Adaptive Model Predictive Current Control for PMLSM Drive System

This article proposes an adaptive model predictive current control (AM-MPCC) for surface-mounted permanent magnet linear synchronous motor systems to simultaneously enhance the robustness against permanent magnet flux, inductance, and resistance mismatches. First, the conventional continuous control set model predictive control is analyzed, illustrating that parameter variations will inevitably deteriorate the current regulation performance. Then, an adaptive predictive model, which involves a disturbance term and an optimized current change rate coefficient, is proposed. The optimal coefficient is estimated using a steady-state incremental model and the steepest descent method at each control period. A discrete-time sliding mode disturbance observer is devised based on the adaptive model with updated coefficients to achieve the disturbance term. Finally, an exponential reaching law-based-reference trajectory is defined for the cost function of AM-MPCC to adjust the current approach trajectory. Experimental results verify the excellent robustness performances of the proposed method.

Automated summary

This article proposes an adaptive model predictive current control (AM-MPCC) method for enhancing the robustness of surface-mounted permanent magnet linear synchronous motor systems. An adaptive predictive model is introduced, along with a disturbance term and an optimized current change rate coefficient. A discrete-time sliding mode disturbance observer is devised to achieve the disturbance term. Experimental results confirm the excellent robustness performances of the proposed method.