Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process

Autores
Zumoffen, David Alejandro Ramon; Basualdo, Marta Susana; Jordan, Mario Alberto; Ceccatto, Hermenegildo A.
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance, having an impact on safety, productivity, and plant economy. In this work, the main novelty is given by the enhancement produced through the integration of the fault detection and identification (FDI) system over a robust adaptive predictive control (RAPC) strategy specially thought to turn it as a fault- tolerant control (FTC) scheme. Additionally, the FDI itself is original because of the sensor and actuator faults treatment. The biases in sensors are detected and quantified by using wavelet decomposition and the extra delays in actuators by applying online identification techniques to appropriately modify the controller action. It is important to remark that the extra time delay, detected particularly at the actuators, is a problem that occurs frequently in practice; however, the academic community has mostly omitted it up to now. This methodology can improve the overall performance for nonlinear stable plants because the FDI is specifically designed as a complement of those aspects that RAPC cannot handle at all. The control technique involves a commutation of a linear time-varying robust filter in the feedback path of the control loop in synchronization with an adaptive predictive controller. Through simulation studies of a continuous stirred tank reactor (CSTR) with jacket, where the integration between FDI and FTC has been implemented, it can be shown that the proposed methodology leads to significant improvement in comparison with the same control scheme without FDI, particularly when the fault magnitude increases.
Fil: Zumoffen, David Alejandro Ramon. Universidad Tecnológica Nacional; Argentina
Fil: Basualdo, Marta Susana. Universidad Tecnológica Nacional; Argentina
Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Ceccatto, Hermenegildo A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
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:11336/30600
Acceder
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spelling Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical ProcessZumoffen, David Alejandro RamonBasualdo, Marta SusanaJordan, Mario AlbertoCeccatto, Hermenegildo A.https://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance, having an impact on safety, productivity, and plant economy. In this work, the main novelty is given by the enhancement produced through the integration of the fault detection and identification (FDI) system over a robust adaptive predictive control (RAPC) strategy specially thought to turn it as a fault- tolerant control (FTC) scheme. Additionally, the FDI itself is original because of the sensor and actuator faults treatment. The biases in sensors are detected and quantified by using wavelet decomposition and the extra delays in actuators by applying online identification techniques to appropriately modify the controller action. It is important to remark that the extra time delay, detected particularly at the actuators, is a problem that occurs frequently in practice; however, the academic community has mostly omitted it up to now. This methodology can improve the overall performance for nonlinear stable plants because the FDI is specifically designed as a complement of those aspects that RAPC cannot handle at all. The control technique involves a commutation of a linear time-varying robust filter in the feedback path of the control loop in synchronization with an adaptive predictive controller. Through simulation studies of a continuous stirred tank reactor (CSTR) with jacket, where the integration between FDI and FTC has been implemented, it can be shown that the proposed methodology leads to significant improvement in comparison with the same control scheme without FDI, particularly when the fault magnitude increases.Fil: Zumoffen, David Alejandro Ramon. Universidad Tecnológica Nacional; ArgentinaFil: Basualdo, Marta Susana. Universidad Tecnológica Nacional; ArgentinaFil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Ceccatto, Hermenegildo A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaAmerican Chemical Society2007-12info: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/11336/30600Zumoffen, David Alejandro Ramon; Basualdo, Marta Susana; Jordan, Mario Alberto; Ceccatto, Hermenegildo A.; Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process; American Chemical Society; Industrial & Engineering Chemical Research; 22; 12-2007; 7152-71630888-5885CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/journal/iecredinfo:eu-repo/semantics/altIdentifier/doi/10.1021/ie070019binfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:33:37Zoai:ri.conicet.gov.ar:11336/30600instacron: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 09:33:37.766CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
title Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
spellingShingle Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
Zumoffen, David Alejandro Ramon
title_short Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
title_full Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
title_fullStr Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
title_full_unstemmed Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
title_sort Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process
dc.creator.none.fl_str_mv Zumoffen, David Alejandro Ramon
Basualdo, Marta Susana
Jordan, Mario Alberto
Ceccatto, Hermenegildo A.
author Zumoffen, David Alejandro Ramon
author_facet Zumoffen, David Alejandro Ramon
Basualdo, Marta Susana
Jordan, Mario Alberto
Ceccatto, Hermenegildo A.
author_role author
author2 Basualdo, Marta Susana
Jordan, Mario Alberto
Ceccatto, Hermenegildo A.
author2_role author
author
author
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance, having an impact on safety, productivity, and plant economy. In this work, the main novelty is given by the enhancement produced through the integration of the fault detection and identification (FDI) system over a robust adaptive predictive control (RAPC) strategy specially thought to turn it as a fault- tolerant control (FTC) scheme. Additionally, the FDI itself is original because of the sensor and actuator faults treatment. The biases in sensors are detected and quantified by using wavelet decomposition and the extra delays in actuators by applying online identification techniques to appropriately modify the controller action. It is important to remark that the extra time delay, detected particularly at the actuators, is a problem that occurs frequently in practice; however, the academic community has mostly omitted it up to now. This methodology can improve the overall performance for nonlinear stable plants because the FDI is specifically designed as a complement of those aspects that RAPC cannot handle at all. The control technique involves a commutation of a linear time-varying robust filter in the feedback path of the control loop in synchronization with an adaptive predictive controller. Through simulation studies of a continuous stirred tank reactor (CSTR) with jacket, where the integration between FDI and FTC has been implemented, it can be shown that the proposed methodology leads to significant improvement in comparison with the same control scheme without FDI, particularly when the fault magnitude increases.
Fil: Zumoffen, David Alejandro Ramon. Universidad Tecnológica Nacional; Argentina
Fil: Basualdo, Marta Susana. Universidad Tecnológica Nacional; Argentina
Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Ceccatto, Hermenegildo A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
description Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance, having an impact on safety, productivity, and plant economy. In this work, the main novelty is given by the enhancement produced through the integration of the fault detection and identification (FDI) system over a robust adaptive predictive control (RAPC) strategy specially thought to turn it as a fault- tolerant control (FTC) scheme. Additionally, the FDI itself is original because of the sensor and actuator faults treatment. The biases in sensors are detected and quantified by using wavelet decomposition and the extra delays in actuators by applying online identification techniques to appropriately modify the controller action. It is important to remark that the extra time delay, detected particularly at the actuators, is a problem that occurs frequently in practice; however, the academic community has mostly omitted it up to now. This methodology can improve the overall performance for nonlinear stable plants because the FDI is specifically designed as a complement of those aspects that RAPC cannot handle at all. The control technique involves a commutation of a linear time-varying robust filter in the feedback path of the control loop in synchronization with an adaptive predictive controller. Through simulation studies of a continuous stirred tank reactor (CSTR) with jacket, where the integration between FDI and FTC has been implemented, it can be shown that the proposed methodology leads to significant improvement in comparison with the same control scheme without FDI, particularly when the fault magnitude increases.
publishDate 2007
dc.date.none.fl_str_mv 2007-12
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/11336/30600
Zumoffen, David Alejandro Ramon; Basualdo, Marta Susana; Jordan, Mario Alberto; Ceccatto, Hermenegildo A.; Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process; American Chemical Society; Industrial & Engineering Chemical Research; 22; 12-2007; 7152-7163
0888-5885
CONICET Digital
CONICET
url http://hdl.handle.net/11336/30600
identifier_str_mv Zumoffen, David Alejandro Ramon; Basualdo, Marta Susana; Jordan, Mario Alberto; Ceccatto, Hermenegildo A.; Robust Adaptive Predictive Fault-Tolerant Control Integrated to a Fault-Detection System Applied to a Nonlinear Chemical Process; American Chemical Society; Industrial & Engineering Chemical Research; 22; 12-2007; 7152-7163
0888-5885
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/journal/iecred
info:eu-repo/semantics/altIdentifier/doi/10.1021/ie070019b
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 American Chemical Society
publisher.none.fl_str_mv American Chemical Society
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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