New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks

Detalhes bibliográficos
Autor(a) principal: Bordon, Mario Eduardo [UNESP]
Data de Publicação: 1999
Outros Autores: da Silva, Ivan Nunes [UNESP], de Souza, Andre Nunes [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ACC.1999.786327
http://hdl.handle.net/11449/65949
Resumo: The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).
id UNSP_f415cee5bc8719dec449ff4ece51c218
oai_identifier_str oai:repositorio.unesp.br:11449/65949
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networksAdaptive control systemsAsynchronous machineryClosed loop control systemsDigital control systemsElectric drivesIntelligent controlNeural networksSpeed controlCerebellar model articulation controller (CMAC)Gain planningThree term control systemsThe present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).UNESP, Sao PauloUNESP, Sao PauloUniversidade Estadual Paulista (Unesp)Bordon, Mario Eduardo [UNESP]da Silva, Ivan Nunes [UNESP]de Souza, Andre Nunes [UNESP]2014-05-27T11:19:49Z2014-05-27T11:19:49Z1999-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2153-2157http://dx.doi.org/10.1109/ACC.1999.786327Proceedings of the American Control Conference, v. 3, p. 2153-2157.0743-1619http://hdl.handle.net/11449/6594910.1109/ACC.1999.7863272-s2.0-003328496355898388442982328212775960494686Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the American Control Conference0,500info:eu-repo/semantics/openAccess2024-06-28T13:34:35Zoai:repositorio.unesp.br:11449/65949Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:33:42.486387Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
title New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
spellingShingle New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
Bordon, Mario Eduardo [UNESP]
Adaptive control systems
Asynchronous machinery
Closed loop control systems
Digital control systems
Electric drives
Intelligent control
Neural networks
Speed control
Cerebellar model articulation controller (CMAC)
Gain planning
Three term control systems
title_short New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
title_full New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
title_fullStr New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
title_full_unstemmed New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
title_sort New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks
author Bordon, Mario Eduardo [UNESP]
author_facet Bordon, Mario Eduardo [UNESP]
da Silva, Ivan Nunes [UNESP]
de Souza, Andre Nunes [UNESP]
author_role author
author2 da Silva, Ivan Nunes [UNESP]
de Souza, Andre Nunes [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Bordon, Mario Eduardo [UNESP]
da Silva, Ivan Nunes [UNESP]
de Souza, Andre Nunes [UNESP]
dc.subject.por.fl_str_mv Adaptive control systems
Asynchronous machinery
Closed loop control systems
Digital control systems
Electric drives
Intelligent control
Neural networks
Speed control
Cerebellar model articulation controller (CMAC)
Gain planning
Three term control systems
topic Adaptive control systems
Asynchronous machinery
Closed loop control systems
Digital control systems
Electric drives
Intelligent control
Neural networks
Speed control
Cerebellar model articulation controller (CMAC)
Gain planning
Three term control systems
description The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).
publishDate 1999
dc.date.none.fl_str_mv 1999-12-01
2014-05-27T11:19:49Z
2014-05-27T11:19:49Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ACC.1999.786327
Proceedings of the American Control Conference, v. 3, p. 2153-2157.
0743-1619
http://hdl.handle.net/11449/65949
10.1109/ACC.1999.786327
2-s2.0-0033284963
5589838844298232
8212775960494686
url http://dx.doi.org/10.1109/ACC.1999.786327
http://hdl.handle.net/11449/65949
identifier_str_mv Proceedings of the American Control Conference, v. 3, p. 2153-2157.
0743-1619
10.1109/ACC.1999.786327
2-s2.0-0033284963
5589838844298232
8212775960494686
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the American Control Conference
0,500
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 2153-2157
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128532025442304

Registros relacionados