The Extended kalman filter (EKF) has been found wide application in the sensorless control of induction motor (IM) because of its good steady and dynamic behaviour,disturbance resistance, and fast convergence. This paper presents a novel speed sensor

针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended K

The paper deals with the application of the Extended Kalman Filter and the Extended Luenberger Observer algorithms for the stator and rotor fault detection of the induction motor fed by PWM inverter. The induction motor conditions are analyzed usin