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Online System Identification in a Duffing Oscillator by Free Energy Minimisation

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Active Inference (IWAI 2020)

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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.

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

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Correspondence to Wouter M. Kouw .

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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.

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  • Print ISBN: 978-3-030-64918-0

  • Online ISBN: 978-3-030-64919-7

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