Simplified Model Predictive Current Control for Single-Phase Multilevel Inverter

In this paper, an efficient finite control set model predictive control (FCS-MPC) for single-phase multilevel inverter (MLI) is proposed. The MLI topology under control reduces the number of the required semiconductor switches and produces more number of levels compared to traditional and recent topologies of MLIs. This topology has 49 different switching states, which means 49 predictions of the future current and 49 calculations of the cost function are required for each evaluation of the conventional FCS-MPC. Accordingly, the computational load is heavy. Thus, this paper presents a simplified FCS-MPC to reduce the calculation burden by computing the reference voltage and dividing the switching states of the MLI into two sets. Based on the reference voltage, one set is identified to determine the optimum voltage level. The proposed method does not require current predictions. Moreover, the number of cost function evaluations for each iteration is halved. As a result, the execution time is significantly reduced compared to that of the conventional FCS-MPC. The trade-off between the average switching frequency and the tracking performance is also investigated for the proposed scheme and compared to the conventional FCS-MPC. The effectiveness of the proposed solution in transient and steady state is verified by the simulation results.