Pankajakshan, A;
Waldron, C;
Quaglio, M;
Gavriilidis, A;
Galvanin, F;
(2019)
A Multi-Objective Optimal Experimental Design Framework for Enhancing the Efficiency of Online Model-Identification Platforms.
Engineering
10.1016/j.eng.2019.10.003.
(In press).
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Abstract
Recent advances in automation and digitization enable the close integration of physical devices with their virtual counterparts, facilitating the real-time modeling and optimization of a multitude of processes in an automatic way. The rich and continuously updated data environment provided by such systems makes it possible for decisions to be made over time to drive the process toward optimal targets. In many manufacturing processes, in order to achieve an overall optimal process, the simultaneous assessment of multiple objective functions related to process performance and cost is necessary. In this work, a multi-objective optimal experimental design framework is proposed to enhance the efficiency of online model-identification platforms. The proposed framework permits flexibility in the choice of trade-off experimental design solutions, which are calculated online—that is, during the execution of experiments. The application of this framework to improve the online identification of kinetic models in flow reactors is illustrated using a case study in which a kinetic model is identified for the esterification of benzoic acid (BA) and ethanol in a microreactor.
| Type: | Article |
|---|---|
| Title: | A Multi-Objective Optimal Experimental Design Framework for Enhancing the Efficiency of Online Model-Identification Platforms |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.eng.2019.10.003 |
| Publisher version: | https://doi.org/10.1016/j.eng.2019.10.003 |
| Language: | English |
| Additional information: | Copyright © 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Multi-objective optimization, Optimal design of experiments, Online |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10083925 |
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