Online particle swarm optimization for sensorless IPMSM drives considering parameter variation

In this paper, a novel online particle swarm optimization method is proposed to design speed and current controllers of sensorless vector controlled interior permanent magnet synchronous motor drives. The sliding mode observer is used for joint stator flux and rotor speed estimation. The stator resistance variation is compensated with a speed correction term which is derived from the estimation error of d-axis current. The speed and current controller gains are optimized with particle swarm optimization online, and the fitness function is changed according to the system dynamic and steady states. The proposed optimization algorithm is compared with conventional PI controller design method in the condition of step speed change and load disturbance. The offline and real-time simulation results are shown to confirm the effectiveness of the proposed method, with which the sensorless IPMSM drive exhibits better robustness and dynamic characteristics compared with the conventional PI controller design method.