A persisting challenge in nonlinear dynamical modelling is parameter inference from data. Provided that an appropriate model structure was selected, the identication 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.
|Title of host publication||Tuning nonlinear state-space models using unconstrained multiple shooting|
|Number of pages||7|
|Publication status||Accepted/In press - 27 Feb 2020|
- Unconstrained multiple shooting
- Nonlinear state-space models
- Nonlinear optimisation
- Unstable initialisation