Two-Phase Permanent Magnet Synchronous Motor State Estimation

Abstract

The goal of this paper is to estimate the states of two-phase permanent magnet (PM) synchronous motor. The system is highly nonlinear and one therefore cannot directly use any linear systems tools for estimation. However, if one can linearize the system around a nominal (possibly time-varying) operating point then linear system tools could be used for control and estimation. The standard discrete Kalman filter (KF) has been used for state estimation. As such, the nonlinear model has been discretized and extended to be suitably applied for such filter. The entire state estimated system has been modeled using MATLAB/SIMULINK blocks. The state estimation algorithm and the motor discretized model are coded inside special S-functions of m-file type. Also, the error covariance matrices of measurement and process will be developed from the system model.