为了提高直接转矩控制（DTC）系统定子磁链估计精度，降低电流、电压测量的随机误差，提出了一种基于扩展卡尔曼滤波（EKF）实现异步电机转子位置和速度估计的方法。扩展卡尔曼滤波器是建立在基于旋转坐标系下由定子电流、电压、转子转速和其它电机参量所构成的电机模型上，将定子电流、定子磁链、转速和转子角位置作为状态变量，定子电压为输入变量，定子电流为输出变量，通过对磁链和转速的闭环控制提高定子磁链的估计精度，实现了异步电机的无速度传感器直接转矩控制策略，仿真结果验证了该方法的可行性,提高了直接转矩的控制性能。
Abstract:
In order to improve the Direct Torque Control（DTC） system of stator flux estimation accuracy and reduce the current， voltage measurement of random error， a novel method to estimate the speed and rotor position of asynchronous motor based on extended Kalman filter was introduced. EKF was based on d-p axis motor and other motor parameters （state vector: stator current， stator flux linkage， rotor angular speed and position； input: stator voltage； output: staror current). EKF was designed for stator flux and rotor speed estimation in close-loop control. It can improve the estimated accuracy of stator flux. It is possible to estimate the speed and rotor position and implement asynchronous motor drives without position and speed sensors. The simulation results show it is efficient and improves the control performance.
