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Revista Colombiana de Tecnologías de Avanzada
Article . 2025 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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Control industrial por aprendizaje reforzado

Authors: Yessica Cindy Mora Cubides; Daniel Steven Arias Otálora; José Antonio Tumialan Borja; Hugo Fernando Velasco Peña;

Control industrial por aprendizaje reforzado

Abstract

En este artículo se presenta la implementación de la técnica de control de caudal con inteligencia artificial (DDPG) en un prototipo funcional completamente instrumentado con sensores y actuadores industriales, simulando la recirculación de caudal a través de tres tanques. Se presenta la metodología utilizada para la identificación del proceso (modelo de primer orden más tiempo muerto (FOPDT)) mediante comunicación OPC Cliente Servidor con Matlab®. También se presenta el diseño del algoritmo de aprendizaje por refuerzo y su adaptación en el entorno de aprendizaje con datos experimentales. Los resultados de la simulación fueron satisfactorios en comparación con las técnicas de control tradicionales, demostrando robustez frente a perturbaciones forzadas. Finalmente, se evaluó la implementación del control de aprendizaje reforzado integrando TIA Portal y Matlab (a través de un controlador PLC-S7-1500) con una referencia de 600 l/h, logrando un sobre impulso del 0% con un tiempo de asentamiento de 22s. Comparado con otros sistemas de control, se observó una mejor respuesta en el tiempo de asentamiento y un control libre de sobre impulso. Finalmente, se aplicaron perturbaciones al sistema, observando su efecto con relación al flujo.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold