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  • 标题:Combined state and parameter estimation for a landslide model using Kalman filter
  • 本地全文:下载
  • 作者:Mohit Mishra ; Gildas Besançon ; Guillaume Chambon
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:7
  • 页码:304-309
  • DOI:10.1016/j.ifacol.2021.08.376
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe paper presents a combined state and parameter estimation for a landslide model using a Kalman filter. The model under investigation is based on underlying mechanics that depicts a landslide behavior. This system is described by an Ordinary Differential Equation (ODE) with displacement as a state and landslide geometrical and material properties as parameters. The Kalman filter approach is utilized on a simplified model equation for state and parameter estimation. Finally, the presented approach is validated by two illustrative examples, the first one a synthetic case study and the second one on Super-Sauze landslide data taken from the literature.
  • 关键词:KeywordsState estimationparameter estimationKalman filterlandslide modelSuper-Sauze landslide
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