改进UKF算法在PMLSM无位置传感控制中的应用

针对永磁直线同步电机(PMLSM)的无位置传感控制,提出了一种基于改进无迹卡尔曼滤波(UKF)算法的永磁直线同步电机的动子速度和位置估计方法,对永磁直线同步电机的动子速度和位置进行估计.相比于传统的UKF算法,改进UKF算法在采样点的获取上进行了改进,在采样点的获取上运用了球形采样策略,而非传统的平方根对称采样策略,极大减少了采样点的数量,减少了状态估计过程中算法的计算量,在估计性能相当的情况下,改进的球形采样策略UKF算法较传统的平方根对称采样UKF算法在永磁同步直线电机无位置传感实时控制系统中有明显优势,取得良好的控制效果.

Application of modified UKF algorithm in PMLSM sensorless control

In view of sensorless control of permanent magnetic linear synchronous motor(PMLSM),put forward a speed and position estimation method based on modified unscented Kalman filtering (UKF) to estimate moving speed and position.Compared to conventional UKF algorithm,the modified UKF algorithm improves at obtaining of sampling point.It uses spherical sampling strategy for obtaining sample points,rather than traditional square root symmetric sampling strategy.It greatly reduces number of sampling points,and reduce calculation of state estimation process.When the estimation properties are equivalent,the modified spherical sampling strategy UKF algorithm is better than the traditional square root symmetric sampling UKF algorithm in permanent magnet linear synchronous motor sensorless real-time control system has obvious advantages and obtain good control effect.