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  • 标题:Model Based Fault Diagnosis of Low Earth Orbiting (LEO) Satellite using Spherical Unscented Kalman Filter
  • 本地全文:下载
  • 作者:P.V. Sunil Nag ; Gowtham kumar Silla ; Venkata Harsha Vardhan Gummadi
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:1
  • 页码:635-638
  • DOI:10.1016/j.ifacol.2016.03.127
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractModel based fault detection and diagnosis (FDD) using a non-linear estimation technique is presented here. The non-linear estimation technique namely spherical Unscented Kalman Filter (UKF) has been applied to other kinds of estimation problems but has never been applied to the FDD problem of a Low Earth Orbiting (LEO) satellite. It has been shown in this work that compared to the standard UKF, which is a derivative free estimation technique unlike the popular Extended Kalman Filter (EKF), the spherical UKF can perform better in terms of computational savings without sacrificing accuracy. Hence it is better suited for real-time fault diagnosis. A planar model of the satellite is used to demonstrate the technique.
  • 关键词:KeywordsFault DetectionKalman FilterNon-linear SystemsEstimationFilteringLEO satellite
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