Modulated Model Predictive Control for Four-Leg Inverters With Online Duty Ratio Optimization

Abstract

Conventional finite control set (FCS) predictive load-voltage control for four-leg inverters features simplification in digital implementation compared to its complex counterpart, three-dimensional space vector modulation. However, the FCS approach is typically characterized by a variable switching frequency, low steady-state performance, and a higher average switching frequency in the neutral leg than the other three legs. To overcome these shortcomings, an online duty-cycle-optimization based model predictive control technique is proposed in this article. The performance of the inverter is evaluated experimentally in terms of load voltage tracking in different operating conditions such as nonlinear loads and balanced/unbalanced references. The proposed technique fulfills the requirement of a high-performance converter, constant switching frequency, and enhanced load voltage tracking at a lower sampling rate and, thus, solves the drawbacks of the conventional FCS model predictive control for a four-leg inverter. Furthermore, the proposed approach can facilitate the overmodulation operation, which is desirable for this type of power converters under nonlinear and unbalanced loading conditions.