Fast FCS-MPC for neutral-point clamped converters with switching constraints

Abstract

Model Predictive Control algorithms have been recently developed for controlling grid-tied converters. However, the inclusion of the converter switching constraints in the optimization problem and the high computational burden are some of the main challenges of these algorithms. In this way, this paper proposes a Fast Finite Control Set Model Predictive Control algorithm with a low computational burden for a three-phase Neutral Point Clamped inverter considering its switching constraints. Initially, the vector with the unconstrained solution in the line-to-line voltage coordinates is obtained to minimize the current tracking error. Then, it is limited to ellipses as an intermediate step to ensure that the selected voltage vector is feasible and to restrict the switching transitions. The constrained vector is rounded to the nearest inverter line-to-line voltage vector to be implemented in the next sampling period. The NPC redundant phase-voltage vectors are generated online to avoid the potentially destructive switching transitions. The neutral point is balanced by minimizing a cost function, considering the obtained redundant phase voltage vectors, and is evaluated at most twice in each sampling period. As both control objectives are treated in a cascaded sequence, the proposed Fast FCS-MPC avoids the design of weighting factors and has the advantages of low computational burden, fast transient response, and good steady-state performance. Finally, Hardware-in-the-Loop results are presented to compare the proposed Fast FCS-MPC to other strategies presented in the literature, and the effectiveness of the proposed algorithm is also demonstrated by means of an experimental prototype.