Investigating Bayesian robust experimental design with principles of global sensitivity analysis

Fei He, Hong Yue, Martin Brown

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

The purpose of model-based experimental design is to maximise the information gathered for quantitative model identification. Instead of the commonly used optimal experimental design, robust experimental design aims to address parametric uncertainties in the design process. In this paper, the Bayesian robust experimental design is investigated, where both a Monte Carlo sampling strategy and local sensitivity evaluation at each sampling point are employed to achieve the robust solution. The link between global sensitivity analysis (GSA) and the Bayesian robust experimental design is established. It is revealed that a lattice sampling based GSA strategy, the Morris method, can be explicitly interpreted as the Bayesian A-optimal design for the uniform hypercube type uncertainties.

Original languageEnglish
Title of host publicationDYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts
Pages577-582
Number of pages6
Volume9
EditionPART 1
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event9th International Symposium on Dynamics and Control of Process Systems, DYCOPS 2010 - Leuven, Belgium
Duration: 5 Jul 20107 Jul 2010

Conference

Conference9th International Symposium on Dynamics and Control of Process Systems, DYCOPS 2010
CountryBelgium
CityLeuven
Period5/07/107/07/10

Fingerprint

Design of experiments
Sensitivity analysis
Sampling
Identification (control systems)
Uncertainty

Keywords

  • Bayesian method
  • Global sensitivity analysis
  • Lattice sampling
  • Parameter estimation
  • Robust experimental design
  • Systems biology

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

He, F., Yue, H., & Brown, M. (2010). Investigating Bayesian robust experimental design with principles of global sensitivity analysis. In DYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts (PART 1 ed., Vol. 9, pp. 577-582)

Investigating Bayesian robust experimental design with principles of global sensitivity analysis. / He, Fei; Yue, Hong; Brown, Martin.

DYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts. Vol. 9 PART 1. ed. 2010. p. 577-582.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

He, F, Yue, H & Brown, M 2010, Investigating Bayesian robust experimental design with principles of global sensitivity analysis. in DYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts. PART 1 edn, vol. 9, pp. 577-582, 9th International Symposium on Dynamics and Control of Process Systems, DYCOPS 2010, Leuven, Belgium, 5/07/10.
He F, Yue H, Brown M. Investigating Bayesian robust experimental design with principles of global sensitivity analysis. In DYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts. PART 1 ed. Vol. 9. 2010. p. 577-582
He, Fei ; Yue, Hong ; Brown, Martin. / Investigating Bayesian robust experimental design with principles of global sensitivity analysis. DYCOPS 2010 - 9th International Symposium on Dynamics and Control of Process Systems, Book of Abstracts. Vol. 9 PART 1. ed. 2010. pp. 577-582
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