M. Zhong, S. Ding, B. Tang, Ping Zhang, T. Jeinsch
{"title":"An LMI approach to robust fault detection filter design for discrete-time systems with model uncertainty","authors":"M. Zhong, S. Ding, B. Tang, Ping Zhang, T. Jeinsch","doi":"10.1109/CDC.2001.980421","DOIUrl":null,"url":null,"abstract":"Deals with the design of a fault detection filter for discrete-time systems with both model uncertainty and disturbances. We propose an approach to the solution, which consists of two steps: (a) selection of a stable weighting function matrix, optimized in the sense of the maximum sensitivity from the faults to residual signal; (b) formulation of the design of fault detection filters as a model-matching problem and solving the optimization problem using the LMI technique. The achieved results are illustrated by a numerical example.","PeriodicalId":131411,"journal":{"name":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2001.980421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
Deals with the design of a fault detection filter for discrete-time systems with both model uncertainty and disturbances. We propose an approach to the solution, which consists of two steps: (a) selection of a stable weighting function matrix, optimized in the sense of the maximum sensitivity from the faults to residual signal; (b) formulation of the design of fault detection filters as a model-matching problem and solving the optimization problem using the LMI technique. The achieved results are illustrated by a numerical example.