Unscented Kalman Filter. Application of the robust approach to polymerization processes

Autores
Tupaz Pantoja, Jhovany Alexander; Asteasuain, Mariano; Sanchez, Mabel Cristina
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The control of polymerization processes has central importance because operational conditions affect the processing and end-use properties of the product. The nonlinear controllers based upon rigorous models make use of the on-line state estimates obtained from the available measurements. For polymerization processes, the Unscented Kalman Filter has shown a rewarding performance for state estimation. Because the presence of outliers distorts the behaviour of the filter, Robust Statistics-based approaches have been proposed to reduce their detrimental effect on variable estimates. Until now, only Huber type M-estimators have been used as loss function of the estimation problem. In this work, the ability of other types of M-estimators to improve estimate robustness without introducing numerical problems is analysed. The performances of the M-estimators are compared for a copolymerization process within the framework of a filtering technique based on the Unscented Transformation, which uses a reformulation of the covariance of measurements errors.
Fil: Tupaz Pantoja, Jhovany Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
Fil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
Materia
Copolymerization
M-Estimators
Outliers
Robust Filtering
Unscented Kalman Filter
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:11336/42999
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/42999
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Unscented Kalman Filter. Application of the robust approach to polymerization processesTupaz Pantoja, Jhovany AlexanderAsteasuain, MarianoSanchez, Mabel CristinaCopolymerizationM-EstimatorsOutliersRobust FilteringUnscented Kalman Filterhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2The control of polymerization processes has central importance because operational conditions affect the processing and end-use properties of the product. The nonlinear controllers based upon rigorous models make use of the on-line state estimates obtained from the available measurements. For polymerization processes, the Unscented Kalman Filter has shown a rewarding performance for state estimation. Because the presence of outliers distorts the behaviour of the filter, Robust Statistics-based approaches have been proposed to reduce their detrimental effect on variable estimates. Until now, only Huber type M-estimators have been used as loss function of the estimation problem. In this work, the ability of other types of M-estimators to improve estimate robustness without introducing numerical problems is analysed. The performances of the M-estimators are compared for a copolymerization process within the framework of a filtering technique based on the Unscented Transformation, which uses a reformulation of the covariance of measurements errors.Fil: Tupaz Pantoja, Jhovany Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaFil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaFil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaElsevier2017-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/42999Tupaz Pantoja, Jhovany Alexander; Asteasuain, Mariano; Sanchez, Mabel Cristina; Unscented Kalman Filter. Application of the robust approach to polymerization processes; Elsevier; Computer Aided Chemical Engineering; 40; 10-2017; 1477-14821570-7946CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/B978-0-444-63965-3.50248-8info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/B9780444639653502488info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T10:25:22Zoai:ri.conicet.gov.ar:11336/42999instacron: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:34982025-11-05 10:25:23.067CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Unscented Kalman Filter. Application of the robust approach to polymerization processes
title Unscented Kalman Filter. Application of the robust approach to polymerization processes
spellingShingle Unscented Kalman Filter. Application of the robust approach to polymerization processes
Tupaz Pantoja, Jhovany Alexander
Copolymerization
M-Estimators
Outliers
Robust Filtering
Unscented Kalman Filter
title_short Unscented Kalman Filter. Application of the robust approach to polymerization processes
title_full Unscented Kalman Filter. Application of the robust approach to polymerization processes
title_fullStr Unscented Kalman Filter. Application of the robust approach to polymerization processes
title_full_unstemmed Unscented Kalman Filter. Application of the robust approach to polymerization processes
title_sort Unscented Kalman Filter. Application of the robust approach to polymerization processes
dc.creator.none.fl_str_mv Tupaz Pantoja, Jhovany Alexander
Asteasuain, Mariano
Sanchez, Mabel Cristina
author Tupaz Pantoja, Jhovany Alexander
author_facet Tupaz Pantoja, Jhovany Alexander
Asteasuain, Mariano
Sanchez, Mabel Cristina
author_role author
author2 Asteasuain, Mariano
Sanchez, Mabel Cristina
author2_role author
author
dc.subject.none.fl_str_mv Copolymerization
M-Estimators
Outliers
Robust Filtering
Unscented Kalman Filter
topic Copolymerization
M-Estimators
Outliers
Robust Filtering
Unscented Kalman Filter
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The control of polymerization processes has central importance because operational conditions affect the processing and end-use properties of the product. The nonlinear controllers based upon rigorous models make use of the on-line state estimates obtained from the available measurements. For polymerization processes, the Unscented Kalman Filter has shown a rewarding performance for state estimation. Because the presence of outliers distorts the behaviour of the filter, Robust Statistics-based approaches have been proposed to reduce their detrimental effect on variable estimates. Until now, only Huber type M-estimators have been used as loss function of the estimation problem. In this work, the ability of other types of M-estimators to improve estimate robustness without introducing numerical problems is analysed. The performances of the M-estimators are compared for a copolymerization process within the framework of a filtering technique based on the Unscented Transformation, which uses a reformulation of the covariance of measurements errors.
Fil: Tupaz Pantoja, Jhovany Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
Fil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; Argentina
description The control of polymerization processes has central importance because operational conditions affect the processing and end-use properties of the product. The nonlinear controllers based upon rigorous models make use of the on-line state estimates obtained from the available measurements. For polymerization processes, the Unscented Kalman Filter has shown a rewarding performance for state estimation. Because the presence of outliers distorts the behaviour of the filter, Robust Statistics-based approaches have been proposed to reduce their detrimental effect on variable estimates. Until now, only Huber type M-estimators have been used as loss function of the estimation problem. In this work, the ability of other types of M-estimators to improve estimate robustness without introducing numerical problems is analysed. The performances of the M-estimators are compared for a copolymerization process within the framework of a filtering technique based on the Unscented Transformation, which uses a reformulation of the covariance of measurements errors.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
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/11336/42999
Tupaz Pantoja, Jhovany Alexander; Asteasuain, Mariano; Sanchez, Mabel Cristina; Unscented Kalman Filter. Application of the robust approach to polymerization processes; Elsevier; Computer Aided Chemical Engineering; 40; 10-2017; 1477-1482
1570-7946
CONICET Digital
CONICET
url http://hdl.handle.net/11336/42999
identifier_str_mv Tupaz Pantoja, Jhovany Alexander; Asteasuain, Mariano; Sanchez, Mabel Cristina; Unscented Kalman Filter. Application of the robust approach to polymerization processes; Elsevier; Computer Aided Chemical Engineering; 40; 10-2017; 1477-1482
1570-7946
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/B978-0-444-63965-3.50248-8
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/B9780444639653502488
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
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 13.087074

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