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Application of fuzzy neural network in the speed control system of induction motor

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2 Author(s)
Li Yi ; Ind. Eng. Training Centre, Shanghai Univ. of Eng. Sci., Shanghai, China ; Pu Yonghong

A novel sensorless adaptive fuzzy neural network (FNN) speed controller for induction motor derives is proposed in this paper. An artificial neural network (ANN) is applied to estimate the motor speed and thus provide a sensorless speed estimator system. The performance of the proposed adaptive FNN 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 FNN 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.

Published in:

Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on  (Volume:3 )

Date of Conference:

10-12 June 2011