Torque and speed estimator for induction motor using parallel neural networks and sensorless technology

Detalhes bibliográficos
Autor(a) principal: Suetake, M.
Data de Publicação: 2009
Outros Autores: Goedtel, A., Silva, I. N. da, Serni, P. J. A. [UNESP], Nascimento, C. F. do, Silva, S. A. O. da
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/IECON.2009.5414705
http://hdl.handle.net/11449/244033
Resumo: Many electronic drivers for induction motor control are based on sensorless technologies. The proposal of this work is to present an efficient torque and speed estimator for induction motor steady state operations by using artificial neural networks. The proposed method is based on off-line training which considers different types of loads and a wide range of supply voltage. The inputs of the network are the induction motor RMS voltage and current. Besides, the estimation processing effort is reduced to a simple matrix solving after the neural network is trained. Simulation and experimental results are also presented to validate the proposed approach. ©2009 IEEE.
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spelling Torque and speed estimator for induction motor using parallel neural networks and sensorless technologyMany electronic drivers for induction motor control are based on sensorless technologies. The proposal of this work is to present an efficient torque and speed estimator for induction motor steady state operations by using artificial neural networks. The proposed method is based on off-line training which considers different types of loads and a wide range of supply voltage. The inputs of the network are the induction motor RMS voltage and current. Besides, the estimation processing effort is reduced to a simple matrix solving after the neural network is trained. Simulation and experimental results are also presented to validate the proposed approach. ©2009 IEEE.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Federal Technological University of Paraná Department of Electrical Engineering, Cornélio Procópio-PRUniversity of São Paulo Department of Electrical Engineering, São Carlos-SPState University of São Paulo Department of Electrical Engineering, Bauru-SPFederal University of ABC Engineering Center, Santo André-SPState Univ Sao Paulo, Dept Elect Engn, Bauru, SP, BrazilFAPESP: 03/11353-0FAPESP: 06/56093-3FAPESP: 2008/00004-8CNPq: 142128/2005-8CNPq: 474290/2008-5IeeeUniversidade de São Paulo (USP)Federal Technological University of ParanáUniversidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Suetake, M.Goedtel, A.Silva, I. N. daSerni, P. J. A. [UNESP]Nascimento, C. F. doSilva, S. A. O. da2022-04-29T08:44:16Z2020-12-10T18:30:55Z2022-04-29T08:44:16Z2020-12-10T18:30:55Z2009-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1362-1367http://dx.doi.org/10.1109/IECON.2009.5414705IECON Proceedings (Industrial Electronics Conference), p. 1362-1367.1553-572Xhttp://hdl.handle.net/11449/24403310.1109/IECON.2009.5414705WOS:0002807620002132-s2.0-77951517840ScopusWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIECON Proceedings (Industrial Electronics Conference)Iecon: 2009 35th Annual Conference Of Ieee Industrial Electronics, Vols 1-6info:eu-repo/semantics/openAccess2024-06-28T13:34:36Zoai:repositorio.unesp.br:11449/244033Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:29:02.355887Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
title Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
spellingShingle Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
Suetake, M.
title_short Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
title_full Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
title_fullStr Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
title_full_unstemmed Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
title_sort Torque and speed estimator for induction motor using parallel neural networks and sensorless technology
author Suetake, M.
author_facet Suetake, M.
Goedtel, A.
Silva, I. N. da
Serni, P. J. A. [UNESP]
Nascimento, C. F. do
Silva, S. A. O. da
author_role author
author2 Goedtel, A.
Silva, I. N. da
Serni, P. J. A. [UNESP]
Nascimento, C. F. do
Silva, S. A. O. da
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Federal Technological University of Paraná
Universidade Estadual Paulista (Unesp)
Universidade Federal do ABC (UFABC)
dc.contributor.author.fl_str_mv Suetake, M.
Goedtel, A.
Silva, I. N. da
Serni, P. J. A. [UNESP]
Nascimento, C. F. do
Silva, S. A. O. da
description Many electronic drivers for induction motor control are based on sensorless technologies. The proposal of this work is to present an efficient torque and speed estimator for induction motor steady state operations by using artificial neural networks. The proposed method is based on off-line training which considers different types of loads and a wide range of supply voltage. The inputs of the network are the induction motor RMS voltage and current. Besides, the estimation processing effort is reduced to a simple matrix solving after the neural network is trained. Simulation and experimental results are also presented to validate the proposed approach. ©2009 IEEE.
publishDate 2009
dc.date.none.fl_str_mv 2009-01-01
2020-12-10T18:30:55Z
2020-12-10T18:30:55Z
2022-04-29T08:44:16Z
2022-04-29T08:44:16Z
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/IECON.2009.5414705
IECON Proceedings (Industrial Electronics Conference), p. 1362-1367.
1553-572X
http://hdl.handle.net/11449/244033
10.1109/IECON.2009.5414705
WOS:000280762000213
2-s2.0-77951517840
url http://dx.doi.org/10.1109/IECON.2009.5414705
http://hdl.handle.net/11449/244033
identifier_str_mv IECON Proceedings (Industrial Electronics Conference), p. 1362-1367.
1553-572X
10.1109/IECON.2009.5414705
WOS:000280762000213
2-s2.0-77951517840
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IECON Proceedings (Industrial Electronics Conference)
Iecon: 2009 35th Annual Conference Of Ieee Industrial Electronics, Vols 1-6
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1362-1367
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Scopus
Web of Science
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
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