Optimal FOC-PID Parameters of BLDC Motor System Control Using Parallel PM-PSO Optimization Technique

Abstract

This paper proposes a parallelization method for meta-heuristic particle swarm optimization algorithm to obtain a convincingly fast execution and stable global solution result. Applied the proposed method, the searching region is efficiently separated into sub-regions which are simultaneously searched using optimization algorithm. The structure of meta-heuristic algorithm is rebuilt as to execute in parallel multi-population mode. The closed loop system of brushless DC electric motor position control is used to verify the proposed method. The simulation and experiment results show that the proposed parallel multi-population technique obtains a competitive performance compared to the standard ones in both of precision and stability criteria. Especially, meta-heuristic algorithms running in parallel multi-population mode execute quite faster than standard ones. In particular, it shows an efficient improvement of the proposed method applied to identify of nonlinear Benchmark tests and to optimize proportional integral derivative parameters for field-oriented control scheme of the brushless DC electric motor system.

Keywords

• Particle swarm optimization (PSO)
• Parallel PSO technique
• Parallel multi-population technique
• Brushless DC electric motor
• BLDC motor system
• Field-oriented control (FOC-PID)