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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/69248
Title: 
Recurrent neural network for induction motor speed estimation in industry applications
Author(s): 
Institution: 
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
Abstract: 
Many 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.
Issue Date: 
1-Dec-2006
Citation: 
Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1134-1137.
Time Duration: 
1134-1137
Keywords: 
  • Computer simulation
  • Electric drives
  • Feedback control
  • Industrial applications
  • Recurrent neural networks
  • Speed control
  • Induction motor feedback
  • RMS voltage
  • Sensorless technologies
  • Induction motors
Source: 
http://dx.doi.org/10.1109/MELCON.2006.1653300
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/69248
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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