State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system

Autores
Fernández, Maria Cecilia; Pantano, Maria Nadia; Rossomando, Francisco Guido; Ortiz, Oscar Alberto; Scaglia, Gustavo Juan Eduardo
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural network states estimation is designed in order to know those variables that cannot be measured. The controller is tuned using a Monte Carlo experiment for which a cost function that penalizes tracking errors is defned. Moreover, several tests (adding parametric uncertainty and perturbations in the control action) are carried out so as to evaluate the controller performance. A comparison with another controller is made. The demonstration of the error convergence, as well as the stability analysis of the neural network, are included.
Fil: Fernández, Maria Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Pantano, Maria Nadia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
Fil: Ortiz, Oscar Alberto. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Scaglia, Gustavo Juan Eduardo. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
FED-BATCH BIOPROCESS
NONLINEAR AND MULTIVARIABLE SYSTEM
NUMERICAL METHODS/LINEAR ALGEBRA
PROFLES TRACKING CONTROL
STATE ESTIMATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/124802
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production systemFernández, Maria CeciliaPantano, Maria NadiaRossomando, Francisco GuidoOrtiz, Oscar AlbertoScaglia, Gustavo Juan EduardoFED-BATCH BIOPROCESSNONLINEAR AND MULTIVARIABLE SYSTEMNUMERICAL METHODS/LINEAR ALGEBRAPROFLES TRACKING CONTROLSTATE ESTIMATIONhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural network states estimation is designed in order to know those variables that cannot be measured. The controller is tuned using a Monte Carlo experiment for which a cost function that penalizes tracking errors is defned. Moreover, several tests (adding parametric uncertainty and perturbations in the control action) are carried out so as to evaluate the controller performance. A comparison with another controller is made. The demonstration of the error convergence, as well as the stability analysis of the neural network, are included.Fil: Fernández, Maria Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Pantano, Maria Nadia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Ortiz, Oscar Alberto. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Scaglia, Gustavo Juan Eduardo. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaBrazilian Society of Chemical Engineering2019-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/124802Fernández, Maria Cecilia; Pantano, Maria Nadia; Rossomando, Francisco Guido; Ortiz, Oscar Alberto; Scaglia, Gustavo Juan Eduardo; State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system; Brazilian Society of Chemical Engineering; Brazilian Journal of Chemical Engineering; 36; 1; 3-2019; 421-4370104-66321678-4383CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1590/0104-6632.20190361s20170379info:eu-repo/semantics/altIdentifier/url/https://www.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000100421&tlng=eninfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-29T12:55:25Zoai:ri.conicet.gov.ar:11336/124802instacron: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:34982025-10-29 12:55:25.604CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
title State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
spellingShingle State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
Fernández, Maria Cecilia
FED-BATCH BIOPROCESS
NONLINEAR AND MULTIVARIABLE SYSTEM
NUMERICAL METHODS/LINEAR ALGEBRA
PROFLES TRACKING CONTROL
STATE ESTIMATION
title_short State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
title_full State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
title_fullStr State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
title_full_unstemmed State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
title_sort State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system
dc.creator.none.fl_str_mv Fernández, Maria Cecilia
Pantano, Maria Nadia
Rossomando, Francisco Guido
Ortiz, Oscar Alberto
Scaglia, Gustavo Juan Eduardo
author Fernández, Maria Cecilia
author_facet Fernández, Maria Cecilia
Pantano, Maria Nadia
Rossomando, Francisco Guido
Ortiz, Oscar Alberto
Scaglia, Gustavo Juan Eduardo
author_role author
author2 Pantano, Maria Nadia
Rossomando, Francisco Guido
Ortiz, Oscar Alberto
Scaglia, Gustavo Juan Eduardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv FED-BATCH BIOPROCESS
NONLINEAR AND MULTIVARIABLE SYSTEM
NUMERICAL METHODS/LINEAR ALGEBRA
PROFLES TRACKING CONTROL
STATE ESTIMATION
topic FED-BATCH BIOPROCESS
NONLINEAR AND MULTIVARIABLE SYSTEM
NUMERICAL METHODS/LINEAR ALGEBRA
PROFLES TRACKING CONTROL
STATE ESTIMATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural network states estimation is designed in order to know those variables that cannot be measured. The controller is tuned using a Monte Carlo experiment for which a cost function that penalizes tracking errors is defned. Moreover, several tests (adding parametric uncertainty and perturbations in the control action) are carried out so as to evaluate the controller performance. A comparison with another controller is made. The demonstration of the error convergence, as well as the stability analysis of the neural network, are included.
Fil: Fernández, Maria Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Pantano, Maria Nadia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
Fil: Ortiz, Oscar Alberto. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Scaglia, Gustavo Juan Eduardo. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural network states estimation is designed in order to know those variables that cannot be measured. The controller is tuned using a Monte Carlo experiment for which a cost function that penalizes tracking errors is defned. Moreover, several tests (adding parametric uncertainty and perturbations in the control action) are carried out so as to evaluate the controller performance. A comparison with another controller is made. The demonstration of the error convergence, as well as the stability analysis of the neural network, are included.
publishDate 2019
dc.date.none.fl_str_mv 2019-03
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/11336/124802
Fernández, Maria Cecilia; Pantano, Maria Nadia; Rossomando, Francisco Guido; Ortiz, Oscar Alberto; Scaglia, Gustavo Juan Eduardo; State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system; Brazilian Society of Chemical Engineering; Brazilian Journal of Chemical Engineering; 36; 1; 3-2019; 421-437
0104-6632
1678-4383
CONICET Digital
CONICET
url http://hdl.handle.net/11336/124802
identifier_str_mv Fernández, Maria Cecilia; Pantano, Maria Nadia; Rossomando, Francisco Guido; Ortiz, Oscar Alberto; Scaglia, Gustavo Juan Eduardo; State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system; Brazilian Society of Chemical Engineering; Brazilian Journal of Chemical Engineering; 36; 1; 3-2019; 421-437
0104-6632
1678-4383
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1590/0104-6632.20190361s20170379
info:eu-repo/semantics/altIdentifier/url/https://www.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322019000100421&tlng=en
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
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 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
_version_ 1847427661042810880
score 13.10058

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