INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT

Detalhes bibliográficos
Autor(a) principal: Martin,Paulo A.
Data de Publicação: 2019
Outros Autores: Zanin,Antonio C., Odloak,Darci
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Chemical Engineering
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000301205
Resumo: Abstract This work reports the integration of Real Time Optimization and Model Predictive Control in the multi-layer control structure of an existing Crude Distillation Unit (CDU) of an oil refinery. The MPC considers output control zones and targets for the inputs or outputs. Both the infinite horizon and the finite output horizon controllers were tested. The plant results show that the infinite horizon controller tends to perform similarly or better then the finite horizon MPC when the CDU system needs to operate at quite different conditions. Although the dynamic layer based on the infinite horizon controller is nominally stable for any set of tuning parameters, in practice, it is observed that the interaction between the layers of the control structure associated to model uncertainty may result in oscillations in some variables that fail to converge to the optimum operation point. This problem can be solved with the retuning of the intermediary layer (target calculation layer), which indicates that the frequent tuning of the MPC is recommended and should be performed in conjunction with tuning of the intermediary layer.
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spelling INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNITCrude distillation unitInfinite horizon MPCIntegration of RTO and MPCAbstract This work reports the integration of Real Time Optimization and Model Predictive Control in the multi-layer control structure of an existing Crude Distillation Unit (CDU) of an oil refinery. The MPC considers output control zones and targets for the inputs or outputs. Both the infinite horizon and the finite output horizon controllers were tested. The plant results show that the infinite horizon controller tends to perform similarly or better then the finite horizon MPC when the CDU system needs to operate at quite different conditions. Although the dynamic layer based on the infinite horizon controller is nominally stable for any set of tuning parameters, in practice, it is observed that the interaction between the layers of the control structure associated to model uncertainty may result in oscillations in some variables that fail to converge to the optimum operation point. This problem can be solved with the retuning of the intermediary layer (target calculation layer), which indicates that the frequent tuning of the MPC is recommended and should be performed in conjunction with tuning of the intermediary layer.Brazilian Society of Chemical Engineering2019-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000301205Brazilian Journal of Chemical Engineering v.36 n.3 2019reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/0104-6632.20190363s20170578info:eu-repo/semantics/openAccessMartin,Paulo A.Zanin,Antonio C.Odloak,Darcieng2019-12-04T00:00:00Zoai:scielo:S0104-66322019000301205Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2019-12-04T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false
dc.title.none.fl_str_mv INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
title INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
spellingShingle INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
Martin,Paulo A.
Crude distillation unit
Infinite horizon MPC
Integration of RTO and MPC
title_short INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
title_full INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
title_fullStr INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
title_full_unstemmed INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
title_sort INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT
author Martin,Paulo A.
author_facet Martin,Paulo A.
Zanin,Antonio C.
Odloak,Darci
author_role author
author2 Zanin,Antonio C.
Odloak,Darci
author2_role author
author
dc.contributor.author.fl_str_mv Martin,Paulo A.
Zanin,Antonio C.
Odloak,Darci
dc.subject.por.fl_str_mv Crude distillation unit
Infinite horizon MPC
Integration of RTO and MPC
topic Crude distillation unit
Infinite horizon MPC
Integration of RTO and MPC
description Abstract This work reports the integration of Real Time Optimization and Model Predictive Control in the multi-layer control structure of an existing Crude Distillation Unit (CDU) of an oil refinery. The MPC considers output control zones and targets for the inputs or outputs. Both the infinite horizon and the finite output horizon controllers were tested. The plant results show that the infinite horizon controller tends to perform similarly or better then the finite horizon MPC when the CDU system needs to operate at quite different conditions. Although the dynamic layer based on the infinite horizon controller is nominally stable for any set of tuning parameters, in practice, it is observed that the interaction between the layers of the control structure associated to model uncertainty may result in oscillations in some variables that fail to converge to the optimum operation point. This problem can be solved with the retuning of the intermediary layer (target calculation layer), which indicates that the frequent tuning of the MPC is recommended and should be performed in conjunction with tuning of the intermediary layer.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000301205
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000301205
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0104-6632.20190363s20170578
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
dc.source.none.fl_str_mv Brazilian Journal of Chemical Engineering v.36 n.3 2019
reponame:Brazilian Journal of Chemical Engineering
instname:Associação Brasileira de Engenharia Química (ABEQ)
instacron:ABEQ
instname_str Associação Brasileira de Engenharia Química (ABEQ)
instacron_str ABEQ
institution ABEQ
reponame_str Brazilian Journal of Chemical Engineering
collection Brazilian Journal of Chemical Engineering
repository.name.fl_str_mv Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)
repository.mail.fl_str_mv rgiudici@usp.br||rgiudici@usp.br
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