Model Predictive Control of Cascaded H-Bridge Inverters based on a Fast-Optimization Algorithm

In this work, a Finite Control Set Model Predictive Control (FCS-MPC) strategy for Cascaded H-bridge (CHB) inverters is proposed. The key novelty of our proposal comes from the way the cost function is designed. Generally, in standard FCS-MPC formulations for power converters, the cost function only considers the current tracking error. In this proposal, the proposed cost function also takes into account the control input tracking error. This allows one to obtain a reduced common-mode voltage during the steady-state while achieving a fast dynamic response during transients, similarly to the one provided by standard FCS-MPC. To account for calculation time, a fast-optimization algorithm based on sphere decoding is also considered. To verify the performance of the proposed predictive strategy, simulation results for a three phase five-level CHB inverter governed by the proposed FCS-MPC are presented.