2026-04-14T17:29:52Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/588482023-03-28T19:00:30Zcom_10324_1168com_10324_931com_10324_894col_10324_1302

Oliveira Silva, Erika Prada Moraga, César de Montes López, Daniel Alberto Navia, Daniel 2023-03-07T09:13:09Z 2023-03-07T09:13:09Z 2023 Computers & Chemical Engineering, 2023, vol. 173, 108205 0098-1354 https://uvadoc.uva.es/handle/10324/58848 10.1016/j.compchemeng.2023.108205 108205 Computers & Chemical Engineering This paper presents a method to estimate process dynamic gradients along the transient that combined with the idea of Modifier Adaptation (MA) improves the economic cost fuction of the examples presented. The gradient estimation method, called TMA, aims to reduce the large convergence time required to traditional MA in processes of slow dynamics. TMA is used with an economic predictive control with MA (eMPC+TMA) and was applied in two case studies: a simulation of the Williams-Otto reactor and a hybrid laboratory plant based on the Van de Vusse reactor. The results show that eMPC+TMA could reach the plant real steady-state optimum despite process-model mismatch, due to the inclusion of the effect of process dynamics in the TMA algorithm. Despite the estimation errors, the proposed methodology improved the profit of the experimental case study, with respect to the use of an eMPC with no modifiers, by about 20% for the unconstrained case, and by 130% in the constrained case. eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2023 The Authors Attribution-NonCommercial-NoDerivatives 4.0 Internacional Ingeniería Automatización Economic MPC with Modifier Adaptation using Transient Measurements info:eu-repo/semantics/article