The regulation of output voltage in power converters often demands nonlinear control techniques; however, their implementation is challenging when deployed on low-cost hardware with limited computational resources. To address this difficulty, the modeling via the sector nonlinearity technique is adopted to represent the converter dynamics as a convex combination of linear vertex models. Building on this representation, this article proposes a vertex-based convex PI controller that significantly reduces the required online computations compared to conventional convex controllers relying on full-state feedback. In the proposed scheme, the inductor current is used solely to evaluate the weighting functions, avoiding the need to compute control gains associated with this state. The effectiveness of the method is demonstrated through offline simulations and validated using hardware-in-the-loop experiments.

This paper presents a Finite Control Set-Model Predictive Control (FCS-MPC) strategy for a modified single-phase 17-level Double Flying-Capacitor Multilevel (DFCM) converter. The proposed approach integrates current regulation, capacitor voltage balancing, switching frequency reduction, delay compensation, and FPGA-based real-time implementation within a unified predictive control framework. A multi-objective cost function exploits the converter’s redundant switching states to achieve accurate control while reducing computational burden. Additionally, the converter topology provides voltage-boosting capability without requiring an additional DC-DC stage. The proposed controller was validated through offline and Hardware-in-the-Loop (HIL) simulations. Simulation results demonstrate robust operation, effective capacitor voltage balancing, and excellent current quality, achieving a THD of 0.7%.