Issue |
E3S Web Conf.
Volume 67, 2018
The 3rd International Tropical Renewable Energy Conference “Sustainable Development of Tropical Renewable Energy” (i-TREC 2018)
|
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Article Number | 03012 | |
Number of page(s) | 5 | |
Section | Multifunctional and Advanced Materials | |
DOI | https://doi.org/10.1051/e3sconf/20186703012 | |
Published online | 26 November 2018 |
Multi Input Multi Output (MIMO) Control 2x2 at Vacuum Distillation Unit for LVGO, MVGO, and HVGO Production
Chemical Engineering Department, Universitas Indonesia, Depok, Indonesia
* Coresponding author: wahid@che.ui.ac.id
Currently, Indonesia is still experiencing a fuel deficit, so it is necessary to build a new oil refinery and a process optimization at an existing refinery. A vacuum distillation unit (VDU) is used to process the atmospheric residue products from crude distillation unit (CDU). A multivariable model predictive control (MMPC) is proposed to improve a control performance in VDU because of the interaction between variables in the unit. Therefore, it is necessary to find the variables that interact with each other. In this study only two variables are discussed. Set point (SP) and disturbance changes are used to test the control performance with integral of square error (ISE) as the indicator. The results are compared with the control performance of the PI controller and a single MPC. As a result, the feed flow rate and bottom-stage temperature are strongest interactions so that both are determined as controlled variables in MMPC. The control performance of MMPC is better than the PI controller and the single MPC with control performance improvement of 48% to the PI controller and 21% to MPC on for Feed Flow Rates, and 98% to the PI controller and 27% to MPC on Bottom Stage Temperature. While on disturbance changes the enhancement is 35% for the Bottom Stage Temperature.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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