PERFORMANCE ENHANCEMENT OF DIRECT TORQUE CONTROLLED BRUSHLESS DC MOTOR USING SOFT COMPUTING METHODS

Abstract

The BLDC motor speed control is creating more importance in industry as it is used in many applications now-a-days. In order to get the accurate and reliable control action Direct Torque Control method is used and PI controller is used to generate the reference signal. The conventional methods of tuning the parameters Kp and Ki is based on trial and error which consumes more time. Hence, in this paper intelligent technique such as Fuzzy logic, Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are proposed to tune the parameters of PI control algorithm. The transient performance and efficiency of the BLDC motor is analyzed to determine the stable and efficient operation. CSA tuned PI control algorithm yielded better performance compared to PI, Fuzzy and PSO tuned PI control algorithms.