Low Complexity Finite Control Set Model Predictive Control for Neutral-Point Clamped Converters with Switching Constraints

In this paper, a fast Finite Control Set Model Predictive Control algorithm is proposed for a three-phase gridtied Neutral-Point Clamped converter. The system model is represented in the converter line-to-line voltages, where the voltage vectors assume only integer entries. First, the unconstrained voltage vector is obtained to minimize the current tracking error. Then, ellipse constraints are considered in the resulting Space-Vector diagram to limit the converter transitions between only adjacent levels in the phase voltages, aiming to ensure safe commutations of the power converter semiconductor devices. As a result, the constrained voltage vector can be rounded to the nearest converter vector, which should be implemented in the next sampling period. In addition, from the redundancies of the selected vector, a cost function is evaluated to ensure the neutral point current control, aiming to balance the dc-link capacitor voltages. As both control objectives are treated in a cascaded sequence, the proposed algorithm avoids the design of weighting factors and has the advantages of low computation burden, fast transient response, and good steady-state performance. Real-time Hardware-in-the-Loop results show the good performance of the proposed algorithm compared to other techniques with reduced computational burden.