Speed control of brushless DC motor using intelligent controllers

The brushless dc motors are widely used in the servo motor application because of their different advantages over conventional DC motors. However high performance motor drives require fast and accurate speed response of the system, quick recovery of speed from any disturbance and sensitivity to motor parameter variation. To operate the motor with proper reference speed different controllers are widely used in industrial application. In this present work, genetic algorithm based PID controller is used to tune the PID controller parameters for speed control of BLDC motor. Ziegler-Nicholas tuning formula is used for tuning and gain predication of GA-PI and GA-PID controller. Genetic algorithm is a robust optimization technique based on natural selection. The basic goal of GA to optimize the fitness function. In the present work we use integral square error (ISE) based fitness function to optimize the gain co-efficient of PID controller by considering the different parameters such as rise time settling time and overshoot of the response. Simulation results obtained from different conventional controllers as well fuzzy-PID controller are compared with the GA-PI and GA-PID controllers.