{"title":"滑模观测器乘性故障估计及其应用","authors":"Chen Wu","doi":"10.1109/ICCAR.2015.7166023","DOIUrl":null,"url":null,"abstract":"Sliding mode observer (SMO) plays an important role in system states or faults estimation, where mostly additive faults are considered. Few papers consider multiplicative faults. The paper proposed an approach for multiplicative fault estimation based on SMO, where linear matrix inequality technique is used to calculate the observer gain. A wind turbine fault detection example shows the design procedure of proposed SMO and its usefulness.","PeriodicalId":422587,"journal":{"name":"2015 International Conference on Control, Automation and Robotics","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multiplicative fault estimation using sliding mode observer with application\",\"authors\":\"Chen Wu\",\"doi\":\"10.1109/ICCAR.2015.7166023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sliding mode observer (SMO) plays an important role in system states or faults estimation, where mostly additive faults are considered. Few papers consider multiplicative faults. The paper proposed an approach for multiplicative fault estimation based on SMO, where linear matrix inequality technique is used to calculate the observer gain. A wind turbine fault detection example shows the design procedure of proposed SMO and its usefulness.\",\"PeriodicalId\":422587,\"journal\":{\"name\":\"2015 International Conference on Control, Automation and Robotics\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Control, Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAR.2015.7166023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Control, Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAR.2015.7166023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiplicative fault estimation using sliding mode observer with application
Sliding mode observer (SMO) plays an important role in system states or faults estimation, where mostly additive faults are considered. Few papers consider multiplicative faults. The paper proposed an approach for multiplicative fault estimation based on SMO, where linear matrix inequality technique is used to calculate the observer gain. A wind turbine fault detection example shows the design procedure of proposed SMO and its usefulness.