Polynomial representation of model uncertainty in dynamical systems

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Abstract

This chapter introduces an approach to capture unmodelled components in dynamical systems through a hierarchical polynomial expansion in the state space. This approach is reminiscent of the empirical acceleration approach commonly used in precise orbit determination to account for unmodelled components in the force model.

Original languageEnglish
Title of host publicationAdvances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences
Subtitle of host publicationComputational Methods in Applied Sciences
Place of PublicationCham, Switzerland
PublisherSpringer
Pages419-432
Number of pages14
ISBN (Print)9783319899862
DOIs
Publication statusPublished - 1 Aug 2019

Publication series

NameComputational Methods in Applied Sciences
Volume48
ISSN (Print)1871-3033

Keywords

  • dynamical systems
  • hierarchical polynomial expansion
  • uncertainty
  • space missions
  • astronautics

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  • Projects

    Marie Curie ITN (Stardust)

    Vasile, M., Biggs, J., Burns, D., Hopkins, J., Macdonald, M., McInnes, C., Minisci, E. & Maddock, C.

    European Commission - FP7 - General

    1/02/1331/01/17

    Project: Research

    Cite this

    Vasile, M. (2019). Polynomial representation of model uncertainty in dynamical systems. In Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences: Computational Methods in Applied Sciences (pp. 419-432). (Computational Methods in Applied Sciences; Vol. 48). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-89988-6_25