abstract
- This work introduces an alternative approach that utilizes a Hyper-Heuristic framework under the umbrella of Automated Algorithm Design to dynamically tailor Metaheuristics (MHs) for fine-tuning PID controller parameters. Our findings emphasize the robust consistency, high precision, and adaptability of the method in creating custom, metaphor-free MHs. We employ this methodology in a case study of real-world engineering problems to develop a control-heuristic-based tuner that significantly improves the performance of DC-DC Buck converters across diverse operational conditions. The analysis reveals dominant trends in search operator preferences, highlighting the reliance on genetic crossover and swarm dynamics. These insights provide actionable directions for similar applications in power electronics. Through rigorous statistical comparisons, we verify the superior efficacy and reliability of our approach relative to conventional methods, remarking on its potential for broad application in the field.