A Robust Dual-Vector Model Predictive Current Control for PMSM Drives

Abstract:
Given the high dependence of traditional model predictive current control (MPCC) methods on the accuracy of motor parameters, this paper proposes a robust dual-vector MPCC (DV-MPCC) method. In this control strategy, separate value functions are designed for the d-axis and q-axis based on sampled information. Subsequently, through the computation of these value functions and rolling optimization, the actual parameters of the motor are estimated. Simultaneously, this estimation information is used to dynamically adjust the predictive model in realtime, thereby achieving strong parameter robustness in control performance. Finally, simulation experiments are conducted to validate the effectiveness of the proposed method in reducing sensitivity to DV-MPCC parameters.