A neural-network-base adaptive estimator for speed-sensorless control of induction motor

This paper presents an adaptive estimator for speed-sensorless field-oriented control of induction motor. By measuring the phase voltages and currents induction motor (IM) drive, a neural network based rotor flux components and speed estimation method for IM is described. The proposed estimator includes two recurrent neural networks (RNN), one is used to estimate rotor flux and speed, the other is used to estimate stator current. Using an improved recursive prediction error algorithm, online adaptive estimation is realized. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness algorithm.