{"title":"Fault detection observer design for Takagi-Sugeno fuzzy systems with finite-frequency specifications.","authors":"Jitao Li, Xu Fang, Zhihao Zhang, Yujia Wang, Xing Liu, Mingjun Zhang","doi":"10.1016/j.isatra.2024.10.010","DOIUrl":null,"url":null,"abstract":"<p><p>This paper addresses robust fault detection observer design for a class of discrete-time Takagi-Sugeno fuzzy systems with finite-frequency specifications. A novel design method is presented based on finite-frequency H<sub>-</sub>/H<sub>∞</sub> indices and peak-to-peak analysis. The finite-frequency H<sub>-</sub> and H<sub>∞</sub> indices are utilized to characterize fault sensitivity and disturbance robustness, respectively. Peak-to-peak analysis is used to derive a dynamic threshold. To further reduce the conservatism caused by predefined parameters, an iterative algorithm is developed. Both theoretical proof and simulation results show that the performance of the proposed method is not worse than the existing works.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.isatra.2024.10.010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses robust fault detection observer design for a class of discrete-time Takagi-Sugeno fuzzy systems with finite-frequency specifications. A novel design method is presented based on finite-frequency H-/H∞ indices and peak-to-peak analysis. The finite-frequency H- and H∞ indices are utilized to characterize fault sensitivity and disturbance robustness, respectively. Peak-to-peak analysis is used to derive a dynamic threshold. To further reduce the conservatism caused by predefined parameters, an iterative algorithm is developed. Both theoretical proof and simulation results show that the performance of the proposed method is not worse than the existing works.
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