Optimal experimental design and some related control problems

Abstract

This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experimental design is briefly presented, and the role of experimental design in the asymptotic properties of estimators is emphasized. Although most of the paper concerns parametric models, some results are also presented for statistical learning and prediction with nonparametric models.

Available at http://www.elsevier.com/locate/automatica

References in corpus (2)

• Improvements on removing non-optimal support points in D-optimum design algorithms
• Asymptotic behaviour of a family of gradient algorithms in R^d and Hilbert spaces

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