Recurrent neural network for induction motor speed estimation in industry applications


Autoria(s): Goedtel, Alessandro; Da Silva, Ivan Nunes; Serni, Paulo José Amaral
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