中文摘要：

Unscented卡尔曼滤波器（UKF）在许多非线性估计问题中是一种估计性能优于扩展卡尔曼滤波器（EKF）的非线性滤波方法。然而在永磁直线同步电动机无位置传感器控制中，UKF是否能提高永磁直线电动机位置与速度的估计性能却尚未见研究。针对永磁直线同步电动机进给系统的特点，建立用于位置与速度估计器的永磁直线同步电动机进给系统模型，提出永磁直线同步电动机无位置传感器控制系统。通过仿真和试验对UKF的估计性能进行评估，并与EKF进行了比较。仿真及试验结果表明，UKF在估计性能与EKF相当，然而UKF的计算量却比EKF大，使得在高速永磁直线同步电动机无位置传感器控制这一特定问题上，EKF比UKF更有效。

英文摘要：

For a variety of nonlinear estimation problems, the unscented Kalman filter （UKF） is a superior alternative to the extended Kalman filter （EKF）. The effectiveness of UKF for position sensorless control of permanent magnet linear synchronous motor （PMLSM） is investigated. At first, the PMLSM model used in the estimation algorithm is established, then, the position sensorless PMLSM drive system based on UKF is presented. Via simulations and experiments, the effectiveness of UKF for position sensorless control of PMLSM is verified. And, a comparison of estimation performance of UKF and EKF for estimating position and speed is carried out. The simulation and experiment results indicate that UKF performs equivalently with EKF, but the computational time of UKF is more than that of EKF. For estimating position and speed of PMLSM, the EKF is a better choice than UKF .