Optimal FCS-MPC Algorithm for Neutral-Point Clamped Converters with Switching Constraints

This paper proposes an optimal Finite Control Set Model Predictive Control for a three-phase Neutral Point Clamped inverter, considering its switching constraints. Initially, an optimization problem is solved to obtain the inverter line-to-line voltage vector that minimizes the current tracking error. Here, the constraints of the optimization problem are the lines that delimitate a convex hull around the last implemented vector, where the candidate vector presents at least one switching state which satisfies the switching constraint of the NPC inverter. The NPC’s redundant phase-voltage vectors are generated according to the switching constraint to avoid the potentially destructive switching transitions, and a cost function is then evaluated to balance the DC bus neutral point voltage, as the second control stage. As a result, the proposed Optimal FCS-MPC avoids the design of weighting factors and has the advantages of optimal performance, fast transient response, and superior steady-state performance, compared to similar algorithms. Finally, simulation results are presented to compare the proposed Optimal FCS-MPC algorithm with other FCS-MPC strategies presented in the literature, and the effectiveness of the proposed algorithm is demonstrated.