{"title":"面向状态的可观测性评估和机械估计应用中的传感器放置","authors":"Julian Staiger, L. Mazzanti, F. Naets","doi":"10.1109/ICM54990.2023.10102033","DOIUrl":null,"url":null,"abstract":"Optimal sensor selection and placement are of paramount importance in estimation and control applications. In this article, we exploit observability metrics based on the observability Gramian to effectively determine sensor locations that contribute significantly to the individual observability of a limited number of states of importance. In particular, the ellipsoid representation of the observability Gramian is utilized to ensure optimal sensor placement in conjunction with a state-based observability evaluation. The method is demonstrated on a numerical example of a mechanical linear time-invariant system. The results show that the method can highlight states with particularly good observability and place a set of sensors in such a way that the observability is maximised for an arbitrary set of interested states.","PeriodicalId":416176,"journal":{"name":"2023 IEEE International Conference on Mechatronics (ICM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State-oriented evaluation of observability and sensor placement for mechanical estimation applications\",\"authors\":\"Julian Staiger, L. Mazzanti, F. Naets\",\"doi\":\"10.1109/ICM54990.2023.10102033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimal sensor selection and placement are of paramount importance in estimation and control applications. In this article, we exploit observability metrics based on the observability Gramian to effectively determine sensor locations that contribute significantly to the individual observability of a limited number of states of importance. In particular, the ellipsoid representation of the observability Gramian is utilized to ensure optimal sensor placement in conjunction with a state-based observability evaluation. The method is demonstrated on a numerical example of a mechanical linear time-invariant system. The results show that the method can highlight states with particularly good observability and place a set of sensors in such a way that the observability is maximised for an arbitrary set of interested states.\",\"PeriodicalId\":416176,\"journal\":{\"name\":\"2023 IEEE International Conference on Mechatronics (ICM)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Mechatronics (ICM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICM54990.2023.10102033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Mechatronics (ICM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM54990.2023.10102033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State-oriented evaluation of observability and sensor placement for mechanical estimation applications
Optimal sensor selection and placement are of paramount importance in estimation and control applications. In this article, we exploit observability metrics based on the observability Gramian to effectively determine sensor locations that contribute significantly to the individual observability of a limited number of states of importance. In particular, the ellipsoid representation of the observability Gramian is utilized to ensure optimal sensor placement in conjunction with a state-based observability evaluation. The method is demonstrated on a numerical example of a mechanical linear time-invariant system. The results show that the method can highlight states with particularly good observability and place a set of sensors in such a way that the observability is maximised for an arbitrary set of interested states.