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Application of Reduced-Order Extended Kalman Filter in Permanent Magnet Synchronous Motor Sensorless Regulating System

机译:降阶扩展卡尔曼滤波器在永磁同步电动机无传感器调节系统中的应用

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Aim at the existing problems of the Extended Kalman Filter (EKF) in speed sensorless control system of permanent magnet synchronous motor (PMSM), such as too much computation, complex structure and high cost. A kind of Reduced-order Extended Kalman Filter (Reduced-order EKF) in speed sensorless control system of PMSM is proposed in this paper. By estimating the counter electromotive force according to the stator current observed as state variables, the reduced-order and the decoupling of the system equation is realized. On this condition, the motor speed is estimated by using the Reduced-order EKF. Compared with the traditional method of EKF, the system order is reduced, the process of iteration of speed estimation is greatly simplified and it is easy to realization of the digitalization system by using this method. The simulation results have shown that this system has fast reacting speed, good dynamic performance, adjust parameters easily, and beneficial to realize digital system.
机译:针对永磁同步电动机(PMSM)无速度传感器控制系统中扩展卡尔曼滤波器(EKF)存在的问题,如计算量大,结构复杂,成本高等。提出了一种PMSM无速度传感器控制系统中的降阶扩展卡尔曼滤波器。通过根据作为状态变量的定子电流估计反电动势,可以实现系统方程的降阶和解耦。在这种情况下,可通过使用降阶EKF来估算电动机速度。与传统的EKF方法相比,减少了系统阶数,大大简化了速度估计的迭代过程,并且使用该方法易于实现数字化系统。仿真结果表明,该系统反应速度快,动态性能好,参数调整容易,有利于数字系统的实现。

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