Recurrent neural network for induction motor speed estimation in industry applications

dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:22:03Z
dc.date.available2014-05-27T11:22:03Z
dc.date.created2014-05-27T11:22:03Z
dc.date.issued2006-12-01
dc.identifierProceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1134-1137.
dc.identifierhttp://hdl.handle.net/11449/69248
dc.identifier10.1109/MELCON.2006.1653300
dc.identifier2-s2.0-34047160114
dc.identifier4831789901823849
dc.identifier0000-0002-9984-9949
dc.description.abstractMany electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work Is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach. © 2006 IEEE.
dc.languageeng
dc.relationProceedings of the Mediterranean Electrotechnical Conference - MELECON
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectComputer simulation
dc.subjectElectric drives
dc.subjectFeedback control
dc.subjectIndustrial applications
dc.subjectRecurrent neural networks
dc.subjectSpeed control
dc.subjectInduction motor feedback
dc.subjectRMS voltage
dc.subjectSensorless technologies
dc.subjectInduction motors
dc.titleRecurrent neural network for induction motor speed estimation in industry applications
dc.typeActas de congresos


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