A reset particle swarm optimization PID control of permanent magnet BLDC motor for airscrew load

When permanent magnet brushless DC motor (PMBLDCM) drive high altitude airscrew load, due to the change in atmospheric density with altitude and the frequent fluctuations of airscrew load torque, the traditional given-parameter PID control meets difficulty in the real-time adjustment of the PID parameters of electric power drive systems (EPDS) with environmental change; so the dynamic characteristics and robustness of system is poor. To solve the problem, a novel PID control method based on the BFGS-RPSO algorithm is proposed. The method uses of flexible global and fast local search optimization of BFGS-RPSO algorithm to online optimize the PID parameters of PMBLDCM control system and improve the dynamic characteristics and robustness of electric drive systems with airscrew load. Matlab simulation and experimental results show that the rise time of speed is shorter and the overshoot of speed and torque is less during starting the motor. Besides, the torque ripple is smaller in load fluctuation. The dynamic characteristics and robustness of BFGS-RPSO PID parameter control are better than those of traditional PID control. The method is feasible for the EPDS of PMBLDCM with propeller load.