Diseño óptimo de un controlador FOPID para un sistema de levitación magnético

Jaqueline González Cabañas; AIDA PAOLA GINEZ SÁNCHEZ; Omar Aguilar Mejia; Antonio Valderrabano-Gonzalez; Irving Barragan Vite

doi:10.29057/icbi.v14iespecial3.18034

Autores/as

Jaqueline González Cabañas Universidad Autónoma del Estado de Hidalgo https://orcid.org/0009-0000-8335-8208
AIDA PAOLA GINEZ SÁNCHEZ Universidad Autónoma del Estado de Hidalgo https://orcid.org/0009-0009-3963-4020
Omar Aguilar Mejia Universidad Autónoma del Estado de Hidalgo https://orcid.org/0000-0001-6316-3518
Antonio Valderrabano-Gonzalez Universidad Panamericana https://orcid.org/0000-0002-8509-6376
Irving Barragan Vite Universidad Autónoma del Estado de Hidalgo https://orcid.org/0000-0002-3625-6943

DOI:

https://doi.org/10.29057/icbi.v14iespecial3.18034

Palabras clave:

Sistema de suspensión magnético, Control PI, Control de orden fraccionario PI, Optimización

Resumen

En este estudio, se propone por primera vez utilizar el algoritmo de optimización del demonio de Tasmania (AODT) para calcular los parámetros óptimos de un controlador PID de orden fraccional (FOPID) para regular la posición de un objeto móvil dentro de un sistema de suspensión magnética. El AODT es un novedoso método de optimización metaheurística basado en población e inspirado en las diferentes formas de cómo obtener su alimento. Para validar el rendimiento del AODT los resultados se compararon con otros algoritmos, como el algoritmo de optimización del pelicano (APO) y el algoritmo de optimización del rumbo de las nubes (AORN). Para analizar el desempeño del FOPID-AODT se realizaron pruebas estadísticas y de perfil de convergencia para demostrar el éxito del algoritmo propuesto. El análisis de la eficiencia y desempeño dinámico del maglev con el controlador FOPID-AODT se realiza mediante análisis de respuesta transitoria y en estado estacionario. Los resultados mostraron que el esquema de control FOPID-AODT diseñado muestra un mejor rendimiento en comparación a los ajustados mediante los algoritmos AORN y APO.

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