Research on model predictive current control of PMSM
based on sliding mode observer

TIAN Ya-nan, XIA Kun

              (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China)

Abstract: Aiming at the sensorless high dynamic performance control of permanent magnet synchronous motor (PMSM), the influence of current PI controller on the performance of traditional vector control system and the inaccuracy of the estimation of rotor position angle and rotor speed in the traditional sliding mode observer (SMO) were improved. A model predictive current control (MPCC) method for PMSM based on improved SMO was proposed in this paper. According to the mathematical model of PMSM in the synchronous rotating coordinate axis, the motor d, q current were selected as the state variables to deduce the prediction model of d, q current with forward Euler. By evaluating the cost function in real time, the voltage vector which has a perfect current tracking effect of the next moment was selected to acts on the inverter with its switching state. Moreover, the sliding mode observer model of surface mounted permanent magnet synchronous motor (SPMSM) was derived, and the rotor position angle and speed that observed by SMO were compensated in this paper, which would obtain the accurate estimation value. The proposed algorithm was tested in Matlab/Simulink. The results indicate that the proposed control method has nice dynamic performance and high steady-state accuracy.
Key words: permanent magnet synchronous motor (PMSM); model predictive current control (MPCC); sliding mode observer (SMO); sensorless control