基于EKF的PMSM滑模控制策略研究

Research on PMSM Sliding Mode Control Strategy Based on EKF

为了优化表贴式三相永磁同步电机(PMSM)的无传感器矢量控制性能,设计卡尔曼滤波器(EKF)实现电机转速与位置的在线估计。针对基于传统PI控制器的PMSM矢量控制抖振问题,在电流环设计基于Super-twisting算法的滑模控制器,并给出了收敛和稳定的必要条件。仿真结果表明,基于EKF算法的观测器能够准确地观测转速和位置,与PI控制器相比,Super-twisting滑模控制器缩短了响应时间,在一定程度上降低了抖振,增强了系统鲁棒性,提高了系统动态性能和抗扰动性。

In order to optimize the sensorless vector control performance of the surface mount three-phase permanent magnet synchronous motor(PMSM),a Kalman filter(EKF)was designed to estimate the speed and position of the motor online.Aiming at the chattering problem of PMSM vector control based on traditional PI controller,a sliding mode controller of super-twisting algorithm is designed in the current loop,and the necessary conditions of convergence and stability are given.The simulation results show that the observer based on the EKF algorithm can accurately observe the rotation speed and position.Compared with the PI controller,the Super-Twisting sliding mode controller can shorten the response time,reduce chattering to some extent,and enhance the system robustness.The dynamic performance and anti-disturbance of the system are improved.