Speed Control of Motor Based on Improved Glowworm Swarm Optimization

To better regulate the speed of brushless DC motors, an improved algorithm based on original Glowworm Swarm Optimization is proposed. The proposed solves problems poor robustness, slow convergence, and low accuracy exhibited by traditional PID controllers. When selecting glowworm neighborhood set, optimization scheme growth competition behavior weeds applied to a single prevent falling into local optimal solution. After glowworm’s position updated, league selection operator introduced search for global Combining ability invasive weed with enhances robustness also accelerates convergence algorithm. mathematical model motor established, parameters are tuned optimized using algorithm, adjusted. In Simulink environment, double closed-loop control was established simulate motor, this simulation compared control. results show that has good steady-state response