MPC for tracking zone regions

Autores
Ferramosca, Antonio; Limón, Daniel; González, Alejandro Hernán; Odloak, Darci; Camacho, Eduardo
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables – possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column.
Fil: Ferramosca, Antonio. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España. Universidad Tecnológica Nacional. Facultad Regional Reconquista; Argentina. 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: Limón, Daniel. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España
Fil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Odloak, Darci. Universidade de Sao Paulo; Brasil
Fil: Camacho, Eduardo. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España
Materia
Model Predictive Control
Tracking
Optimality
Zone 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:11336/13443
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/13443
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling MPC for tracking zone regionsFerramosca, AntonioLimón, DanielGonzález, Alejandro HernánOdloak, DarciCamacho, EduardoModel Predictive ControlTrackingOptimalityZone Controlhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables – possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column.Fil: Ferramosca, Antonio. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España. Universidad Tecnológica Nacional. Facultad Regional Reconquista; Argentina. 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: Limón, Daniel. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; EspañaFil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Odloak, Darci. Universidade de Sao Paulo; BrasilFil: Camacho, Eduardo. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; EspañaElsevier2010-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/13443Ferramosca, Antonio; Limón, Daniel; González, Alejandro Hernán; Odloak, Darci; Camacho, Eduardo; MPC for tracking zone regions; Elsevier; Journal Of Process Control; 20; 1-2010; 506-5160959-1524enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jprocont.2010.02.005info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0959152410000466info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:59:16Zoai:ri.conicet.gov.ar:11336/13443instacron: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:34982025-09-29 09:59:16.822CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv MPC for tracking zone regions
title MPC for tracking zone regions
spellingShingle MPC for tracking zone regions
Ferramosca, Antonio
Model Predictive Control
Tracking
Optimality
Zone Control
title_short MPC for tracking zone regions
title_full MPC for tracking zone regions
title_fullStr MPC for tracking zone regions
title_full_unstemmed MPC for tracking zone regions
title_sort MPC for tracking zone regions
dc.creator.none.fl_str_mv Ferramosca, Antonio
Limón, Daniel
González, Alejandro Hernán
Odloak, Darci
Camacho, Eduardo
author Ferramosca, Antonio
author_facet Ferramosca, Antonio
Limón, Daniel
González, Alejandro Hernán
Odloak, Darci
Camacho, Eduardo
author_role author
author2 Limón, Daniel
González, Alejandro Hernán
Odloak, Darci
Camacho, Eduardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Model Predictive Control
Tracking
Optimality
Zone Control
topic Model Predictive Control
Tracking
Optimality
Zone 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 This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables – possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column.
Fil: Ferramosca, Antonio. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España. Universidad Tecnológica Nacional. Facultad Regional Reconquista; Argentina. 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: Limón, Daniel. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España
Fil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Odloak, Darci. Universidade de Sao Paulo; Brasil
Fil: Camacho, Eduardo. Universidad de Sevilla. Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros Industriales; España
description This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables – possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column.
publishDate 2010
dc.date.none.fl_str_mv 2010-01
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/11336/13443
Ferramosca, Antonio; Limón, Daniel; González, Alejandro Hernán; Odloak, Darci; Camacho, Eduardo; MPC for tracking zone regions; Elsevier; Journal Of Process Control; 20; 1-2010; 506-516
0959-1524
url http://hdl.handle.net/11336/13443
identifier_str_mv Ferramosca, Antonio; Limón, Daniel; González, Alejandro Hernán; Odloak, Darci; Camacho, Eduardo; MPC for tracking zone regions; Elsevier; Journal Of Process Control; 20; 1-2010; 506-516
0959-1524
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jprocont.2010.02.005
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0959152410000466
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
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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 13.070432

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