3 papers
eess.SY2026
From Learning to Control: Data-Driven Multi-Agent Reinforcement Learning for Multivariable Control in a Microalgae Bioprocess
Juan D. Gil, Ehecatl Antonio Del Rio Chanona, José Luis Guzmán +1
Effective control of bioprocesses is particularly challenging due to the intrinsic nonlinearity and dynamic variability of living-cell systems. In microalgae-based photobioreactors…
eess.SY2026
Unlocking feedforward capabilities in Model Predictive Control algorithms to deal with measurable disturbances
José Luis Guzmán, Igor Pataro, Juan D. Gil +1
Disturbance rejection is a central objective in process control, particularly when measurable disturbances can be exploited through feedforward action. Although Model Predictive Co…
eess.SY2025
Reinforcement learning meets bioprocess control through behaviour cloning: Real-world deployment in an industrial photobioreactor
Juan D. Gil, Ehecatl Antonio Del Rio Chanona, José L. Guzmán +1
The inherent complexity of living cells as production units creates major challenges for maintaining stable and optimal bioprocess conditions, especially in open Photobioreactors (…