抽象的

Particle Swarm Optimization Based Direct Torque Control of Brushless DC Motor

Dr.T.Vamsee Kiran, A.Siva Nagaraju

This paper deals with the direct torque control (DTC) of BLDC motor drives by using particle swarm optimization technique. BLDC motors have wide variety of advantages like higher speed ranges, higher efficiency, and better speed versus torque characteristics. Direct torque control (DTC) is one of the efficient methods used in variable frequency drives to control the BLDC motor. DTC offers many advantages like fast torque response, no need of coordinate transformation and less dependence on the rotor parameters. In DTC, the estimated flux magnitude and torque are compared with their reference values. The reference torque is generated from the output of the speed regulator (PI controller).Tuning PI parameters (Kp, Ki) are essential to DTC system to improve the performance of the system at low speeds. In conventional PI controller, the performance of the motor may cause unexpected torque disturbances. Particle swarm optimization (PSO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion.The simulation results of BLDC drive employing conventional PI and PSO based PI controllers is compared and evaluatedunder various load disturbances in the MATLAB/simulink environment.