Research about the Sensorless Vector Control of Permanent Magnet Synchronous Motor Based on Two-stage Filter Sliding Mode Observer

Abstract

In order to overcome the disadvantages of installing mechanical sensors and the problems of chattering and low observation accuracy in traditional sliding mode observer sensorless control, a two-stage filter Sliding Mode Observer (SMO) is proposed in this paper. By collecting the current and voltage of the Permanent Magnet Synchronous Motor (PMSM), the SMO algorithm is realized by using the state equation of the motor in the synchronous stationary coordinate system; the position of the rotor is estimated by the arc tangent function, the observation accuracy of the rotor position is improved by increasing phase compensation; the variable cut-off frequency filter is introduced to make the Low Pass Filter (LPF) cut-off frequency can be self-adjusted with the change of rotational speed, which improves the estimation accuracy of rotor position at different rotational speeds. Kalman filter is introduced to form a two-stage filter with variable cut-off frequency LPF, which greatly weakens the chattering of the motor and reduces the observation error. Finally, the simulation is carried out under MATLAB/Simulink. The simulation results show that the PMSM vector control system with two-stage filter sliding mode observer has high estimation accuracy, good dynamic and steady-state performance, strong anti-jamming ability and robustness.