Online system identification in a Duffing oscillator by free energy minimisation

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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
Subtitle of host publicationFirst International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings
EditorsTim Verbelen, Pablo Lanillos, Christopher L. Buckley, Cedric De Boom
Place of PublicationCham
Number of pages10
ISBN (Electronic)978-3-030-64919-7
ISBN (Print)978-3-030-64918-0
Publication statusPublished - 18 Dec 2020
Event1st International Workshop on Active Inference (IWAI 2020) - Virtual, Ghent, Belgium
Duration: 14 Sept 202014 Sept 2020
Conference number: 1

Publication series

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


Workshop1st International Workshop on Active Inference (IWAI 2020)
Abbreviated titleIWAI 2020
OtherIn Conjunction with ECML/PKDD 2020
Internet address


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


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