中文摘要：

针对普通UKF在永磁同步电动机速度估计中存在对模型不确定性的鲁棒性差、对突变状态的跟踪能力低和收敛速度慢等问题,结合强跟踪滤波器对UKF滤波进行改进,引入时变渐消因子在线自适应调整增益矩阵和状态预测误差协方差矩阵,实现残差序列正交或近似正交,强迫UKF滤波保持对实际状态的快速跟踪。将该算法在永磁同步电动机无速度传感器矢量控制系统中进行仿真研究。试验结果与统计分析表明,相对与普通UKF,基于改进UKF滤波的永磁同步电动机转子速度及角度估计更准确,误差更小,跟踪速度更快,鲁棒性更好。

英文摘要：

Concerning on the problem of permanent magnet synchronous motor （PMSM） state estimation based on ordinary UKF, such as bad robustness of model uncertainty,lower tracking ability to abrupt state and slow convergence etc, the speed-sensorless control system of PMSM based on improved UKF was proposed. The time-varying fading factor was introduced to adaptive adjust gain matrices and the state forecast covariance matrices, in order to realize the residuals orthogonality or approximately orthogonality and force the UKF to track the real state rapidly. The sensorless vector control system of PMSM was set up based on this estimation approach. The results of simulation prove that, contrast to ordinary UKF, the proposed method is capable of precisely estimating the rotor speed and space position, and high robustness is achieved in this control system.