Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

MG Potters, X Bombois, M Mansoori Habib Abadi, PMJ van den Hof

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Abstract

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.
Original languageEnglish
Pages (from-to)1533 - 1553
JournalInternational Journal of Control
Volume89
Issue number8
DOIs
Publication statusPublished - 2016

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