Sensorless Control of Permanent Magnet Synchronous Motor Based on SH-SSTEKF

In order to improve the estimation accuracy and anti-interference performance of the sensorless control system of permanent magnet synchronous motor, this paper proposes a sensorless control method based on extended Kalman filter with adaptive symmetric strong tracking. This method introduces the fading factor into the covariance matrix of the predicted state, eliminates the asymmetric influence brought by it, tunes the gain matrix online, reduces the modeling error, enhances the adaptability of the system to the changes of the external environment, realizes the rapid tracking of the sudden change state, and has excellent anti-error ability; in addition, the adaptive algorithm can recursively estimate the system noise, dynamically update the error covariance matrix, and further improve the convergence and estimation accuracy of the algorithm. Simulation experiments have proved the effectiveness of this method.