Research on Sensorless Control of Built-in Permanent Magnet Synchronous Motor Based on Extended Kalman Filter Algorithm

Abstract

The permanent magnet synchronous motor (PMSM) is a system of complex interior structure coupling and nonlinear, variable parameters. In order to track and observe the position and speed of PMSM in real time, the extended Kalman filter (EKF) algorithm is used in this paper to track the speed and position of the built-in PMSM. The influence of the Q and R covariance matrix on the observation effect is studied by using the control variable method of trial and error. The reliability of the EKF on the observation function of velocity position is verified by MATLAB simulation.