基于双无迹卡尔曼滤波算法的永磁同步电机转子磁链辨识

转子磁链的准确辨识是实现永磁同步电机(Permanent Magnet Synchronous Motor, PMSM)转子磁场监控，确保其驱动系统可靠运行并实现高性能控制的有效方法。为解决测量噪声、电机参数变化及辨识模型欠秩对转子磁链辨识精度影响的问题，提出了基于双无迹卡尔曼滤波（UKF）算法的PMSM转子磁链辨识方法，可在确保满秩辨识的前提下，减小测量噪声与电机参数变化对转子磁链辨识精度的影响，实现PMSM转子磁链的准确辨识，并在参数敏感性分析的基础上，降低了算法计算量，合理兼顾了辨识精度与辨识速度。对所提方法进行了仿真研究和实验验证，研究结果证实了所提方法的有效性。

The Identification for Rotor Flux Linkage of PMSM Base on Dual UKF Algorithm

Accurate identification of rotor flux linkage is an effective method to monitor the rotor magnetic field of permanent magnet synchronous motor(PMSM) , guarantee the reliable operation and high performance control of PMSM drive system. For solving the problem of negative impacts on identification precise of rotor flux linkage produced by measurement noise, parameters variation of PMSM and deficient rank of identification model, the identification method for rotor flux linkage of PMSM based on dual unscented kalman filter is proposed, in consequence, the negative impacts on identification precise of rotor flux linkage induced by measurement noise and parameters variation of PMSM is reduced on the premise of ensuring full rank identification, the accurate identification of rotor flux linkage is achieved, the algorithm computation is also reduced based on parameters sensitivity analysis, and the reasonable balance of identification accuracy and identification speed is achieved. The simulation research and experimental validation of the proposed method is implemented, and the research results verified the effectiveness of the proposed method.