Identification of IM resistance using artificial neural network in low speed region

Soenmez M., Yakut M.

3rd Intelligent Sensors, Sensor Networks and Information Processing Conference, Adelaide, Australia, 3 - 06 December 2007, pp.437-439 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/issnip.2007.4496883
  • City: Adelaide
  • Country: Australia
  • Page Numbers: pp.437-439


This paper presents a new method of estimation for the stator and rotor resistances of the induction motor for speed sensorless motor control drives, using artificial neural networks. The error between the motor quantity based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the stator resistance estimation. For the rotor resistance estimation, the error between the measured stator current and the estimated stator resistance using neural network is back propagated to adjust the weights of the neural network. The rotor speed is extracted from the induction motor state equations. The performance of the stator and rotor resistance estimators are investigated with the help of measured the stator voltage and current. Both resistances are estimated experimentally, using the proposed neural network in an induction motor drive.