Computationally Efficient Modulated Model Predictive Control for a Four Leg Inverter Feeding Unbalanced Loads

Recently, MPC has achieved much recognition among the power electronic investigators because of its characteristics like constraint handling, intuitiveness, superior dynamic performance, and robustness. However, the conventional MPC operates at a changeable switching frequency which leads to an increased steady state ripple and difficulties in the filter design. To counter these, modulated MPC has been proposed in the literature by applying multiple vectors in a sampling period. The existing modulated MPC for four leg inverter requires a huge number of computations. So, this paper proposes a computationally efficient modulated model predictive control (MPC) for four leg inverters using a tetrahedron identification method based on the sensed three phase currents. The overall computational savings are ≈ 48% without effecting the steady state and dynamic performance of the load currents. To validate the proposed MPC, simulation results are presented.