A Deadbeat Model Predictive Current Control Algorithm for Modular Multilevel Converters with Enhanced Steady-State Performance

Abstract

Model predictive control (MPC) algorithms are popularly studied for modular multilevel converters (MMCs) because of the multi-objective regulation capability and fast dynamic response. However, they have some inherent drawbacks, for example, calculation complexity, non-fixed switching frequency, complex weighting factor determination as well as weak steady state performance. This article proposes a deadbeat model predictive control algorithm for MMCs. The proposed algorithm can accurately track the reference of output ac and circulating currents in one control period, therefore can provide a fast-dynamic performance. In addition, switching state and cost function calculation and weighting factor determination are removed. Hence, its calculation burden is very low, and not related to the submodules (SMs) number. Since a modulator is adopted, a fixed switching frequency and thus a good steady-state performance are achieved. The impacts of circuit parameter mismatches as well as SM capacitor voltage ripples on the control algorithm are analyzed. Improvement measures are proposed to enhance the steady-state performance and system stability. The effectiveness of the proposed control algorithm is verified by experiments.