A Robust Minimax Semidefinite Programming Formulation for Optimal Design of Experiments for Model Parametrization
- Model-based optimal design of experiments (M-bODE) is a crucial step in model parametrization since it encloses a framework that maximizes the amount of information extracted from a battery of lab experiments. We address the design of M-bODE for dynamic models considering a continuous representation of the design. We use Semidefinite Programming (SDP) to derive robust minmax formulations for nonlinear models, and extend the formulations to other criteria. The approaches are demonstrated for a CSTR where a two-step reaction occurs.
| Author: | Belmiro P.M. Duarte, Guillaume Sagnol, Nuno M.C. Oliveira |
|---|---|
| Document Type: | In Proceedings |
| Parent Title (English): | 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering |
| Volume: | 37 |
| First Page: | 905 |
| Last Page: | 910 |
| Series: | Computer Aided Chemical Engineering |
| Year of first publication: | 2015 |
| Preprint: | urn:nbn:de:0297-zib-54626 |
| DOI: | https://doi.org/10.1016/B978-0-444-63578-5.50146-8 |
