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  • 标题:Robust Fault Detection using Set-based Approaches for LPV Systems: Application to Autonomous Vehicles
  • 本地全文:下载
  • 作者:Shuang Zhang ; Vicenç Puig ; Sara Ifqir
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:6
  • 页码:31-36
  • DOI:10.1016/j.ifacol.2022.07.101
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper addresses the problem of robust fault detection for Linear Parameter Varying (LPV) systems using set-based approaches. Two approaches are proposed, based respectively on set-based state and parameter estimation methods, for implementing direct and inverse test for robust fault detection (FD). The uncertainties are assumed to be unknown but bounded and their effect is propagated using zonotopic sets. These robust FD test methods aim at checking the consistency between the measured and estimated behaviour obtained from estimator in the parameter or output space considering the effect of the uncertainty. When an inconsistency is detected, a fault can be indicated. A case study based on an autonomous vehicle is employed to compare the performance of proposed FD tests.
  • 关键词:KeywordsLPVLMIfault detectionzonotopeSMA
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