氢气泵自适应无迹卡尔曼滤波无传感器控制  

Sensorless Control of Hydrogen Pump Using Adaptive Unscented Kalman Filter

作　　者：Sheianov Aleksandr 康尔良[1] Sheianov Aleksandr;KANG Er-liang(School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China)

机构地区：[1]哈尔滨理工大学电气与电子工程学院,哈尔滨150080

出　　处：《哈尔滨理工大学学报》2020年第3期25-32,共8页Journal of Harbin University of Science and Technology

基　　金：黑龙江省科技攻关资助项目(GC04A517)。

摘　　要：提出了一种氢气泵用PMSM转子位置新型非线性估算方法。卡尔曼滤波常用于在非线性系统,在计算量相同的情况下,无迹卡尔曼滤波器(UKF)较扩展卡尔曼滤波器(EKF)的计算结果更为准确,因为应用较多。在燃料电池系统中,氢气泵用PMSM的负载常发生持续变化或突变;由于UKF采用固定过程噪声协方差(Q矩阵),无法响应负载变换造成的过程噪声变化,传统卡尔曼滤波器的性能可能下降。提出了一种自适应UKF方法,通过计算UKF的自适应增益,以补偿实际残差协方差与滤波器导出值之间的不匹配,从而在负载变换的情况下,保证了转子位置估算的精度。最后,搭建氢气泵用PMSM控制系统,并进行了自适应UKF转子位置估算。实验结果验证了该算法的可行性和有效性。This paper demonstrates a special and new type of non-linear observer for a permanent magnet synchronous motor used in hydrogen pump applications.For nonlinear systems,the unscented Kalman filter(UKF)is a very popular approach for the controller design.Some researches have shown that the UKF is usually more accurate than the extended Kalman filter(EKF)whereas the computation burden is the same in both cases.However,the performance of traditional Kalman filter may degrade when process noise and load are constantly changing or a sudden disturbance occurs due to the fixed process noise covariance(Q matrix)in the filter,which is the case in fuel cell systems where a hydrogen pump is used.An adaptive gain is calculated to compensate for the mismatch between the actual residual covariance and the deduced value from the filter,ensuring that the sequence of residual is uncorrelated.Also,the derivation of the proposed adaptive UKF is explained in details.Finally,experimental tests under sensorless position control for hydrogen pump are carried out with the proposed method,in which the feasibility and effectiveness of the algorithm is shown.

关 键 词：无传感器控制 自适应卡尔曼滤波 氢气泵 

分 类 号：TM351[电气工程—电机]