Cover Image

Reinforcement learning meets bioprocess control through behaviour cloning: Real-world deployment in an industrial photobioreactor

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gil, Juan D., Chanona, Ehecatl Antonio Del Rio, Guzmán, José L., Berenguel, Manuel
Format:	Preprint
Published:	2025
Subjects:	Systems and Control Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses
by: Espinel-Ríos, Sebastián, et al.
Published: (2025)

ARRTOC: Adversarially Robust Real-Time Optimization and Control
by: Ahmed, Akhil, et al.
Published: (2023)

Hierarchical RL-MPC for Demand Response Scheduling
by: Bloor, Maximilian, et al.
Published: (2025)

Survey and Tutorial of Reinforcement Learning Methods in Process Systems Engineering
by: Bloor, Maximilian, et al.
Published: (2025)

Data-driven Koopman MPC using Mixed Stochastic-Deterministic Tubes
by: Zhong, Zhengang, et al.
Published: (2025)

Enhancing industrial microalgae production through Economic Model Predictive Control
by: Otálora, Pablo, et al.
Published: (2025)

Enhancing reinforcement learning for population setpoint tracking in co-cultures
by: Espinel-Ríos, Sebastián, et al.
Published: (2024)

Addressing Terminal Constraints in Data-Driven Demand Response Scheduling
by: Bloor, Maximilian, et al.
Published: (2026)

Control-Informed Reinforcement Learning for Chemical Processes
by: Bloor, Maximilian, et al.
Published: (2024)

PC-Gym: Benchmark Environments For Process Control Problems
by: Bloor, Maximilian, et al.
Published: (2024)

Switching-time bioprocess control with pulse-width-modulated optogenetics
by: Espinel-Ríos, Sebastián
Published: (2025)

A Comprehensive Benchmark Platform for Process Control Research of Outdoor Microalgae Raceway Reactors
by: Rodríguez-Miranda, Enrique, et al.
Published: (2025)

Sketch2Simulation: Automating Flowsheet Generation via Multi Agent Large Language Models
by: Bahamdan, Abdullah, et al.
Published: (2026)

MORSE: Multi-Objective Reinforcement Learning via Strategy Evolution for Supply Chain Optimization
by: Kotecha, Niki, et al.
Published: (2025)

Reinforcement learning for robust dynamic metabolic control
by: Espinel-Ríos, Sebastián, et al.
Published: (2025)

Linear Dynamics meets Linear MDPs: Closed-Form Optimal Policies via Reinforcement Learning
by: Makdah, Abed AlRahman Al, et al.
Published: (2025)

Surrogate-Based Optimization Techniques for Process Systems Engineering
by: Neufang, Mathias, et al.
Published: (2024)

When control meets large language models: From words to dynamics
by: Nosrati, Komeil, et al.
Published: (2026)

Reinforcement learning-based adaptive speed controllers in mixed autonomy condition
by: Wang, Han, et al.
Published: (2024)

Learning to Optimize meets Neural-ODE: Real-Time, Stability-Constrained AC OPF
by: Di Vito, Vincenzo, et al.
Published: (2024)

Leveraging Graph Neural Networks and Multi-Agent Reinforcement Learning for Inventory Control in Supply Chains
by: Kotecha, Niki, et al.
Published: (2024)

Scalable machine learning-based approaches for energy saving in densely deployed Open RAN
by: Liang, Xuanyu, et al.
Published: (2026)

Real-time control of multiphase processes with learned operators
by: Guida, Paolo, et al.
Published: (2026)

Machine learning for industrial sensing and control: A survey and practical perspective
by: Lawrence, Nathan P., et al.
Published: (2024)

Input-to-state stability meets small-gain theory
by: Mironchenko, Andrii
Published: (2024)

Real-world energy data of 200 feeders from low-voltage grids with metadata in Germany over two years
by: Treutlein, Manuel, et al.
Published: (2026)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
by: van Laatum, Bart, et al.
Published: (2024)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
by: Mitra, Aritra, et al.
Published: (2023)

Circular economy meets building automation
by: Cai, Hanmin
Published: (2023)

Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems
by: Savage, Tom, et al.
Published: (2024)

Smart Charging Impact Analysis using Clustering Methods and Real-world Distribution Feeders
by: Shrestha, Ravi Raj, et al.
Published: (2025)

Dual-quaternion learning control for autonomous vehicle trajectory tracking with safety guarantees
by: Nieto, Omayra Yago, et al.
Published: (2026)

Coupled Rendezvous and Docking Maneuver control of satellite using Reinforcement learning-based Adaptive Fixed-Time Sliding Mode Controller
by: Sahoo, Rakesh Kumar, et al.
Published: (2025)

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom
by: Bian, Yuexin, et al.
Published: (2025)

Learning swarm behaviour from a flock of homing pigeons using inverse optimal control
by: Islam, Afreen
Published: (2026)

Towards Real-world Deployment of NILM Systems: Challenges and Practices
by: Xue, Junyu, et al.
Published: (2024)

Characterizing simulation relations through control architectures in abstraction-based control
by: Calbert, Julien, et al.
Published: (2024)

Low-cost Real-world Implementation of the Swing-up Pendulum for Deep Reinforcement Learning Experiments
by: Böhm, Peter, et al.
Published: (2025)

Bio-inspired metaheuristic optimization for hierarchical architecture design of industrial control systems
by: Zakirzyanov, Ruslan
Published: (2026)

Online learning for robust voltage control under uncertain grid topology
by: Yeh, Christopher, et al.
Published: (2023)