A new algorithm for flux and speed estimation in induction machine

Yang Wenqiang, Jia Zhengchun, Xu Qiang
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引用次数: 9

Abstract

A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm.
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感应电机磁链和转速估计的新算法
针对无速度传感器矢量控制中感应电机转子磁链分量和转速的估计问题,提出了一种新的降阶扩展卡尔曼滤波器。该方法选取两个转子磁链分量作为状态变量,将转子转速作为估计参数作为增广状态变量。降阶算法降低了计算复杂度,使所提出的估计器能够实时实现。仿真结果表明该算法具有较高的估计精度,验证了该算法的有效性。
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