Online system identification in a Duffing oscillator by free energy minimisation

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Online system identification is the estimation of parameters of a dynamical system, such as mass or friction coefficients, for each measurement of the input and output signals. Here, the nonlinear stochastic differential equation of a Duffing oscillator is cast to a generative model and dynamical parameters are inferred using variational message passing on a factor graph of the model. The approach is validated with an experiment on data from an electronic implementation of a Duffing oscillator.The proposed inference procedure performs as well as offline prediction error minimisation in a state-of-the-art nonlinear model.
Original languageEnglish
Title of host publicationActive Inference - First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Proceedings
EditorsTim Verbelen, Pablo Lanillos, Christopher L. Buckley, Cedric De Boom
PublisherSpringer
Pages42-51
Number of pages10
Edition1
ISBN (Electronic)978-3-030-64919-7
ISBN (Print)978-3-030-64918-0
DOIs
Publication statusPublished - 18 Dec 2020
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Ghent, Belgium
Duration: 14 Sep 202018 Sep 2020
Conference number: 2020
https://ecmlpkdd2020.net/

Publication series

NameCommunications in Computer and Information Science
Volume1326
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Abbreviated titleECML-PKDD
CountryBelgium
CityGhent
Period14/09/2018/09/20
Internet address

Keywords

  • Duffing oscillator
  • Forney factor graphs
  • Free energy minimisation
  • Online system identification
  • Variational message passing

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