Abstract
This paper presents speed sensorless direct torque control (DTC) of induction motor using Artificial intelligence (AI). The artificial neural network (ANN) MRAS-based speed estimation is used. The error between the reference model and the neural network based adaptive model is used to adjust the weights by on-line Back propagation (BP) training algorithm. The speed loop regulation is carried out by a fuzzy controller giving exceeding performance in comparison with a classic PI regulator. The performance of fuzzy speed controller and speed estimator are investigated with the help of Matlab/Simulink®. The estimated speed accuracy was achieved with high performance of the speed controller. The estimated speed error is less than 1% both in transient and steady-state operation. The fuzzy controller is robust to load torque perturbations and speed reference changes.
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