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

dc.contributor.authorGoedtel, A.
dc.contributor.authorDa Silva, I. N.
dc.contributor.authorSerni, P. J.A. [UNESP]
dc.contributor.institutionIEEE
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-28T20:18:49Z
dc.date.available2022-04-28T20:18:49Z
dc.date.issued2006-12-01
dc.description.abstractThe 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.en
dc.description.affiliationIEEE
dc.description.affiliationElectrical Engineering Department (EESC) University of São Paulo (USP), Av. Trabalhador Sao-carlense, 400, CEP 13566-590, São Carlos, SP
dc.description.affiliationElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SP
dc.description.affiliationUnespElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SP
dc.identifierhttp://dx.doi.org/10.1109/PEDES.2006.344293
dc.identifier.citation2006 International Conference on Power Electronics, Drives and Energy Systems, PEDES '06.
dc.identifier.doi10.1109/PEDES.2006.344293
dc.identifier.scopus2-s2.0-34547596849
dc.identifier.urihttp://hdl.handle.net/11449/224948
dc.language.isoeng
dc.relation.ispartof2006 International Conference on Power Electronics, Drives and Energy Systems, PEDES '06
dc.sourceScopus
dc.titleSpeed estimation for sensorless technology using recurrent neural networks and single current sensoren
dc.typeTrabalho apresentado em evento
dspace.entity.typePublication
unesp.departmentEngenharia Elétrica - FEBpt

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