Force Ripple Suppression of Permanent Magnet Linear Synchronous Motor Based on Fuzzy Adaptive Kalman Filter
PMLSM、fuzzy、Kalman filter
Control methods for linear drives
Final Paper
Xiaowen Zhang / School of Electrical Engineering and Automation; Harbin Institute of Technology
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.
