Low-Complexity Dual-Vector Model Predictive Control for Single-Phase Nine-Level ANPC-Based Converter

This article proposes a dual-vector finite-control-set model predictive control (FCS-MPC) with reduced complexity for a novel nine-level active neutral point clamped (ANPC) converter. This topology considerably reduces the used number of power switches compared to other topologies. Only nine power switches and two flying capacitors (FCs) are used to generate nine voltage levels. The proposed MPC scheme notably reduces the computational burden by directly locating the best two vectors without the need for multiple evaluations of the cost function as in the conventional method. Using one weighting factor in the cost function, three objectives are considered, namely, current tracking, FCs voltage control, and dc-link stabilization, reducing the heavy effort of coordinating weighting factors. Mathematical analyzes were carried out to determine the optimal duration of the selected voltage vectors. While the sequence of the two voltage vectors is identified based on the total harmonic distortion (THD) definition to minimize its value. Compared with standard FCS-MPC, lower steady-state errors, lower THDs, better harmonic distribution, and shorter execution times are achieved. The proposed MPC method is validated and compared with other prior-art control methods through experimental implementation.