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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/42999
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T10:03:36Zoai: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:34982025-09-03 10:03:36.519CONICET 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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1842269810037096448 |
score |
13.13397 |