A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger

Autores
Pipino, Hugo; Adam, Eduardo J.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Most industrial processes are nonlinear, which complicates the application of conventional Model-based Predictive Control (MPC) algorithms. Consequently, in this article, the formulations of MPC methods for nonlinear processes represented through polytopic Linear Parameter-Varying models are analysed. The compared methods are adaptive algorithm, synthesised with a prediction model based on a scheduling polytope. At each discrete sampling instant, they determine a model, used for prediction purposes; and optimise the process performances over a finite prediction horizon. These methods are applied to control of a Heat Exchanger system, from which the performance and effectiveness of each technique are discussed. The simulation results are thoroughly analyzed, and the advantages and disadvantages of each strategy are discussed.
Fil: Pipino, Hugo. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina.
Fil: Adam, Eduardo J. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina.
Fuente
XX Workshop on Information Processing and Control (RPIC): 229 - 234 (2023).
Materia
Model-based predictive control
Linear parameter-varying
Nonlinear system
Heat exchanger
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-08-05T18:46:51Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/11241
Acceder
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network_name_str Repositorio Institucional Abierto (UTN)
spelling A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat ExchangerPipino, HugoAdam, Eduardo J.Model-based predictive controlLinear parameter-varyingNonlinear systemHeat exchangerMost industrial processes are nonlinear, which complicates the application of conventional Model-based Predictive Control (MPC) algorithms. Consequently, in this article, the formulations of MPC methods for nonlinear processes represented through polytopic Linear Parameter-Varying models are analysed. The compared methods are adaptive algorithm, synthesised with a prediction model based on a scheduling polytope. At each discrete sampling instant, they determine a model, used for prediction purposes; and optimise the process performances over a finite prediction horizon. These methods are applied to control of a Heat Exchanger system, from which the performance and effectiveness of each technique are discussed. The simulation results are thoroughly analyzed, and the advantages and disadvantages of each strategy are discussed.Fil: Pipino, Hugo. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina.Fil: Adam, Eduardo J. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina.Universidad Nacional de Misiones. Facultad de Ingeniería.2024-08-05T18:46:51Z2024-08-05T18:46:51Z2023-11-03info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaplainapplication/pdf2023 XX Workshop on Information Processing and Control (RPIC)978-950-766-230-0http://hdl.handle.net/20.500.12272/11241XX Workshop on Information Processing and Control (RPIC): 229 - 234 (2023).reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica NacionalengengNacionalinfo:eu-repo/semantics/openAccess2024-08-05T18:46:51Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacional.2026-09-24T12:48:03Zoai:ria.utn.edu.ar:20.500.12272/11241instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:48:05.925Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
title A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
spellingShingle A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
Pipino, Hugo
Model-based predictive control
Linear parameter-varying
Nonlinear system
Heat exchanger
title_short A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
title_full A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
title_fullStr A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
title_full_unstemmed A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
title_sort A Comparative Analysis of Adaptive Predictive Control Methods Applied in a Heat Exchanger
dc.creator.none.fl_str_mv Pipino, Hugo
Adam, Eduardo J.
author Pipino, Hugo
author_facet Pipino, Hugo
Adam, Eduardo J.
author_role author
author2 Adam, Eduardo J.
author2_role author
dc.subject.none.fl_str_mv Model-based predictive control
Linear parameter-varying
Nonlinear system
Heat exchanger
topic Model-based predictive control
Linear parameter-varying
Nonlinear system
Heat exchanger
dc.description.none.fl_txt_mv Most industrial processes are nonlinear, which complicates the application of conventional Model-based Predictive Control (MPC) algorithms. Consequently, in this article, the formulations of MPC methods for nonlinear processes represented through polytopic Linear Parameter-Varying models are analysed. The compared methods are adaptive algorithm, synthesised with a prediction model based on a scheduling polytope. At each discrete sampling instant, they determine a model, used for prediction purposes; and optimise the process performances over a finite prediction horizon. These methods are applied to control of a Heat Exchanger system, from which the performance and effectiveness of each technique are discussed. The simulation results are thoroughly analyzed, and the advantages and disadvantages of each strategy are discussed.
Fil: Pipino, Hugo. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina.
Fil: Adam, Eduardo J. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina.
description Most industrial processes are nonlinear, which complicates the application of conventional Model-based Predictive Control (MPC) algorithms. Consequently, in this article, the formulations of MPC methods for nonlinear processes represented through polytopic Linear Parameter-Varying models are analysed. The compared methods are adaptive algorithm, synthesised with a prediction model based on a scheduling polytope. At each discrete sampling instant, they determine a model, used for prediction purposes; and optimise the process performances over a finite prediction horizon. These methods are applied to control of a Heat Exchanger system, from which the performance and effectiveness of each technique are discussed. The simulation results are thoroughly analyzed, and the advantages and disadvantages of each strategy are discussed.
publishDate 2023
dc.date.none.fl_str_mv 2023-11-03
2024-08-05T18:46:51Z
2024-08-05T18:46:51Z
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv 2023 XX Workshop on Information Processing and Control (RPIC)
978-950-766-230-0
http://hdl.handle.net/20.500.12272/11241
identifier_str_mv 2023 XX Workshop on Information Processing and Control (RPIC)
978-950-766-230-0
url http://hdl.handle.net/20.500.12272/11241
dc.language.none.fl_str_mv eng
eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-08-05T18:46:51Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
.
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-08-05T18:46:51Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
.
dc.format.none.fl_str_mv plain
application/pdf
dc.coverage.none.fl_str_mv Nacional
dc.publisher.none.fl_str_mv Universidad Nacional de Misiones. Facultad de Ingeniería.
publisher.none.fl_str_mv Universidad Nacional de Misiones. Facultad de Ingeniería.
dc.source.none.fl_str_mv XX Workshop on Information Processing and Control (RPIC): 229 - 234 (2023).
reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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