基于鲁棒UKF 的永磁同步电机转子速度估计

吉林大学学报(信息科学版) ›› 2015, Vol. 33 ›› Issue (2): 137-143.

基于鲁棒UKF 的永磁同步电机转子速度估计

沈绍博¹, 祖晖², 李涛^1,2, 费树岷³

1. 南京航空航天大学自动化学院, 南京 210016; 2. 张家港智能电力研究院智电柔性输配电技术研究所,江苏张家港 215600; 3. 东南大学自动化学院, 南京 210096

收稿日期:2014-11-10 出版日期:2015-03-24 发布日期:2015-05-29
作者简介:沈绍博(1993—), 男, 安徽宿州人, 南京航空航天大学硕士研究生, 主要从事风力发电技术、鲁棒控制研究, (Tel)86-18205099953(E-mail)shenshaobo@126. com; 李涛(1979—), 男, 安徽淮南人, 南京航空航天大学副教授, 博士, 硕士生导师, 主要从事网络控制系统、复杂网络系统研究, (Tel)86-13851475878(E-mail)autolitao@ nuaa. edu. cn。
基金资助:
国家自然科学基金资助项目(61473079; 61374116); 江苏省自然科学基金资助项目(BK201212211)

Estimation of Speed for Sensorless DD-PMSG Based on Robust UKF Method

SHEN Shaobo¹, ZU Hui², LI Tao ^1,2, FEI Shumin³

1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Zhangjiagang Research Institute of Smart Grid for Electricity Transmission and Distribution Technology, Zhangjiagang 215600, China;3. School of Automation, Southeast University, Nanjing 210096, China

Received:2014-11-10 Online:2015-03-24 Published:2015-05-29

摘要/Abstract

摘要：

针对无位置传感器直驱永磁同步电机系统(DD-PMSG: Direct-Driven Permanent Magnetic Synchronous Generator), 无迹Kalman 滤波(UKF: Unscented Kalman Filtering)方法鲁棒性不高的问题, 提出了基于一种新的鲁棒UKF 的转子速度估计方法。该方法将DD-PMSG 模型转化为由发电机机电状态与定子参数组成的增广方程形式。运用鲁棒UKF 算法, 可同时辨识发电机的机电状态和定子不确定参数动态, 使估计发电机参数不确定的鲁棒性得以改善。仿真结果表明, 与传统UKF 方法相比, 该方法对存在不确定性及非高斯噪声的系统模型具有较强的鲁棒性。

关键词: 直驱永磁同步电机, 无位置传感器控制, 转速估计, 鲁棒无迹卡尔曼滤波

Abstract:

To solve the weak robustness of UKF(Unscented Kalman Filtering) of the DD-PMSG(Direct-Driven Permanent Synchronous Magnetic Generator) without position sensor, a rotor speed estimation method based on RUKF(Robust Unscented Kalman Filtering) algorithm is proposed. The DD-PMSG model is transformed into the augmented equations with electromechanical state and stator parameters. By applying the RUKF to the augmented model, the PMSG states will be estimated, and the uncertain parameters dynamic, in which the latter participates in the iterative process of state estimation and improves the robustness of state estimation against parameter uncertainties. The stronger robustness can be shown by comparing with the UKF method in simulation results.

Key words: permanent magnetic synchronous generator(PMSG), sensorless control, speed estimation, robustunscented Kalman filtering(RUKF)

中图分类号:

TM351

沈绍博, 祖晖, 李涛, 费树岷. 基于鲁棒UKF 的永磁同步电机转子速度估计[J]. 吉林大学学报(信息科学版), 2015, 33(2): 137-143.

SHEN Shaobo, ZU Hui, LI Tao, FEI Shumin. Estimation of Speed for Sensorless DD-PMSG Based on Robust UKF Method[J]. Journal of Jilin University(Information Science Ed, 2015, 33(2): 137-143.