Tuning nonlinear state-space models using unconstrained multiple shooting

Research output: Contribution to journalConference paper

2 Citations (Scopus)

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 - 1 Jan 2020

Bibliographical note

Funding Information:
This work was supported by the Fund for Scientific Research (F★WO-Vlaanderen) under projects G.0280.15N and G.0901.17N, (FWO-Vlaanderen) under projects G.0280.15N and G.0901.17N, EOS Project no 30468160, the Swedish Research Council (VR) via Systems (contract number: 621-2016-06079), and by the Swedish Foundation for Strategic Research (SSF) via the project ASSEMBLE Foundation for Strategic Research (SSF) via the project ASSEMBLE (contract number: RIT15-0012).

Publisher Copyright:
Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

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