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A robust minimax Semidefinite Programming formulation for optimal design of experiments for model parametrization

Please always quote using this URN: urn:nbn:de:0297-zib-54626
  • 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.

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Author:Belmiro P.M. Duarte, Guillaume Sagnol, Nuno M.C. Oliveira
Document Type:ZIB-Report
Tag:Optimal design of experiments; Robust minmax designs; Semidefinite Programming
MSC-Classification:62-XX STATISTICS / 62Kxx Design of experiments [See also 05Bxx] / 62K25 Robust parameter designs
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C22 Semidefinite programming
Date of first Publication:2015/04/22
Series (Serial Number):ZIB-Report (15-03)
Published in:Appeared in: Computer Aided Chemical Engineering Volume 37, 2015, Pages 905–910 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering
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