Sensorless speed control of induction motor derives using a robust and adaptive neuro-fuzzy based intelligent controller

In this paper a novel sensorless adaptive neurofuzzy speed controller for induction motor derives is formulated. An artificial neural network (ANN) is adopted to estimate the motor speed and thus provide a sensorless speed estimator system. The performance of the proposed adaptive neurofuzzy speed controller is evaluated for a wide range of operating conditions for induction motor. These include startup, step changes in reference speed, unknown load torque and parameters variations. Obtained results show that the proposed ANN provides a very satisfactory speed estimation under the above mentioned operation conditions and also the sensorless adaptive neurofuzzy speed controller can achieve very robust and satisfactory performance and could be used to get the desired performance levels. The response time is also very fast despite the fact that the control strategy is based on bounded rationality.