Model Predictive Control of Three-Level ANPC Converter Based on Voltage Vector Tracking

When the classical finite control set model predictive control (FCS-MPC) is applied to three-level active neutral-point-clamped (dxe) converters, it suffers from issues such as variable switching frequency, heavy computational burden due to exhaustive traversal of the control set, and complex weighting factor tuning. To address these challenges, this paper proposes a model predictive control algorithm based on voltage vector tracking (VVT-MPC). The algorithm first calculates the reference voltage vector at the current sampling instant using the measured current and predicted reference current values. Subsequently, based on the sector where the reference voltage vector resides, appropriate voltage vectors are selected and synthesized to track the reference voltage vector accurately. Furthermore, redundant positive and negative small vector pairs are utilized to achieve capacitor voltage balance control, thereby entirely eliminating the need for weighting factors. Finally, dynamic and steady-state simulations validate the effectiveness of the proposed algorithm, while comparative simulation results demonstrate its superior performance.