Soft Computing Using GWO (Grey Wolf Optimization) for the Performance Improvement of High Speed Brushless DC Motor

Abstract

This papers aims at the design of Buck-Boost converter fed BLDC (Brushless DC) motor drive. Many industrial applications brushless DC motor (BLDC) is widely used because of their high torque, high efficiency and low volume. Brushless DC motor performances are compared for different control strategies in this paper. The main core of this work compare the performance of the conventional PI controller, FUZZY logic controller, hybrid (PI+FUZZY) and Grey wolf optimization (GWO) algorithm. Compared to the conventional techniques GWO has the ability to satisfied control characteristics and it is easy for computing. For comparison, across the supply mains Total, Crest Factor (CF), Harmonic Distortion (THD) and Power Factor (PF), the controller performances are maximum peak overshoot (M p ), settling time (T s ), rise time (T r ) and steady state error (Ess) and motor parameters are speed and torque are to be analyzed simultaneously. The modeling, control and simulation of the BLDC motor have been done using the software packages MATLAB/SIMULINK result verifies that the GWO gives the better control performance than the conventional controllers.