Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection

Autores
Bottari, Agustin; Marchetti, Pablo Andres; Marchetti, Alejandro Gabriel
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.
Fil: Bottari, Agustin. 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: Marchetti, Alejandro Gabriel. 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
Materia
Self-Optimizing
Steady-State
Control Structure Selection
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:11336/150896
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Self-Optimizing Steady-State Back-Off Approach for Control Structure SelectionBottari, AgustinMarchetti, Pablo AndresMarchetti, Alejandro GabrielSelf-OptimizingSteady-StateControl Structure Selectionhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.Fil: Bottari, Agustin. 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: Marchetti, Alejandro Gabriel. 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; ArgentinaAmerican Chemical Society2019-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/150896Bottari, Agustin; Marchetti, Pablo Andres; Marchetti, Alejandro Gabriel; Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection; American Chemical Society; Industrial & Engineering Chemical Research; 58; 30; 3-2019; 13699-137170888-5885CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1021/acs.iecr.8b06296info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/10.1021/acs.iecr.8b06296info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:08:18Zoai:ri.conicet.gov.ar:11336/150896instacron: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 13:08:19.04CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
title Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
spellingShingle Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
Bottari, Agustin
Self-Optimizing
Steady-State
Control Structure Selection
title_short Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
title_full Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
title_fullStr Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
title_full_unstemmed Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
title_sort Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection
dc.creator.none.fl_str_mv Bottari, Agustin
Marchetti, Pablo Andres
Marchetti, Alejandro Gabriel
author Bottari, Agustin
author_facet Bottari, Agustin
Marchetti, Pablo Andres
Marchetti, Alejandro Gabriel
author_role author
author2 Marchetti, Pablo Andres
Marchetti, Alejandro Gabriel
author2_role author
author
dc.subject.none.fl_str_mv Self-Optimizing
Steady-State
Control Structure Selection
topic Self-Optimizing
Steady-State
Control Structure Selection
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.
Fil: Bottari, Agustin. 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: Marchetti, Alejandro Gabriel. 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
description The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.
publishDate 2019
dc.date.none.fl_str_mv 2019-03
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/11336/150896
Bottari, Agustin; Marchetti, Pablo Andres; Marchetti, Alejandro Gabriel; Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection; American Chemical Society; Industrial & Engineering Chemical Research; 58; 30; 3-2019; 13699-13717
0888-5885
CONICET Digital
CONICET
url http://hdl.handle.net/11336/150896
identifier_str_mv Bottari, Agustin; Marchetti, Pablo Andres; Marchetti, Alejandro Gabriel; Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection; American Chemical Society; Industrial & Engineering Chemical Research; 58; 30; 3-2019; 13699-13717
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/doi/10.1021/acs.iecr.8b06296
info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/10.1021/acs.iecr.8b06296
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 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
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score 12.993085

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