Automated Design and Selection of Metaheuristics for PID Control in Power Electronics
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.
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BibTeX
@article{zambranogutierrez2026automated,
title = {{Automated Design and Selection of Metaheuristics for PID Control in Power Electronics}},
author = {Daniel Zambrano-Gutierrez and José Carlos Ortiz-Bayliss and Iván Amaya and Maricela Rodríguez-Nieto and Juan Gabriel Avina-Cervantes and Jorge Cruz-Duarte},
journal = {IEEE Access},
year = {2026},
month = sep,
doi = {10.1109/access.2026.3673085},
url = {https://hal.science/hal-05758479v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Automated Design and Selection of Metaheuristics for PID Control in Power Electronics
AU - Daniel Zambrano-Gutierrez
AU - José Carlos Ortiz-Bayliss
AU - Iván Amaya
AU - Maricela Rodríguez-Nieto
AU - Juan Gabriel Avina-Cervantes
AU - Jorge Cruz-Duarte
PY - 2026
DA - 2026/09/22
JO - IEEE Access
DO - 10.1109/access.2026.3673085
UR - https://hal.science/hal-05758479v1
AB - 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.
SN - 2169-3536
SN - 2169-3536
ER -