在永磁同步电机矢量控制设计中，针对传统方式的利用机械传感器检测转子位置和转速等输出反馈信号难以检测的问题，提出基于无传感器技术的卡尔曼滤波技术。在永磁同步电机控制系统中利用该技术可以在线估算永磁同步电机转子的位置和转速等反馈信号。本文详细阐述了扩展卡尔曼算法（Extended Kalman Filter，EKF）的计算过程并指出其缺点，针对以上缺点引入无迹卡尔曼滤波算法，同时指出无迹卡尔曼（Unsecented Kalman Filter，UKF）技术算法的优点及应用。针对目前少有人研究基于UKF无传感器永磁同步矢量控制技术，提出该方案研究的前景和可行性。%In the design of the permanent magnet synchronous motor vector control, there is a problem of feedback signal which is difficult to detect, and this signal is from the rotor position and speed which is detected by the use of the mechanical sensors in the traditional methods. This paper puts forward Kalman filtering technique based on no sensor technology. In the permanent magnet synchronous motor vector control system, it can estimate rotor position and speed and other feedback signals online by use of this technique. This paper describes calculation process of the extended Kalman algorithm (Extended Kalman Filter, EKF) and points out its shortcomings, and introduces unscented Kalman filter algorithm aiming at the above disadvantages, while this paper points out the advantages and applications of the unscented Kalman (Unsecented Kalman Filter, UKF) algorithm technology. Aiming at the situation that few people has researched on permanent magnet synchronous vector control technology based on UKF sensorless, this paper presents the prospects and feasibility of the program of study.
展开▼
