{"title":"Simultaneous State and Fault Estimation for Descriptor Systems using an Augmented PD Observer","authors":"F. Shi, R. Patton","doi":"10.3182/20140824-6-ZA-1003.01383","DOIUrl":null,"url":null,"abstract":"Abstract This paper proposes an augmented Proportional plus Derivative (PD) state estimator to achieve simultaneous system state and fault estimation of descriptor systems. Descriptor systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system model is subject to model uncertainty, external disturbance or sensor noise. The H ∞ performance is adopted to improve the estimator robustness subject to disturbance, sensor noise or model uncertainty. The estimator gains are obtained via an LMI approach. An example is studied to show the usefulness and effectiveness of the proposed approach.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"75 1","pages":"8006-8011"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Proceedings Volumes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3182/20140824-6-ZA-1003.01383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
Abstract This paper proposes an augmented Proportional plus Derivative (PD) state estimator to achieve simultaneous system state and fault estimation of descriptor systems. Descriptor systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system model is subject to model uncertainty, external disturbance or sensor noise. The H ∞ performance is adopted to improve the estimator robustness subject to disturbance, sensor noise or model uncertainty. The estimator gains are obtained via an LMI approach. An example is studied to show the usefulness and effectiveness of the proposed approach.