A Model Predictive Control Strategy for Three-level NPC Rectifier-Inverter Drive System Without Weighting Factor

Aiming at the high performance and high efficiency control of the three-level neutral point clamped (NPC) rectifier-inverter drive system of induction motor, this paper builds a prediction and loss model of the three-level rectifier-inverter system, constructs a cost function including the midpoint voltage balance and loss optimization, and proposes a sequential parallel model predictive control. By classifying the multiple objectives in the cost function into two sequence optimization sets, the strategy divides the multiple control objectives into primary and secondary control objectives for sequence optimization. Adaptive parallel optimization is used to select the optimal switching state in each sequence, which avoids the design of weighting factors and ensures the synchronous optimization of targets in the same sequence. Simulation and experimental results show that the proposed method has good control performance and parameter robustness, and can effectively control the midpoint voltage fluctuation and reduce the system loss.