2026-04-18T04:35:08Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4434912026-01-27T02:33:34Zcom_2072_1033col_2072_452950

urn:hdl:2117/443491 Nonlinear dynamic modeling and control of ethanol steam reforming for hydrogen production Arcilla-Osorio, Mateo Destro, Francesco Ocampo-Martínez, Carlos Llorca, Jordi Braatz, Richard D. Àrees temàtiques de la UPC::Informàtica::Automàtica i control Àrees temàtiques de la UPC::Enginyeria química Hydrogen production Ethanol steam reforming Nonlinear dynamic model Staged separation membrane reactor PID control Smart energy systems Copyright © 2025. The Authors. This is an open access article under the CC BY-NC-ND license. Hydrogen is a key facilitator of smart energy systems, with applications in power generation, transportation, and industry. This article presents a nonlinear dynamic model of ethanol steam reforming (ESR) within an staged separation membrane reactor (SSMR) and explores its application in real-time control. A proportional-integral-derivative (PID) controller is implemented to regulate hydrogen output by adjusting ethanol feed to match a step-wise demand profile. Simulation results confirm the model applicability and control effectiveness. This study demonstrates the potential of advanced modeling for hydrogen-based energy applications, paving the way for future research in advanced control design and broader energy systems integration. This work was supported in part by the Ag`encia de Gesti´o d’Ajuts Universitaris i de Recerca (AGAUR), Generalitat de Catalunya under Grant FI SDUR 2023 and the Spanish project SEAMLESS: Sustainable learning-based Management of Multiresource Large-scale Systems (ref. PID2023-148840OB-I00), funded by MCIN/AEI/10.13039/501100011033/FEDER, UE. Peer Reviewed Postprint (published version) 2025 Article https://www.sciencedirect.com/science/article/pii/S2405896325007086 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-148840OB-I00/ES/GESTION SOSTENIBLE Y BASADA EN APRENDIZAJE DE SISTEMAS MULTI-RECURSO DE GRAN ESCALA/ http://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access Attribution-NonCommercial-NoDerivatives 4.0 International Elsevier