基于滑模估计器和卡尔曼滤波的PMSM速度估计  

Speed Estimate of PMSM Using Sliding Mode Estimator and Extended Kalman Filter

作　　者：刘宇[1] 刘杰[1] 戴丽[1] 喻春明[1] 

机构地区：[1]东北大学机械工程与自动化学院,沈阳110004

出　　处：《系统仿真学报》2008年第1期162-164,190,共4页Journal of System Simulation

摘　　要：针对永磁同步电机(PMSM)无传感器的控制问题,提出了一种结合滑模估计器和扩展卡尔曼滤波(EKF)两种方法优点的混合估计器。混合估计器解决了滑模估计器对于反电动势具有较大"畸变"的电机速度估计效果差的缺点。混合估计器建立了一个3阶EKF滤波器,把反电动势高次谐波分量作为系统和测量噪声处理。降阶后的EKF参数调节变得比传统的EKF估计器相对容易很多,在反电动势有"畸变"单纯滑模估计器估计效果很差时,估计效果依然很好。对滑模估计器、传统EKF估计器和混合控制器三种估计效果做了比较,阐明了混合估计器的优缺点。A method integrating the advantages of sliding mode estimator and Extended Kalman Filter （EKF） for sensorless control of Permanent Magnet Synchronous Motor （PMSM） was proposed. The hybrid approach overcomes the shortcoming of sliding mode estimator that it is not suitable for PMSM with nonsinusoidal back EMF distributing. A 3-orde EKF estimator is established, considering the high-order harmonics components as system and measurement noise. It is easier to tune the parameter for the order lowered EKF estimator than traditional EKF estimator, and have a good performance for PMSM with nonsinusoidal back EMF distributing while Sliding mode estimator has a worse capability. A comparison was provided among sliding mode estimator, traditional EKF estimator, and hybrid estimator to support the advantage and disadvantage of the proposed method.

关 键 词：PMSM 无传感器控制 扩展卡尔曼滤波 滑模估计器 混合估计器 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]