Speed Sensorless Control with Neuron MRAS Estimator of an Induction Machine

Abstract

In the high speed range, vector control of rotor flux orientation of an induction machine implements good performance. However, the performance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MRAS) for speed estimation are used to improve the performance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved performance in low speed range.