永磁同步电机转子位置及速度提取灰色预测法  

Extraction of rotor position and speed for PMSM using grey system prediction

作　　者：祝晓辉[1,2] 李颖晖[1] 陈玉峰 

机构地区：[1]空军工程大学工程学院,陕西西安710038 [2]空军93163部队,黑龙江哈尔滨150001

出　　处：《电机与控制学报》2009年第2期184-189,共6页Electric Machines and Control

基　　金：陕西省自然科学基金(2006E132)

摘　　要：针对永磁同步电机的调速及伺服运行状态具有较强周期性与规律性的特点,提出了基于灰色系统预测理论的电机转子位置和速度自检测方法。通过相关因子序列的灰色关联度分析,确定了转子位置及速度的有效预测因子:即磁链—电流—转子位置角关系曲线及反电势—电压有效值—转子速度关系曲线,转子位置的预测采用等间隔的5条关系曲线,建立了等间隔GM(1,1)预测模型,而转子速度的预测根据低速及中高速范围确定为非等间距的8条关系曲线,建立了非等间隔GM(1,1)预测模型。将此预测方法用于永磁同步电机的矢量控制当中,仿真及实验表明状态估计准确、参数变化鲁棒性强,控制系统具有优良的静态和动态性能。For the fact that the running of permanent magnet synchronous motor （PMSM） has a strong characteristic of periodicity and orderliness, the new rotor position and speed self-sensing technique is proposed using grey system prediction theory. The valid predictors which are the curves of magnetic fluxstator current-rotor position and the curves of electromotive force-virtual value of voltage-rotor speed are chosen by grey correlation analysis. Then the rotor position was predicted by the five curves using equal interval GM （ 1,1 ） prediction model and the rotor speed was predicted using non-equal interval GM （ 1,1 ） prediction model according to the different speed range. Sensorless vector control was investigated using the proposed method. Simulation and experimental results reveal the effectiveness of state estimation and robustness for parameter variations, the control system has a good static and dynamic performance.

关 键 词：永磁同步电机 转子位置自检测 灰色系统预测理论 无传感器控制 

分 类 号：TM301.2[电气工程—电机] TP271.4[自动化与计算机技术—检测技术与自动化装置]