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International Workshop on Active Inference

IWAI 2020: Active Inference pp 42–51Cite as

Online System Identification in a Duffing Oscillator by Free Energy Minimisation

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1326))

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.

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Notes

  1. 1.

    http://nonlinearbenchmark.org/.

  2. 2.

    Derivations at https://github.com/biaslab/IWAI2020-onlinesysid.

  3. 3.

    Experiment notebooks at https://github.com/biaslab/IWAI2020-onlinesysid.

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Acknowledgements

The author thanks Magnus Koudahl, Albert Podusenko and Thijs van de Laar for insightful discussions and the reviewers for their constructive feedback.

Author information

Authors and Affiliations

  1. Bayesian Intelligent Autonomous Systems Lab, TU Eindhoven, Eindhoven, 5612AP, Netherlands

    Wouter M. Kouw

Authors
  1. Wouter M. Kouw
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Correspondence to Wouter M. Kouw .

Editor information

Editors and Affiliations

  1. Ghent University, Ghent, Belgium

    Tim Verbelen

  2. Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands

    Pablo Lanillos

  3. University of Sussex, Brighton, UK

    Christopher L. Buckley

  4. Ghent University, Ghent, Belgium

    Cedric De Boom

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Kouw, W.M. (2020). Online System Identification in a Duffing Oscillator by Free Energy Minimisation. In: Verbelen, T., Lanillos, P., Buckley, C.L., De Boom, C. (eds) Active Inference. IWAI 2020. Communications in Computer and Information Science, vol 1326. Springer, Cham. https://doi.org/10.1007/978-3-030-64919-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-64919-7_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64918-0

  • Online ISBN: 978-3-030-64919-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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