Split Cost Function-Based Single-Horizon Finite-Set Model Predictive Control for Boost Converter With Loading Current Estimation

This article presents a robust single-horizon finite-set model predictive control (FS-MPC) method for controlling the output voltage of boost converters. Unlike the long-horizon FS-MPC approach, which addresses the nonminimum phase (NMP) behavior of the converter by extending the prediction horizon (thereby increasing computational effort), the proposed method ensures stable voltage regulation by incorporating inductor current regulation into the cost function. To achieve this, the desired inductor current is calculated based on input–output power balance theory. Unlike recent studies that require an additional sensor to measure the loading current, this article develops a loading current estimation approach to eliminate the need for extra current sensors, thereby enhancing the robustness of the proposed FS-MPC method. In addition, overcurrent protection, which is typically absent in conventional FS-MPC used for direct voltage regulation, is also incorporated into the proposed method. The conventional cost function is also modified to tackle the NMP behavior more effectively. The performance of the proposed method in regulating the output voltage is evaluated through simulation results. Finally, its effectiveness across a wide range of output power and various load characteristics, including resistive, constant power, and constant current loads, is validated via experimental results. The results demonstrate that the proposed method is not only able to eliminate the overshoot and undershoot but also can improve the settling time by 41% compared with a well-tuned conventional cascaded proportional-integral (PI) controller. In addition, the proposed method can reduce the computational burden by 84% compared with the conventional long-horizon FS-MPC approach.