A Comparative Evaluation of Metaheuristic Optimization Methods for Control Applications

David García, Marco Herrera, Oscar Camacho

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Resumen

This paper presents a comparative study of metaheuristic techniques for optimizing tuning in two controllers applied to processes characterized by long-dead times. Experimental validation was conducted on an Arduino Temperature Control Lab with additional software-induced delays. The investigation involved tuning the Smith Predictor and PI controllers by utilizing three distinct meta-heuristic optimization algorithms: the Whale Optimization Algorithm, Gray Wolf Optimizer, and Ant Lion Optimizer. The pursuit was guided by the minimization of the Integral Square Error, serving as the cost function. The effectiveness of these control strategies was evaluated using diverse performance indices. The results accentuate the predominance of the Smith Predictor coupled with the Whale Optimization Algorithm, emerging as the most suitable and balanced choice among the examined control methodologies.

Idioma originalInglés
Título de la publicación alojadaECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
EditoresDavid Rivas Lalaleo, Manuel Ignacio Ayala Chauvin
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798350338232
DOI
EstadoPublicada - 2023
Evento7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023 - Ambato, Ecuador
Duración: 10 oct. 202313 oct. 2023

Serie de la publicación

NombreECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

Conferencia

Conferencia7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023
País/TerritorioEcuador
CiudadAmbato
Período10/10/2313/10/23

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