eprintid: 1508466 rev_number: 25 eprint_status: archive userid: 608 dir: disk0/01/50/84/66 datestamp: 2016-09-13 13:48:27 lastmod: 2020-02-13 06:34:13 status_changed: 2016-09-13 13:48:27 type: article metadata_visibility: show creators_name: Strutzel, FAM creators_name: Bogle, IDL title: Assessing plant design with regard to MPC performance ispublished: pub divisions: UCL divisions: A01 divisions: B09 keywords: Integrated process design and control; Model predictive control (MPC); Zone constrained model predictive control; Zone control; Controllability analysis; Crude oil distillation note: © 2016 Elsevier Inc. This manuscript version is made available under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International license (CC BY-NC-ND 4.0). This license allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licenses are available at http://creativecommons.org/ licenses/by/4.0. Access may be initially restricted by the publisher. abstract: Model Predictive Control is ubiquitous in the chemical industry and offers great advantages over traditional controllers. Notwithstanding, new plants are being projected without taking into account how design choices affect the MPC’s ability to deliver better control and optimization. Thus a methodology to determine if a certain design option favours or hinders MPC performance would be desirable. This paper presents the economic MPC optimization index whose intended use is to provide a procedure to compare different designs for a given process, assessing how well they can be controlled and optimised by a zone constrained MPC. The index quantifies the economic benefits available and how well the plant performs under MPC control given the plant’s controllability properties, requirements and restrictions. The index provides a monetization measure of expected control performance. This approach assumes the availability of a linear state-space model valid within the control zone defined by the upper and lower bounds of each controlled and manipulated variable. We have used a model derived from simulation step tests as a practical way to use the method. The impact of model uncertainty on the methodology is discussed. An analysis of the effects of disturbances on the index illustrates how they may reduce profitability by restricting the ability of a MPC to reach dynamic equilibrium near process restrictions, which in turn increases product quality giveaway and costs. A case of study consisting of four alternative designs for a realistically sized crude oil atmospheric distillation plant is provided in order to demonstrate the applicability of the index. date: 2016-11-02 date_type: published official_url: http://dx.doi.org/10.1016/j.compchemeng.2016.07.007 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1154622 doi: 10.1016/j.compchemeng.2016.07.007 lyricists_name: Bogle, Ian lyricists_id: IDLBO29 actors_name: Bogle, Ian actors_id: IDLBO29 actors_role: owner full_text_status: public publication: Computers & Chemical Engineering volume: 94 number: C pagerange: 180-211 issn: 0098-1354 citation: Strutzel, FAM; Bogle, IDL; (2016) Assessing plant design with regard to MPC performance. Computers & Chemical Engineering , 94 (C) pp. 180-211. 10.1016/j.compchemeng.2016.07.007 <https://doi.org/10.1016/j.compchemeng.2016.07.007>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1508466/3/ASSESSING%20PLANT%20DESIGN%20WITH%20REGARD%20TO%20MPC%20PERFORMANCE_CACEFINAL.pdf