Safety-Aware Multi-Agent Deep Reinforcement Learning for Adaptive Fault-Tolerant Control in Sensor-Lean Industrial Systems: Validation in Beverage CIP

Fault-tolerant control in safety-critical industrial systems demands adaptive responses to equipment degradation, parameter drift, and sensor failures while maintaining strict operational constraints. Traditional model-based controllers struggle under these conditions, requiring extensive retuning a...

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Главные авторы:	Apolinar González-Potes, Ramón A. Félix-Cuadras, Luis J. Mena, Vanessa G. Félix, Rafael Martínez-Peláez, Rodolfo Ostos, Pablo Velarde-Alvarado, Alberto Ochoa-Brust
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2026-01-01
Серии:	Technologies
Предметы:	fault-tolerant control reinforcement learning multi-agent systems safety-critical systems deep learning industrial automation
Online-ссылка:	https://www.mdpi.com/2227-7080/14/1/44
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