基于PSO和滑模观测器的永磁同步电机预测控制

Predictive Control of Permanent Mangnet Synchronous Motor Based on PSO and Sliding Mode Observer

针对传统永磁同步电机(PMSM)无差拍电流预测控制中参数失配会导致电流误差甚至系统失稳的问题,提出了一种基于粒子群算法(PSO)和滑模观测器的预测控制。基于无差拍电流预测控制算法,建立了电流预测控制系统,并分析了电阻、电感和转子磁链参数对dq轴电流误差的影响。通过建立滑模观测器,利用观测到的系统扰动对参考电压进行补偿,提高了系统抗参数扰动的能力。针对观测器参数难以整定问题,提出基于PSO优化观测器参数的方法。最后通过仿真验证了所提方法的可行性。

Aiming at the problem of current error and even system instability caused by parameter mismatch in the deadbeat current predictive control of traditional permanent magnet synchronous motor(PMSM),a predictive control based on particle swarm optimization(PSO)and sliding mode observer was proposed.Based on the deadbeat current predictive control algorithm,a current predictive control system was built to analyze the influence of resistance,inductance and rotor flux parameters on the error of dq-axes currents.A sliding mode observer was established,and the reference voltage was compensated by the system disturbance obtained from the observation,which can improve the anti-parameter disturbance ability.A method of optimizing observer parameters based on PSO was proposed to deal with the problem of difficult tuning of observer parameters.The simulation analysis verified the feasibility of the proposed method.