Speed estimation for sensorless technology using recurrent neural networks and single current sensor

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorIEEE-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorGoedtel, A.-
Autor(es): dc.creatorDa Silva, I. N.-
Autor(es): dc.creatorSerni, P. J.A.-
Data de aceite: dc.date.accessioned2025-08-21T18:18:52Z-
Data de disponibilização: dc.date.available2025-08-21T18:18:52Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2006-12-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PEDES.2006.344293-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/224948-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/224948-
Descrição: dc.descriptionThe use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables involved in this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of artificial neural networks to estimate one of the most important variables in the induction motor control schemes: the speed. Simulation results are presented to validate the proposed approach. ©2006 IEEE.-
Descrição: dc.descriptionIEEE-
Descrição: dc.descriptionElectrical Engineering Department (EESC) University of São Paulo (USP), Av. Trabalhador Sao-carlense, 400, CEP 13566-590, São Carlos, SP-
Descrição: dc.descriptionElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SP-
Descrição: dc.descriptionElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SP-
Idioma: dc.languageen-
Relação: dc.relation2006 International Conference on Power Electronics, Drives and Energy Systems, PEDES '06-
???dc.source???: dc.sourceScopus-
Título: dc.titleSpeed estimation for sensorless technology using recurrent neural networks and single current sensor-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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