Efficient model-free predictive power control for active front-end modular multilevel converter

Abstract

In this paper, we propose a simple and efficient model-free predictive power control for active front-end modular multilevel converter. The main contribution of the proposed solution relies on the fact that no online optimization and weighting factors as well as parameters information in whole control process are required, while guaranteeing adaptability to different conditions. To be specific, it is realized by cascading an efficient model-free predictive power control based on extended state observer and a Kalman filter-based submodule voltage estimation technique, which is responsible for enhancing the robustness and reliability of the control system in the presence of parametric uncertainties. As such, unlike the conventional scheme that needs to evaluate the cost function, the philosophy behind the proposed methodology is to reduce the control complexity by eliminating the online optimization and weighting factors, which leads to a significant reduction in the calculation effort without sacrificing the performance. Alternatively, the stability of the closed-loop system is analyzed. Finally, the proposed methodology is experimentally assessed for active front-end modular multilevel converter, where steady-state and transient-state performance tests confirm the interest of the proposal.