基于UKF算法的无刷直流电机转子位置和速度的估计

针对无刷直流电机（BLDCM）非线性严重而导致控制困难的问题，利用无轨迹卡尔曼滤波（UKF）算法设计了观测器，以估计无刷直流电机的转子位置和角速度，分析了在BLDCM系统负载变化、负载扰动、参数变化以及低转速情况下的估计结果，同时讨论了噪声统计参数的变化对估计效果的影响由此可知，良好的估计效果与UKF算法中各个参数的设置有重要的关系．仿真和实验结果表明，该转子位置观测方法可以比较正确地给出电机换相信号，实现电机的无位置传感器控制．

Estimates of Rotor Position and Velocity of Brushless DC Motor with UKF Algorithm

In view of control difficulty caused by severe nonlinear performance of brushless DC motor （BLDCM）, an observer was designed for estimating the rotor position and velocity of BLDCM by using unscented Kalman filter （UKF） algorithm. The estimated results under certain circumstances such as load variation, load disturbance, parameter variation and low speed rotation were analyzed. And effects of the variation of noise statistic parameters on estimated results were discussed, which proved that good estimated results were strongly related to the UKF parameters. Simulation and experiment results showed that the method mentioned in this paper can provide the exact commutation signals, and realize the BLDCM control without any position sensor.