@inproceedings{619a155c803c4e2dbdb150d45baea428,
title = "Design of a Robust MPC for Copper Recovery in an Industrial Flotation Column",
abstract = "This paper presents the design of a RMPC (Robust Model Predictive Controller) for effective control of the copper recovery in an industrial flotation column. Copper ore properties vary frequently causing uncertainties and disturbances in the dynamics of the recovery process in the flotation column. Using the system identification tools, a MIMO model of this plant was achieved, whose validation results exhibited adequacy degrees of 88.21% for froth depth, and 87.32% for air holdup. The design of the RMPC was carried out based on the nominal MIMO model and its obtained uncertainties. It was demonstrated that the designed RMPC makes it possible to control the process with high precision under various industrial operation scenarios. The simulation results of the control system designed with the RMPC and the GPC (Generalized Predictive Controller) revealed an improved performance when using the RMPC.",
keywords = "Robust control, additive uncertainties, column flotation cell, copper recovery process, min-max approach, predictive control, system identification",
author = "R. Rivas-Perez and J. Sotomayor-Moriano and Perez-Zu{\~n}iga, {C. G.} and J. Ccarita",
note = "Publisher Copyright: Copyright {\textcopyright} 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/); 22nd IFAC World Congress ; Conference date: 09-07-2023 Through 14-07-2023",
year = "2023",
month = jul,
day = "1",
doi = "10.1016/j.ifacol.2023.10.1838",
language = "English",
series = "IFAC-PapersOnLine",
publisher = "Elsevier B.V.",
number = "2",
pages = "4448--4453",
editor = "Hideaki Ishii and Yoshio Ebihara and Jun-ichi Imura and Masaki Yamakita",
booktitle = "IFAC-PapersOnLine",
edition = "2",
}