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Discrete-time formulations as time discretization strategies in data assimilation

  • INRIA
  • Department of Mechanics École Polytechnique

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Data assimilation combines control theory and scientific computing to propose a set of methods for coupling dynamic models and data sequences for estimation and prediction in all engineering domains. Data assimilation naturally raises the question of how the developed control and optimization methods interact with the discretization of the underlying physical models, in particular their temporal discretization. We would like to present here some of the best known techniques developed for discrete-time models, which are essentially based on a mechanism involving model prediction on the one hand and data correction on the other. We show that they can be considered as specific discretizations of the data assimilation strategies proposed for continuous-time models in the sense of a discretization-and-then-control approach. This paradigm justifies the stability of these prediction-correction schemes, paving the way for convergence properties and justifying their popularity in practice.

Original languageEnglish
Title of host publicationNumerical Control
Subtitle of host publicationPart B
EditorsEmmanuel Trélat, Enrique Zuazua
PublisherElsevier B.V.
Pages297-339
Number of pages43
ISBN (Print)9780323850605
DOIs
Publication statusPublished - 1 Jan 2023
Externally publishedYes

Publication series

NameHandbook of Numerical Analysis
Volume24
ISSN (Print)1570-8659

Keywords

  • Kalman filtering
  • Least squares minimization
  • Luenberger observer
  • Mortensen estimator

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