Speed Control of PMSM Using Modified Particle Swarm Optimization Technique Based on Inertia Weight Updating Mechanism

In this paper, the modified Particle Swarm Optimization (PSO) algorithm is implemented to tune the gain parameters of the PI speed controller of the PMSM drive system. The PSO is one of the artificial intelligence techniques which is modified with the inertia weight updating mechanism to prevent premature convergence and balance the exploration and exploitation of the particles. The field-oriented vector control PMSM drive is developed in MATLAB/Simulink to examine three different conditions such as start-up, speed command change, and sudden load torque imposition. The different parameters are then examined such as speed overshoot, settling time, peak time, rise time and speed ripple and the results are compared with conventional PSO-tuned PI controllers for the same motor. From the results, it is proved that the modified PSO-PI controller gives better performance compared to the conventional PSO-PI speed controller.