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Adaptive Model Predictive Current Control for PMLSM Drive System
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DOI：10.1109/TIE.2022.3179550.png)
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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.
Keyword:
Discrete-time sliding mode disturbance observer (DSMDO)
model predictive control (MPC)
surface-mounted permanent magnet linear synchronous motor (SPMLSM)
期刊
IF:
7.2
论文数:
1.8W
被引数:
9.8W
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