2 citations · 2 across the 5 of their papers we have counts for
6 papers
Hierarchical Control via MPC-RL for Multi-Timescale Battery Systems
Rasa Pourjam, Ehecatl Antonio del Río Chanona, Paulina Quintanilla
Multi-timescale systems present a fundamental challenge, where fast operational decisions must coexist with long-horizon sustainability targets. In this work, we propose a new hier…
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…
Addressing Terminal Constraints in Data-Driven Demand Response Scheduling
Maximilian Bloor, Martha White, Ehecatl Antonio del Rio Chanona +1
Electrified chemical processes are incentivized by exposure to time-varying electricity markets to operate flexibly, but participating in demand response schemes can require satisf…
Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems
Tom Savage, Ehecatl Antonio del Rio Chanona
Bayesian optimization has been successfully applied throughout Chemical Engineering for the optimization of functions that are expensive-to-evaluate, or where gradients are not eas…
Machine Learning-Assisted Discovery of Flow Reactor Designs
Tom Savage, Nausheen Basha, Jonathan McDonough +3
Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such s…
Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations
Tom Savage, Nausheen Basha, Jonathan McDonough +2
The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highl…