An Analysis on Speed Control of Three-Phase Asynchronous Motor using Fuzzy Logic Controller

Abstract

Every manufacturing Industry which drives heavy load requires the help of a three-phase induction motor to run its mechanical load. The reason behind its popularity is its low manufacturing cost, less maintenance, and simple working principle. Induction motors also widely find prime application in many commercial, residential, and agricultural centers. Initially in all-purpose having constant load uses IM and varying load is done using DC motor due to its smooth speed control characteristics. But in the past couple of decades, many scalar and vector control strategies have been developed for Induction Motor drives thus replacing DC drives completely. In almost all industries a varying mechanical load is needed to be fulfilled with varying torque produced by Induction Motor speed control.
Hence it is expected from induction motor drives to have high-grade efficient performance. From efficient performance, smooth speed control of the motor is expected which will eventually lead to the conservation of energy.
This work is mainly focused on utilizing the power of the artificial neural network in speed control of 3 ϕ IM. A comparison of a result obtained through this method is done with the conventional technique to prove the superiority of artificial intelligence in solving this problem. The designing of an induction motor drive based on ANN is consisting of two parts, one is an identifier based on ANN which has the purpose of estimating required motor speed and the other is a controller based on ANN which has the purpose of forming an appropriate signal for the motor speed controlling. For both such purposes, usually, the back propagation neural network training approach is very effective due to its exceptional quality to drive meaning out of non-linear distributed data. The proposed work is done using MATLAB/Simulink software.