Huang, Chunbing;
Cattani, Federica;
Galvanin, Federico;
(2023)
An optimal experimental design strategy for improving parameter estimation in stochastic models.
Computers and Chemical Engineering
, 170
, Article 108133. 10.1016/j.compchemeng.2023.108133.
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Abstract
Systematic model-based design of experiment is essential to maximise the information from an experimental campaign. This technique is even more important to design experiments in systems described by stochastic models where the information quantity is characterised by intrinsic uncertainty, which has a significant impact on the experimental design for yielding informative data for precisely estimating model parameters. In this work, a new method for stochastic model-based design of experiments (SMBDoE) is presented to simultaneously identify the optimal operating conditions and the allocation of sampling points in time. The optimal experiment is identified by two sampling strategies selecting sampling intervals based on the average and the uncertainty of Fisher information. Seed coating is used as a case study to illustrate the feasibility of the method in identifying optimal coating conditions and sampling strategy in an industrial application.
| Type: | Article |
|---|---|
| Title: | An optimal experimental design strategy for improving parameter estimation in stochastic models |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.compchemeng.2023.108133 |
| Publisher version: | https://doi.org/10.1016/j.compchemeng.2023.108133 |
| Language: | English |
| Additional information: | © 2023 The Author(s). Published by Elsevier Ltd. under a Creative Commons license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Stochastic model-based design of experiments, stochastic simulation, seed coating system, sampling strategy |
| 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/10162690 |
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