Model Predictive Control of Modular Multilevel Converters Using Quadratic Programming

The finite control set-model predictive control (FCS-MPC) has been adopted as an excellent choice for the applications of multilevel converters during the last two decades for its salient performance. However, in the case of modular multilevel converters (MMCs), a high amount of calculation is always involved in the implementation, making the FCS-MPC less suitable especially for an MMC with a high number of submodules. To cope with the issue, this article proposes an MPC technique for the MMC with a very low calculation cost. In each sampling period, the arm voltage references of each phase are determined analytically by solving a constrained quadratic programming problem formulated from the cost function. Both a rigorous and simplified procedure is provided to solve the optimization problem. Then, the four nearest candidates around the arm voltage references are evaluated, leading to a proper selection of arm voltage levels. Several experimental tests on an MMC prototype are carried out to validate the effectiveness of the proposed method. Results show that compared with the conventional FCS-MPC method which evaluates all voltage-level combinations, the proposed scheme presents an apparent advantage in terms of calculation cost while achieving similar performance.