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Online system identification in a Duffing oscillator by free energy minimisation (2009.00845v1)
Published 2 Sep 2020 in cs.LG, cs.NE, cs.SY, eess.SY, and stat.ML
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.