Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações

Autores
Coelho, Leandro dos Santos; Coelho, Antonio Augusto Rodrigues
Año de publicación
1997
Idioma
portugués
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper several evolutionary computation paradigms in process identification and control are utilized. The following methodologies are addressed: i) genetic algorithms (with floating point representation), ii) hybrid algorithms composed by genetic algorithms with simulated annealing, and iii) evolution strategies (without and with self-adaptation mechanisms). Experiments in identification were conducted in mono-tank level and temperature processes. Experimental tests in control are conducted in order to find the design parameter of the PID control when controlling a non-linear level process, composed of coupled twin-tanks, which are submitted to reference change and load disturbance, and steering a trailer truck while backing up to a loading dock.
Eje: Workshop sobre Aspectos Teoricos de la Inteligencia Artificial
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Applications
genetic algorithms
evolution strategies
process identification
process control
practical application
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/24061

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network_name_str SEDICI (UNLP)
spelling Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicaçõesCoelho, Leandro dos SantosCoelho, Antonio Augusto RodriguesCiencias InformáticasARTIFICIAL INTELLIGENCEAlgorithmsApplicationsgenetic algorithmsevolution strategiesprocess identificationprocess controlpractical applicationIn this paper several evolutionary computation paradigms in process identification and control are utilized. The following methodologies are addressed: i) genetic algorithms (with floating point representation), ii) hybrid algorithms composed by genetic algorithms with simulated annealing, and iii) evolution strategies (without and with self-adaptation mechanisms). Experiments in identification were conducted in mono-tank level and temperature processes. Experimental tests in control are conducted in order to find the design parameter of the PID control when controlling a non-linear level process, composed of coupled twin-tanks, which are submitted to reference change and load disturbance, and steering a trailer truck while backing up to a loading dock.Eje: Workshop sobre Aspectos Teoricos de la Inteligencia ArtificialRed de Universidades con Carreras en Informática (RedUNCI)1997info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/24061info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)porreponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:41Zoai:sedici.unlp.edu.ar:10915/24061Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:41.548SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
title Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
spellingShingle Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
Coelho, Leandro dos Santos
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Applications
genetic algorithms
evolution strategies
process identification
process control
practical application
title_short Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
title_full Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
title_fullStr Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
title_full_unstemmed Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
title_sort Computação evolucionária em identificação e controle de processos: fundamentos, análise e aplicações
dc.creator.none.fl_str_mv Coelho, Leandro dos Santos
Coelho, Antonio Augusto Rodrigues
author Coelho, Leandro dos Santos
author_facet Coelho, Leandro dos Santos
Coelho, Antonio Augusto Rodrigues
author_role author
author2 Coelho, Antonio Augusto Rodrigues
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Applications
genetic algorithms
evolution strategies
process identification
process control
practical application
topic Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Applications
genetic algorithms
evolution strategies
process identification
process control
practical application
dc.description.none.fl_txt_mv In this paper several evolutionary computation paradigms in process identification and control are utilized. The following methodologies are addressed: i) genetic algorithms (with floating point representation), ii) hybrid algorithms composed by genetic algorithms with simulated annealing, and iii) evolution strategies (without and with self-adaptation mechanisms). Experiments in identification were conducted in mono-tank level and temperature processes. Experimental tests in control are conducted in order to find the design parameter of the PID control when controlling a non-linear level process, composed of coupled twin-tanks, which are submitted to reference change and load disturbance, and steering a trailer truck while backing up to a loading dock.
Eje: Workshop sobre Aspectos Teoricos de la Inteligencia Artificial
Red de Universidades con Carreras en Informática (RedUNCI)
description In this paper several evolutionary computation paradigms in process identification and control are utilized. The following methodologies are addressed: i) genetic algorithms (with floating point representation), ii) hybrid algorithms composed by genetic algorithms with simulated annealing, and iii) evolution strategies (without and with self-adaptation mechanisms). Experiments in identification were conducted in mono-tank level and temperature processes. Experimental tests in control are conducted in order to find the design parameter of the PID control when controlling a non-linear level process, composed of coupled twin-tanks, which are submitted to reference change and load disturbance, and steering a trailer truck while backing up to a loading dock.
publishDate 1997
dc.date.none.fl_str_mv 1997
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/24061
url http://sedici.unlp.edu.ar/handle/10915/24061
dc.language.none.fl_str_mv por
language por
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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