Tuning nonlinear state-space models using unconstrained multiple shooting

Research output: Contribution to journalConference paper

1 Citation (Scopus)


A persisting challenge in nonlinear dynamical modelling is parameter inference from data. Provided that an appropriate model structure was selected, the identification problem is profoundly affected by a choice of initialisation. A particular challenge that may arise is initialisation within a region of the parameter space where the model is not contractive. Exploring such regions is not feasible using the conventional optimisation tools for they require a bounded evaluation of the cost. This work proposes an unconstrained multiple shooting technique, able to mitigate stability issues during the optimisation of nonlinear state-space models. The technique is illustrated on simulation results of a Van der Pol oscillator and benchmark results on a Bouc-Wen hysteretic system.

Original languageEnglish
Pages (from-to)334-340
Number of pages7
Issue number2
Publication statusPublished - 1 Jan 2020


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