Min-Max MPC based on a computationally efficient upper bound of the worst case cost

Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible cas...

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Autores: Rodríguez Ramírez, Daniel, Alamo, Teodoro, Camacho, Eduardo F., Muñoz de la Peña Sequedo, David
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2006
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/94724
Acceso en línea:https://hdl.handle.net/11441/94724
https://doi.org/10.1016/j.jprocont.2005.07.005
Access Level:acceso abierto
Palabra clave:Predictive control
Minimax techniques
Uncertain linear systems
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spelling Min-Max MPC based on a computationally efficient upper bound of the worst case costRodríguez Ramírez, DanielAlamo, TeodoroCamacho, Eduardo F.Muñoz de la Peña Sequedo, DavidPredictive controlMinimax techniquesUncertain linear systemsMin-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible case of a performance index have been used to reduce the computational burden. This paper proposes a computationally efficient MMMPC control strategy in which the worst case cost is approximated by an upper bound based on a diagonalization scheme. The upper bound can be computed with O(n3) operations and using only simple matrix operations. This implies that the algorithm can be coded easily even in non-mathematical oriented programming languages such as those found in industrial embedded control hardware. A simulation example is given in the paper.ElsevierIngeniería de Sistemas y Automática2006info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/94724https://doi.org/10.1016/j.jprocont.2005.07.005reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésJournal of Process Control, 16 (5), 511-519.https://www.sciencedirect.com/science/article/pii/S0959152405001009#!info:eu-repo/semantics/openAccessoai:idus.us.es:11441/947242026-06-17T12:51:07Z
dc.title.none.fl_str_mv Min-Max MPC based on a computationally efficient upper bound of the worst case cost
title Min-Max MPC based on a computationally efficient upper bound of the worst case cost
spellingShingle Min-Max MPC based on a computationally efficient upper bound of the worst case cost
Rodríguez Ramírez, Daniel
Predictive control
Minimax techniques
Uncertain linear systems
title_short Min-Max MPC based on a computationally efficient upper bound of the worst case cost
title_full Min-Max MPC based on a computationally efficient upper bound of the worst case cost
title_fullStr Min-Max MPC based on a computationally efficient upper bound of the worst case cost
title_full_unstemmed Min-Max MPC based on a computationally efficient upper bound of the worst case cost
title_sort Min-Max MPC based on a computationally efficient upper bound of the worst case cost
dc.creator.none.fl_str_mv Rodríguez Ramírez, Daniel
Alamo, Teodoro
Camacho, Eduardo F.
Muñoz de la Peña Sequedo, David
author Rodríguez Ramírez, Daniel
author_facet Rodríguez Ramírez, Daniel
Alamo, Teodoro
Camacho, Eduardo F.
Muñoz de la Peña Sequedo, David
author_role author
author2 Alamo, Teodoro
Camacho, Eduardo F.
Muñoz de la Peña Sequedo, David
author2_role author
author
author
dc.contributor.none.fl_str_mv Ingeniería de Sistemas y Automática
dc.subject.none.fl_str_mv Predictive control
Minimax techniques
Uncertain linear systems
topic Predictive control
Minimax techniques
Uncertain linear systems
description Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible case of a performance index have been used to reduce the computational burden. This paper proposes a computationally efficient MMMPC control strategy in which the worst case cost is approximated by an upper bound based on a diagonalization scheme. The upper bound can be computed with O(n3) operations and using only simple matrix operations. This implies that the algorithm can be coded easily even in non-mathematical oriented programming languages such as those found in industrial embedded control hardware. A simulation example is given in the paper.
publishDate 2006
dc.date.none.fl_str_mv 2006
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/94724
https://doi.org/10.1016/j.jprocont.2005.07.005
url https://hdl.handle.net/11441/94724
https://doi.org/10.1016/j.jprocont.2005.07.005
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Journal of Process Control, 16 (5), 511-519.
https://www.sciencedirect.com/science/article/pii/S0959152405001009#!
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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