drawbacks of this kind of approach are the complexity of the required solution methods (stochastic/deterministic global search), the computational time, and the optimality of the solution when simplifications are made. Instead, this work shows that, by using the sum of squared deviations (SSD) as well as the net load evaluation (NLE) concepts, the control structure design problem can be formulated as a mixed-integer quadratic programming (MIQP) model with linear constraints, featuring both optimality and improved computational performance due to state-of-the-art solvers. The formulation is implemented in the GAMS environment using CPLEX as the selected solver and two typical case studies are presented to show the benefits of the proposed approach.
Fil: Braccia, Lautaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Marchetti, Pablo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Luppi, Patricio Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina. Universidad Tecnológica Nacional. Facultad Regional Rosario; Argentina
Materia
PLANTWIDE PROCESS CONTROL
CONTROL STRUCTURE SELECTION
MIXED-INTEGER QUADRATIC PROGRAMMING
BILEVEL OPTIMIZATION PROBLEMS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/50345
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/50345
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Multivariable control structure design based on mixed-integer quadratic programmingBraccia, LautaroMarchetti, Pablo AndresLuppi, Patricio AlfredoZumoffen, David Alejandro RamonPLANTWIDE PROCESS CONTROLCONTROL STRUCTURE SELECTIONMIXED-INTEGER QUADRATIC PROGRAMMINGBILEVEL OPTIMIZATION PROBLEMShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this work a new approach to address multivariable control structure (MCS) design for medium/large-scale processes is proposed. The classical MCS design methodologies rely on superstructure representations which define sequential and/or bilevel mixed-integer nonlinear programming (MINLP) problems. The main drawbacks of this kind of approach are the complexity of the required solution methods (stochastic/deterministic global search), the computational time, and the optimality of the solution when simplifications are made. Instead, this work shows that, by using the sum of squared deviations (SSD) as well as the net load evaluation (NLE) concepts, the control structure design problem can be formulated as a mixed-integer quadratic programming (MIQP) model with linear constraints, featuring both optimality and improved computational performance due to state-of-the-art solvers. The formulation is implemented in the GAMS environment using CPLEX as the selected solver and two typical case studies are presented to show the benefits of the proposed approach.Fil: Braccia, Lautaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Marchetti, Pablo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Luppi, Patricio Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina. Universidad Tecnológica Nacional. Facultad Regional Rosario; ArgentinaAmerican Chemical Society2017-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/50345Braccia, Lautaro; Marchetti, Pablo Andres; Luppi, Patricio Alfredo; Zumoffen, David Alejandro Ramon; Multivariable control structure design based on mixed-integer quadratic programming; American Chemical Society; Industrial & Engineering Chemical Research; 56; 39; 9-2017; 11228-112440888-5885CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/doi/abs/10.1021/acs.iecr.7b02270info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.iecr.7b02270info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-17T11:47:31Zoai:ri.conicet.gov.ar:11336/50345instacron: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:34982025-09-17 11:47:31.896CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multivariable control structure design based on mixed-integer quadratic programming
title Multivariable control structure design based on mixed-integer quadratic programming
spellingShingle Multivariable control structure design based on mixed-integer quadratic programming
Braccia, Lautaro
PLANTWIDE PROCESS CONTROL
CONTROL STRUCTURE SELECTION
MIXED-INTEGER QUADRATIC PROGRAMMING
BILEVEL OPTIMIZATION PROBLEMS
title_short Multivariable control structure design based on mixed-integer quadratic programming
title_full Multivariable control structure design based on mixed-integer quadratic programming
title_fullStr Multivariable control structure design based on mixed-integer quadratic programming
title_full_unstemmed Multivariable control structure design based on mixed-integer quadratic programming
title_sort Multivariable control structure design based on mixed-integer quadratic programming
dc.creator.none.fl_str_mv Braccia, Lautaro
Marchetti, Pablo Andres
Luppi, Patricio Alfredo
Zumoffen, David Alejandro Ramon
author Braccia, Lautaro
author_facet Braccia, Lautaro
Marchetti, Pablo Andres
Luppi, Patricio Alfredo
Zumoffen, David Alejandro Ramon
author_role author
author2 Marchetti, Pablo Andres
Luppi, Patricio Alfredo
Zumoffen, David Alejandro Ramon
author2_role author
author
author
dc.subject.none.fl_str_mv PLANTWIDE PROCESS CONTROL
CONTROL STRUCTURE SELECTION
MIXED-INTEGER QUADRATIC PROGRAMMING
BILEVEL OPTIMIZATION PROBLEMS
topic PLANTWIDE PROCESS CONTROL
CONTROL STRUCTURE SELECTION
MIXED-INTEGER QUADRATIC PROGRAMMING
BILEVEL OPTIMIZATION PROBLEMS
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 this work a new approach to address multivariable control structure (MCS) design for medium/large-scale processes is proposed. The classical MCS design methodologies rely on superstructure representations which define sequential and/or bilevel mixed-integer nonlinear programming (MINLP) problems. The main drawbacks of this kind of approach are the complexity of the required solution methods (stochastic/deterministic global search), the computational time, and the optimality of the solution when simplifications are made. Instead, this work shows that, by using the sum of squared deviations (SSD) as well as the net load evaluation (NLE) concepts, the control structure design problem can be formulated as a mixed-integer quadratic programming (MIQP) model with linear constraints, featuring both optimality and improved computational performance due to state-of-the-art solvers. The formulation is implemented in the GAMS environment using CPLEX as the selected solver and two typical case studies are presented to show the benefits of the proposed approach.
Fil: Braccia, Lautaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Marchetti, Pablo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Luppi, Patricio Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina. Universidad Tecnológica Nacional. Facultad Regional Rosario; Argentina
description In this work a new approach to address multivariable control structure (MCS) design for medium/large-scale processes is proposed. The classical MCS design methodologies rely on superstructure representations which define sequential and/or bilevel mixed-integer nonlinear programming (MINLP) problems. The main drawbacks of this kind of approach are the complexity of the required solution methods (stochastic/deterministic global search), the computational time, and the optimality of the solution when simplifications are made. Instead, this work shows that, by using the sum of squared deviations (SSD) as well as the net load evaluation (NLE) concepts, the control structure design problem can be formulated as a mixed-integer quadratic programming (MIQP) model with linear constraints, featuring both optimality and improved computational performance due to state-of-the-art solvers. The formulation is implemented in the GAMS environment using CPLEX as the selected solver and two typical case studies are presented to show the benefits of the proposed approach.
publishDate 2017
dc.date.none.fl_str_mv 2017-09
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/11336/50345
Braccia, Lautaro; Marchetti, Pablo Andres; Luppi, Patricio Alfredo; Zumoffen, David Alejandro Ramon; Multivariable control structure design based on mixed-integer quadratic programming; American Chemical Society; Industrial & Engineering Chemical Research; 56; 39; 9-2017; 11228-11244
0888-5885
CONICET Digital
CONICET
url http://hdl.handle.net/11336/50345
identifier_str_mv Braccia, Lautaro; Marchetti, Pablo Andres; Luppi, Patricio Alfredo; Zumoffen, David Alejandro Ramon; Multivariable control structure design based on mixed-integer quadratic programming; American Chemical Society; Industrial & Engineering Chemical Research; 56; 39; 9-2017; 11228-11244
0888-5885
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://pubs.acs.org/doi/abs/10.1021/acs.iecr.7b02270
info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.iecr.7b02270
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical 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
_version_ 1843606823887699968
score 13.001348

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