Recurrent neural network for induction motor speed estimation in industry applications
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
---|---|
Data(s) |
27/05/2014
27/05/2014
01/12/2006
|
Resumo |
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. |
Formato |
1134-1137 |
Identificador |
http://dx.doi.org/10.1109/MELCON.2006.1653300 Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1134-1137. http://hdl.handle.net/11449/69248 10.1109/MELCON.2006.1653300 2-s2.0-34047160114 |
Idioma(s) |
eng |
Relação |
Proceedings of the Mediterranean Electrotechnical Conference - MELECON |
Direitos |
closedAccess |
Palavras-Chave | #Computer simulation #Electric drives #Feedback control #Industrial applications #Recurrent neural networks #Speed control #Induction motor feedback #RMS voltage #Sensorless technologies #Induction motors |
Tipo |
info:eu-repo/semantics/conferencePaper |