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  • 标题:A Relaxed Solution to Unknown Input Observers for State and Fault Estimation
  • 本地全文:下载
  • 作者:Daoliang Tan ; Daoliang Tan ; Ron J. Patton
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:21
  • 页码:1048-1053
  • DOI:10.1016/j.ifacol.2015.09.665
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Abstract A lot of effort has been devoted to the unknown input observer (UIO) research over the past years. However, the strong disturbance decoupling assumption (manifested as some rank constraint) is often implicitly embedded in much of the existing UIO work. With the purpose of state and fault estimation, this fact motivates us to investigate the viability of the UIO research when the strong disturbance decoupling is not possible, i.e., a “degenerate” problem of UIO decoupling exists. Inspired by the scheme of reducing the effect of external disturbance on estimation error, this paper incorporates the relaxed UIO (RxUIO) concept by means of the H∞ H2, and mixed H2¡H∞ techniques. Necessary and sufficient conditions for the existence of different RxUIOs are presented in the tractable linear matrix inequality (LMI) form. Numerical experiments are presented to illustrate the effectiveness of the suggested method.
  • 关键词:KeywordsFault DiagnosisFault EstimationUnknown Input ObserverLinear Matrix Inequality
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