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  • 标题:Tuning nonlinear state-space models using unconstrained multiple shooting
  • 本地全文:下载
  • 作者:J. Decuyper ; M.C. Runacres ; J. Schoukens
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:334-340
  • DOI:10.1016/j.ifacol.2020.12.182
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractA 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.
  • 关键词:KeywordsUnconstrained multiple shootingNonlinear state-space modelsNonlinear optimisationUnstable initialisation
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