{"title":"Fault estimation using adaptive observer-based technique for time delay fractional-order systems","authors":"Halima Atitallah, A. Aribi, M. Aoun","doi":"10.1109/ASET.2019.8871006","DOIUrl":null,"url":null,"abstract":"This paper proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example.","PeriodicalId":216138,"journal":{"name":"2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASET.2019.8871006","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 proposes a technique to detect and estimate faults for fractional-order systems with time delay. Two observers are used in this method. Indeed, a time-delay fractional Luenberger observer is generated to detect fault. An adaptive fractional order with time delay observer is then constructed to estimate the fault by providing an on-line estimation algorithm. The convergence criteria of this observer is expressed via linear matrix inequalities (LMIs) by the use of a specific Lyapunov function considering the continuous frequency disturbed model. The validity of the fault detection and estimation technique is shown by a numerical example.