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  • 标题:Modulation-Function-Based Data-Driven Design of Fault Detection Systems for Continuous-Time LTI Systems
  • 本地全文:下载
  • 作者:Benjamin Jahn ; Yuri A.W. Shardt
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:7
  • 页码:562-567
  • DOI:10.1016/j.ifacol.2022.07.503
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, a data-driven or model-free approach is presented to design a fault detection system of continuous-time linear time-invariant (LTI) systems based on input and output data in the time domain. The main idea is to directly identify the subspaces and their related matrices relevant for parity-space-based residual generation based on a modulated output equation by use of modulation functions and their properties. Therefore, the explicit model identification of the process for a model-based approach in a conventional two-step procedure can be avoided saving design effort especially for large-scale systems. A simulation of the resulting fault detection system is provided showing the effectiveness of the design approach.
  • 关键词:KeywordsFault DetectionModulation FunctionsSubspace MethodsResidual GenerationParity SpaceModel-FreeData-Driven
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