An Advanced Control Strategy Applying Reduced Order Extended Kalman Filter Algorithm for Permanent Magnet Synchronous Motor

In control system of permanent magnet synchronous motor, the estimation of rotor position is an essential issue. The classical Kalman filter algorithm has been previously proposed to estimate rotor position, but it is commonly subject to parameter nonlinear characteristics. This paper presents an advanced control method based on Reduced Order Extended Kalman Filter (ROEKF) to deal with control issue of PMSM in low-speed region. The EKF is able to address the nonlinear characteristic of permanent magnet synchronous motor, where the reduced-order matrix can reduce computational burdens. Then, simulation verification is performed in MATLAB/Simulink and PSIM. In addition, experiments are performed to validate the proposed control method in a three-phase inverter-fed drive system using gallium nitride (GaN) power device. The simulation and experimental results show that the proposed control algorithm can quickly and accurately track the rotor position of PMSM.