Artificial Neural Network based Sensorless Vector Control of Induction Motor Drive

Abstract

Controlled induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. For these speed sensorless AC drive system, it is key to realize speed estimation accurately. This paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab. Simulation result shows a good performance of speed estimator. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to resistances of stator variations.