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Design of Kalman Filter for induction motor drive

机译:感应电动机驱动用卡尔曼滤波器的设计

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This paper compares the standard and extended versions of kalman filter for rotor flux estimation in a voltage source inverter fed vector controlled induction motor drive. The design method for the both versions of kalman filter is presented and shown. Only simulation results are presented in this paper. Methodologyto create KF, EKF for online identification ofinduction motor parameters are also described in details. The Extended Kalman Filter can be used for combined state and parameter estimation by treating selected parameters as extra states and forming an augmented state vector. Depending on whether the original state space model is linear or not, the augmented model is nonlinear in multiplication of states. A fifth order augmented state space model is developed when the EKF is applied to the simultaneous estimation of states of stator and rotor d-q current and rotor d-q fluxes. Important conclusions,togetherwith recommendations for observer selection.
机译:本文比较了卡尔曼滤波器的标准版和扩展版,用于在电压源逆变器馈电矢量控制感应电动机驱动器中估算转子磁通。介绍并显示了两种版本的卡尔曼滤波器的设计方法。本文仅介绍了仿真结果。还详细介绍了用于在线识别感应电动机参数的创建KF,EKF的方法。通过将所选参数视为额外状态并形成增强状态向量,扩展卡尔曼滤波器可用于组合状态和参数估计。根据原始状态空间模型是否是线性的,扩充模型在状态相乘中是非线性的。当将EKF用于同时估计定子和转子d-q电流和转子d-q磁通的状态时,便建立了五阶增强状态空间模型。重要结论,以及有关观察者选择的建议。

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