Recurrent Neural Network for Induction Motor Speed Estimation in Industry Applications

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.