Publication: Economic model predictive control (EMPC) of an industrial diesel hydroprocessing plant
dc.contributor.coauthor | Is, Gamze | |
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.kuauthor | Aydın, Erdal | |
dc.contributor.kuauthor | Arkun, Yaman | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | 311745 | |
dc.contributor.yokid | 108526 | |
dc.date.accessioned | 2024-11-09T23:27:39Z | |
dc.date.issued | 2016 | |
dc.description.abstract | Diesel hydroprocessing is a refinery process by which the sulfur impurities are removed by hydrodesulfurization and the main product diesel is obtained by hydrocracking. The industrial Diesel Hydroprocessing Plant considered in this study consists of two hydrodesulfurization reactors and one hydrocracking reactor in series. The feed to the plant is a blend of four different raw material streams which are heavy diesel (HD), light diesel (LD), light vacuum gas oil (LVGO) and imported diesel from another refinery. A two-layer, hierarchical Economic Model Predictive Control (EMPC) structure is proposed to maximize the profit of the plant. The plant-wide profit is maximized by computing the optimal set-points by the upper economic model predictive control layer while these set-points are tracked by the regulatory model predictive controllers in the lower level. Set-point tracking and disturbance rejection performances of the proposed EMPC structure are tested through closed-loop simulations. (C) 2016. IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. | |
dc.description.indexedby | WoS | |
dc.description.indexedby | Scopus | |
dc.description.issue | 7 | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsorship | TUPRAS Refineries The authors gratefully acknowledge the financial support of TUPRAS Refineries. | |
dc.description.volume | 49 | |
dc.identifier.doi | 10.1016/j.ifacol.2016.07.403 | |
dc.identifier.issn | 2405-8963 | |
dc.identifier.scopus | 2-s2.0-84991039874 | |
dc.identifier.uri | http://dx.doi.org/10.1016/j.ifacol.2016.07.403 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/11756 | |
dc.identifier.wos | 381504800096 | |
dc.keywords | Economic model predictive control | |
dc.keywords | Non-linear control | |
dc.keywords | Hierarchical control | |
dc.keywords | Real-time optimization | |
dc.keywords | Hydrodesulfurization | |
dc.keywords | Hydrocracking optimization | |
dc.language | English | |
dc.publisher | Elsevier Science Bv | |
dc.source | IFAC Papersonline | |
dc.subject | Automation | |
dc.subject | Control systems | |
dc.title | Economic model predictive control (EMPC) of an industrial diesel hydroprocessing plant | |
dc.type | Conference proceeding | |
dspace.entity.type | Publication | |
local.contributor.authorid | 0000-0002-8498-4830 | |
local.contributor.authorid | 0000-0002-3740-379X | |
local.contributor.kuauthor | Aydın, Erdal | |
local.contributor.kuauthor | Arkun, Yaman | |
relation.isOrgUnitOfPublication | c747a256-6e0c-4969-b1bf-3b9f2f674289 | |
relation.isOrgUnitOfPublication.latestForDiscovery | c747a256-6e0c-4969-b1bf-3b9f2f674289 |