Artificial Neural Network Based Controller for Speed Control of An Induction Motor (IM) using Indirect Vector Control Method

摘要

In this paper, an implementation of intelligent controller for speed control of an induction motor (IM) using indirect vector control method has been developed and analyzed in detail. The project is complete mathematical model of field orientation control (FOC) induction motor is described and simulated in MATLAB for studies a 50 HP(37KW), cage type induction motor has been considered .The comparative performance of PI, Fuzzy and Neural network control techniques have been presented and analyzed in this work. The present approach avoids the use of flux and speed sensor which increase the installation cost and mechanical robustness .The neural network based controller is found to be a very useful technique to obtain a high performance speed control. The scheme consist of neural network controller, reference modal, an algorithm for changing the neural network weight in order that speed of the derive can track performance speed. The indirect vector controlled induction motor drive involve decoupling of the stator current in to torque and flux producing components.