dc.contributorUniversity of Technology - Paraná (UTFPR-CP)
dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:23:43Z
dc.date.available2014-05-27T11:23:43Z
dc.date.created2014-05-27T11:23:43Z
dc.date.issued2008-12-01
dc.identifier2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA.
dc.identifierhttp://hdl.handle.net/11449/70676
dc.identifier10.1109/TDC-LA.2008.4641832
dc.identifier2-s2.0-67650475717
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 related to 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 a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.
dc.languageeng
dc.relation2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectInduction motors
dc.subjectNeural networks
dc.subjectSystem identification
dc.subjectCurrent sensors
dc.subjectElectrical machine
dc.subjectMechanical parameters
dc.subjectRecurrent artificial neural networks
dc.subjectSensorless
dc.subjectSensorless control scheme
dc.subjectIdentification (control systems)
dc.subjectMotors
dc.subjectRecurrent neural networks
dc.subjectSensor networks
dc.titleEstimation of electrical machine speed using sensorless technology and neural networks
dc.typeActas de congresos


Este ítem pertenece a la siguiente institución