An Adaptive Competitive Surrogate Modeling Framework for Efficient Control Parameter Optimization of Buck Converters
Controller parameter tuning for buck converters is computationally expensive because it requires repeated high-fidelity simulations. Moreover, the prediction performance of individual surrogate models may vary across different regions and stages of the optimization process, whereas fixed multi-surrogate combinations ca...