Buck Converter Control Based on Optimal Control Algorithm Model Predictive Control

Precise and rapid output voltage regulation remains a critical challenge in Buck converter applications. Conventional control strategies often suffer from computational inefficiency, limited voltage accuracy, and significant overshoot under load transients, compromising dynamic performance. To address these limitations, this study introduces an optimal control-based model predictive control framework for Buck converters, optimizing both transient response and steady-state precision. The proposed approach demonstrates superior dynamic stability during startup, load changes, and reference voltage variations, ensuring rapid convergence with minimal overshoot. Comprehensive simulations validate the algorithm's efficacy, showcasing its potential for high-performance power conversion systems.