永磁同步电机的改进扩展卡尔曼滤波测速算法

摘要

Aiming at the lagging and inaccuracy in the traditional velocity estimation method for permanent magnet synchronous motor (PMSM) with incremental encoder, an improved method based on extended Kalman filter (EKF) was proposed, an EKF observer was designed to obtain the estimated speed accurately without lagging, and the algorithm was simplified with matrix transformation and the overflow periodicity of accumulator in the fixed-point DSP. The experiment results show the relatively accurate velocity estimation without large lagging in the entire process of motor.%针对使用增量式编码器的永磁同步电机(PMSM)伺服系统中的传统测速算法(M算法结合低通滤波)存在的时延与不准确的问题,提出了一种改进的扩展卡尔曼滤波( EKF)测速算法.该方法在不修改原有电路的前提下,利用EKF算法抑制噪声且不产生时延的特点,针对性地设计了观测模型,并通过矩阵变换与利用定点数字信号处理器累加溢出的周期性,极大地简化了原有的EKF算法.实验结果证明:该算法能够在电机的整个运行过程中给出相对实时的、准确的速度估计值,在一定程度上改善了电机的调速性能,并且算法具有很强的实用性.