S. Chabane, C. Stoica, T. Alamo, E. Camacho, D. Dumur
{"title":"基于分区集隶属度估计的传感器故障检测与诊断","authors":"S. Chabane, C. Stoica, T. Alamo, E. Camacho, D. Dumur","doi":"10.1109/MED.2014.6961381","DOIUrl":null,"url":null,"abstract":"This paper proposes new sensor fault detection algorithms for linear discrete-time systems with bounded perturbations and bounded measurement noise. This fault detection technique is based on a zonotopic set-membership estimation method. The first proposed fault detection algorithm allows to detect the presence of a fault. A second algorithm leading to guaranteed state estimation in the presence of sensor faults is developed, sometimes leading to conservative results. Thereafter, the last proposed algorithm allows to reduce the conservativeness while offering an estimation of the state closer to the real state of the faulty system. An illustrative example is analyzed to show the performance of the proposed algorithms.","PeriodicalId":127957,"journal":{"name":"22nd Mediterranean Conference on Control and Automation","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Sensor fault detection and diagnosis using zonotopic set-membership estimation\",\"authors\":\"S. Chabane, C. Stoica, T. Alamo, E. Camacho, D. Dumur\",\"doi\":\"10.1109/MED.2014.6961381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes new sensor fault detection algorithms for linear discrete-time systems with bounded perturbations and bounded measurement noise. This fault detection technique is based on a zonotopic set-membership estimation method. The first proposed fault detection algorithm allows to detect the presence of a fault. A second algorithm leading to guaranteed state estimation in the presence of sensor faults is developed, sometimes leading to conservative results. Thereafter, the last proposed algorithm allows to reduce the conservativeness while offering an estimation of the state closer to the real state of the faulty system. An illustrative example is analyzed to show the performance of the proposed algorithms.\",\"PeriodicalId\":127957,\"journal\":{\"name\":\"22nd Mediterranean Conference on Control and Automation\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd Mediterranean Conference on Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MED.2014.6961381\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd Mediterranean Conference on Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MED.2014.6961381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensor fault detection and diagnosis using zonotopic set-membership estimation
This paper proposes new sensor fault detection algorithms for linear discrete-time systems with bounded perturbations and bounded measurement noise. This fault detection technique is based on a zonotopic set-membership estimation method. The first proposed fault detection algorithm allows to detect the presence of a fault. A second algorithm leading to guaranteed state estimation in the presence of sensor faults is developed, sometimes leading to conservative results. Thereafter, the last proposed algorithm allows to reduce the conservativeness while offering an estimation of the state closer to the real state of the faulty system. An illustrative example is analyzed to show the performance of the proposed algorithms.