State estimation of two-phase permanent magnet synchronous motor

Abstract EN

The goal of this paper is to estimate the states of two-phase permanent magnet synchronous motor (PMSM).

The system is highly nonlinear and one therefore cannot directly use any linear system 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.

Firstly, the error covariance matrices of measurement and process would be derived when the system inputs and outputs are subjected to uncertain variations.

Then, the corruptednoise nonlinear model of the system will be discretized and extended to be suitable for applying standard discrete Kalman filter (KF) for state estimation purpose.

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.