Advanced control of propylene polimerizations in slurry reactors

Detalhes bibliográficos
Autor(a) principal: Bolsoni,A.
Data de Publicação: 2000
Outros Autores: Lima,E.L., Pinto,J.C.
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=S0104-66322000000400021
Resumo: The objective of this work is to develop a strategy of nonlinear model predictive control for industrial slurry reactors of propylene polymerizations. The controlled variables are the melt index (polymer quality) and the amount of unreacted monomer (productivity). The model used in the controller presents a linear dynamics and a nonlinear static gain given by a neuronal network MLP (multilayer perceptron). The simulated performance of the controller was evaluated for a typical propylene polymerization process. It is shown that the performance of the proposed control strategy is much better than the one obtained with the use of linear predictive controllers for setpoint tracking control problems.
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spelling Advanced control of propylene polimerizations in slurry reactorsPredictive ControlPolymerization ReactorsNeural NetworksMelt IndexThe objective of this work is to develop a strategy of nonlinear model predictive control for industrial slurry reactors of propylene polymerizations. The controlled variables are the melt index (polymer quality) and the amount of unreacted monomer (productivity). The model used in the controller presents a linear dynamics and a nonlinear static gain given by a neuronal network MLP (multilayer perceptron). The simulated performance of the controller was evaluated for a typical propylene polymerization process. It is shown that the performance of the proposed control strategy is much better than the one obtained with the use of linear predictive controllers for setpoint tracking control problems.Brazilian Society of Chemical Engineering2000-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322000000400021Brazilian Journal of Chemical Engineering v.17 n.4-7 2000reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/S0104-66322000000400021info:eu-repo/semantics/openAccessBolsoni,A.Lima,E.L.Pinto,J.C.eng2001-03-16T00:00:00Zoai:scielo:S0104-66322000000400021Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2001-03-16T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false
dc.title.none.fl_str_mv Advanced control of propylene polimerizations in slurry reactors
title Advanced control of propylene polimerizations in slurry reactors
spellingShingle Advanced control of propylene polimerizations in slurry reactors
Bolsoni,A.
Predictive Control
Polymerization Reactors
Neural Networks
Melt Index
title_short Advanced control of propylene polimerizations in slurry reactors
title_full Advanced control of propylene polimerizations in slurry reactors
title_fullStr Advanced control of propylene polimerizations in slurry reactors
title_full_unstemmed Advanced control of propylene polimerizations in slurry reactors
title_sort Advanced control of propylene polimerizations in slurry reactors
author Bolsoni,A.
author_facet Bolsoni,A.
Lima,E.L.
Pinto,J.C.
author_role author
author2 Lima,E.L.
Pinto,J.C.
author2_role author
author
dc.contributor.author.fl_str_mv Bolsoni,A.
Lima,E.L.
Pinto,J.C.
dc.subject.por.fl_str_mv Predictive Control
Polymerization Reactors
Neural Networks
Melt Index
topic Predictive Control
Polymerization Reactors
Neural Networks
Melt Index
description The objective of this work is to develop a strategy of nonlinear model predictive control for industrial slurry reactors of propylene polymerizations. The controlled variables are the melt index (polymer quality) and the amount of unreacted monomer (productivity). The model used in the controller presents a linear dynamics and a nonlinear static gain given by a neuronal network MLP (multilayer perceptron). The simulated performance of the controller was evaluated for a typical propylene polymerization process. It is shown that the performance of the proposed control strategy is much better than the one obtained with the use of linear predictive controllers for setpoint tracking control problems.
publishDate 2000
dc.date.none.fl_str_mv 2000-12-01
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=S0104-66322000000400021
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322000000400021
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0104-66322000000400021
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.17 n.4-7 2000
reponame:Brazilian Journal of Chemical Engineering
instname:Associação Brasileira de Engenharia Química (ABEQ)
instacron:ABEQ
instname_str Associação Brasileira de Engenharia Química (ABEQ)
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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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