Bisection Algorithm based Indirect Finite Control Set Model Predictive Control for Modular Multilevel Converters

In this work, an idea based on the bisection algorithm is used to reduce the computational burden of indirect finite control set model predictive control (FCS-MPC) for modular multilevel converters (MMCs). The proposed method greatly reduces the search space for reaching the optimal insertion index (number of submodules to be inserted). Therefore, the strategy proposed offers similar steady-state and dynamic performance compared to full indirect FCS-MPC at a much lower computational burden. A new cost function is also proposed for indirect FCS-MPC which eliminates the need for an outer loop or additional control of differential current to regulate the summation voltages in each arm. The results of the proposed strategy are validated through simulations in MATLAB/Simulink.