Tuning nonlinear state-space models using unconstrained multiple shooting

Jan Decuyper, Mark C. Runacres, Johan Schoukens, Koen Tiels

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)
100 Downloads (Pure)

Abstract

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
JournalIFAC-PapersOnLine
Volume53
Issue number2
DOIs
Publication statusPublished - Nov 2020
Event21st World Congress of the International Federation of Aufomatic Control (IFAC 2020 World Congress) - Berlin, Germany
Duration: 12 Jul 202017 Jul 2020
Conference number: 21
https://www.ifac2020.org/

Keywords

  • Unconstrained multiple shooting
  • Nonlinear state-space models
  • Nonlinear optimisation
  • Unstable initialisation

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