H.A.F. Mohamed and S. Yaacob (Malaysia)
Artificial Neural Networks, System Identification, Induction Motors Control, Electric Drives
This paper carries out the identification of a squirrel-cage induction motor using the artificial neural network and precisely the Back Propagation Algorithm. The same algorithm is then used to design a direct inverse neural network based control scheme to control the speed of the motor. The performance of the designed controller is tested in real time. To performance of the system is also checked out under load conditions by applying a load torque to the shaft of the motor. The results show that the controller could compensate for this kind of disturbances. The system is also tested for the tracking property using different types of reference signals.
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