【摘要】 为了提高永磁同步电机永磁磁链观测器的观测性能,提出了一种基于SSIUKF(超球体迭代无迹卡尔曼滤波)的永磁磁链辨识方法。在无迹卡尔曼滤波的观测更新阶段,用阻尼的高斯-牛顿算法对预测值进行迭代。在采样阶段采用超球体算法,有效减少改进后算法的计算量。仿真和实验结果表明,采用超球体迭代无迹卡尔曼滤波与无迹卡尔曼滤波相比,在保证观测实时性的同时,可以进一步提高永磁磁链辨识的准确性。更多还原

【Abstract】 In order to improve the observing performance of permanent magnet synchronous motor(PMSM) flux observer,a method of permanent magnet flux identification based on SSIUKF(hypersphere iterated unscented Kalman filter) is proposed. In the observation update phase of unscented Kalman filter,the damped Gauss-Newton algorithm is used to iterate the predicted values. In the sampling stage,the hypersphere algorithm is used to reduce the computational complexity of the improved algorithm. The simulation and experimental results show that compared with the unscented Kalman filter,the hypersphere iterated unscented Kalman filter can further improve the accuracy of permanent magnet flux identification while guaranteeing the real-time observation.更多还原