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Force Ripple Suppression of Permanent Magnet Linear Synchronous Motor Based on Fuzzy Adaptive Kalman Filter

机译:基于模糊自适应卡尔曼滤波器的永磁线性同步电动机力纹波抑制

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Aiming at the problem that the noise covariance matrix is difficult to get when using the Kalman filter to observe the force, a force ripple suppression strategy of permanent magnet linear synchronous motor based on fuzzy adaptive Kalman filter is proposed. According to the fuzzy control theory, this method takes the error of the q-axis current and rate of the error as fuzzy controller inputs, and takes the parameter in the covariance matrix of the measurement noise as fuzzy controller output, which reduces the burden of parameter tuning and improve disturbance rejection performance. The experimental results show that compared with the Kalman filter with fixed parameters, the method proposed in this paper has better dynamic performance.
机译:旨在解决噪声协方差矩阵难以使用卡尔曼滤波器观察力时难以获得的问题,提出了基于模糊自适应卡尔曼滤波器的永磁线性同步电动机的力纹波抑制策略。 根据模糊控制理论,该方法将Q轴电流的误差和误差速率作为模糊控制器输入,并将测量噪声的协方差矩阵中的参数作为模糊控制器输出,这减少了负担 参数调谐和提高干扰抑制性能。 实验结果表明,与具有固定参数的卡尔曼滤波器相比,本文提出的方法具有更好的动态性能。

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