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  • 标题:Robust Fault Detection and Isolation of Discrete-Time LPV Systems Combining Set-theoretic UIO and Invariant Sets ⁎
  • 本地全文:下载
  • 作者:Junbo Tan ; Feng Xu ; Jun Yang
  • 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:724-729
  • DOI:10.1016/j.ifacol.2020.12.822
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper proposes a mixed active/passive robust fault detection and isolation (FDI) method for discrete-time linear paramter varying (LPV) systems based on set-theoretic unknown input observers (SUIO) and invariant sets. The robustness against system uncertainties in FDI of LPV systems can be guaranteed by actively decoupling or passively bounding their effect on residual signal. Furthermore, the quadratic H∞stability condition of the LPV-form state-estimation-error dynamics is established based on a group of linear matrix inequalities (LMIs). Under the precondition of stability, a family of residual sets are constructed to establish set-separation guaranteed fault isolation (FI) conditions using invariant sets off-line. As long as the occurred faults satisfy the guaranteed FI conditions, they can be isolated from each other. At the end, a numerical example is used to illustrate the effectiveness of the proposed method.
  • 关键词:KeywordsFault detectionisolationLPV systemsSet-theoretic unknown input observerInvariant sets
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