Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production

Autores
Fernández Puchol, María Cecilia; Pantano, Maria Nadia; Rodríguez, Leandro; Groff, Maria Carla; Montoro, Maria Laura; Scaglia, Gustavo Juan Eduardo
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The development of efficient strategies for optimizing and controlling nonlinear bioprocessesremains a significant challenge due to their complex dynamics and sensitivity tooperating conditions. This work addresses the problem by proposing a two-step methodologyapplied to a laboratory-scale fed-batch bioethanol process. The first step employsa dynamic optimization approach based on Fourier parameterization and orthonormalpolynomials, which generates smooth and continuous substrate-feed profiles using onlythree parameters instead of the ten required by piecewise approaches. The second stepintroduces a controller formulated through basic linear algebra operations, which ensuresaccurate trajectory tracking of the optimized state variables. Simulation results demonstratea 3.65% increase in ethanol concentration at the end of the process, together withan accumulated tracking error of only 0.0189 under nominal conditions. In addition, theclosed-loop strategy outperforms open-loop implementation when the initial conditionsdeviate from their nominal values. These findings highlight that the proposed methodologyreduces mathematical complexity and computational effort while producing continuouscontrol profiles suitable for practical application. The combination of optimization andalgebraic control thus provides a promising alternative for improving the efficiency ofbioethanol-production processes.
Fil: Fernández Puchol, María Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; 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. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Rodríguez, Leandro. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Groff, Maria Carla. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Montoro, Maria Laura. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Materia
DYNAMIC OPTIMIZATION
FOURIER SERIES
LINEAR ALGEBRA
NONLINEAR BIOPROCESSCONTROL
ORTHONORMAL POLYNOMIAL
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:11336/274537
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/274537
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol ProductionFernández Puchol, María CeciliaPantano, Maria NadiaRodríguez, LeandroGroff, Maria CarlaMontoro, Maria LauraScaglia, Gustavo Juan EduardoDYNAMIC OPTIMIZATIONFOURIER SERIESLINEAR ALGEBRANONLINEAR BIOPROCESSCONTROLORTHONORMAL POLYNOMIALhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2The development of efficient strategies for optimizing and controlling nonlinear bioprocessesremains a significant challenge due to their complex dynamics and sensitivity tooperating conditions. This work addresses the problem by proposing a two-step methodologyapplied to a laboratory-scale fed-batch bioethanol process. The first step employsa dynamic optimization approach based on Fourier parameterization and orthonormalpolynomials, which generates smooth and continuous substrate-feed profiles using onlythree parameters instead of the ten required by piecewise approaches. The second stepintroduces a controller formulated through basic linear algebra operations, which ensuresaccurate trajectory tracking of the optimized state variables. Simulation results demonstratea 3.65% increase in ethanol concentration at the end of the process, together withan accumulated tracking error of only 0.0189 under nominal conditions. In addition, theclosed-loop strategy outperforms open-loop implementation when the initial conditionsdeviate from their nominal values. These findings highlight that the proposed methodologyreduces mathematical complexity and computational effort while producing continuouscontrol profiles suitable for practical application. The combination of optimization andalgebraic control thus provides a promising alternative for improving the efficiency ofbioethanol-production processes.Fil: Fernández Puchol, María Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Pantano, Maria Nadia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Rodríguez, Leandro. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Groff, Maria Carla. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Montoro, Maria Laura. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaMDPI2025-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/274537Fernández Puchol, María Cecilia; Pantano, Maria Nadia; Rodríguez, Leandro; Groff, Maria Carla; Montoro, Maria Laura; et al.; Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production; MDPI; Processes; 13; 9; 8-2025; 1-162227-9717CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2227-9717/13/9/2792info:eu-repo/semantics/altIdentifier/doi/10.3390/pr13092792info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-12T09:56:29Zoai:ri.conicet.gov.ar:11336/274537instacron: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:34982025-11-12 09:56:29.355CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
title Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
spellingShingle Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
Fernández Puchol, María Cecilia
DYNAMIC OPTIMIZATION
FOURIER SERIES
LINEAR ALGEBRA
NONLINEAR BIOPROCESSCONTROL
ORTHONORMAL POLYNOMIAL
title_short Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
title_full Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
title_fullStr Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
title_full_unstemmed Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
title_sort Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production
dc.creator.none.fl_str_mv Fernández Puchol, María Cecilia
Pantano, Maria Nadia
Rodríguez, Leandro
Groff, Maria Carla
Montoro, Maria Laura
Scaglia, Gustavo Juan Eduardo
author Fernández Puchol, María Cecilia
author_facet Fernández Puchol, María Cecilia
Pantano, Maria Nadia
Rodríguez, Leandro
Groff, Maria Carla
Montoro, Maria Laura
Scaglia, Gustavo Juan Eduardo
author_role author
author2 Pantano, Maria Nadia
Rodríguez, Leandro
Groff, Maria Carla
Montoro, Maria Laura
Scaglia, Gustavo Juan Eduardo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv DYNAMIC OPTIMIZATION
FOURIER SERIES
LINEAR ALGEBRA
NONLINEAR BIOPROCESSCONTROL
ORTHONORMAL POLYNOMIAL
topic DYNAMIC OPTIMIZATION
FOURIER SERIES
LINEAR ALGEBRA
NONLINEAR BIOPROCESSCONTROL
ORTHONORMAL POLYNOMIAL
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 development of efficient strategies for optimizing and controlling nonlinear bioprocessesremains a significant challenge due to their complex dynamics and sensitivity tooperating conditions. This work addresses the problem by proposing a two-step methodologyapplied to a laboratory-scale fed-batch bioethanol process. The first step employsa dynamic optimization approach based on Fourier parameterization and orthonormalpolynomials, which generates smooth and continuous substrate-feed profiles using onlythree parameters instead of the ten required by piecewise approaches. The second stepintroduces a controller formulated through basic linear algebra operations, which ensuresaccurate trajectory tracking of the optimized state variables. Simulation results demonstratea 3.65% increase in ethanol concentration at the end of the process, together withan accumulated tracking error of only 0.0189 under nominal conditions. In addition, theclosed-loop strategy outperforms open-loop implementation when the initial conditionsdeviate from their nominal values. These findings highlight that the proposed methodologyreduces mathematical complexity and computational effort while producing continuouscontrol profiles suitable for practical application. The combination of optimization andalgebraic control thus provides a promising alternative for improving the efficiency ofbioethanol-production processes.
Fil: Fernández Puchol, María Cecilia. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; 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. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Rodríguez, Leandro. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Groff, Maria Carla. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Montoro, Maria Laura. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
description The development of efficient strategies for optimizing and controlling nonlinear bioprocessesremains a significant challenge due to their complex dynamics and sensitivity tooperating conditions. This work addresses the problem by proposing a two-step methodologyapplied to a laboratory-scale fed-batch bioethanol process. The first step employsa dynamic optimization approach based on Fourier parameterization and orthonormalpolynomials, which generates smooth and continuous substrate-feed profiles using onlythree parameters instead of the ten required by piecewise approaches. The second stepintroduces a controller formulated through basic linear algebra operations, which ensuresaccurate trajectory tracking of the optimized state variables. Simulation results demonstratea 3.65% increase in ethanol concentration at the end of the process, together withan accumulated tracking error of only 0.0189 under nominal conditions. In addition, theclosed-loop strategy outperforms open-loop implementation when the initial conditionsdeviate from their nominal values. These findings highlight that the proposed methodologyreduces mathematical complexity and computational effort while producing continuouscontrol profiles suitable for practical application. The combination of optimization andalgebraic control thus provides a promising alternative for improving the efficiency ofbioethanol-production processes.
publishDate 2025
dc.date.none.fl_str_mv 2025-08
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/11336/274537
Fernández Puchol, María Cecilia; Pantano, Maria Nadia; Rodríguez, Leandro; Groff, Maria Carla; Montoro, Maria Laura; et al.; Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production; MDPI; Processes; 13; 9; 8-2025; 1-16
2227-9717
CONICET Digital
CONICET
url http://hdl.handle.net/11336/274537
identifier_str_mv Fernández Puchol, María Cecilia; Pantano, Maria Nadia; Rodríguez, Leandro; Groff, Maria Carla; Montoro, Maria Laura; et al.; Fourier Optimization and Linear-Algebra-Based Combination of Controls to Improve Bioethanol Production; MDPI; Processes; 13; 9; 8-2025; 1-16
2227-9717
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2227-9717/13/9/2792
info:eu-repo/semantics/altIdentifier/doi/10.3390/pr13092792
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
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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 12.976206

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