{"title":"Event-triggered distributed state and disturbance estimation for LTI systems using a network of observers.","authors":"Junqi Yang, Dongzheng Wang, Jianfeng Xu, Yantao Chen","doi":"10.1016/j.isatra.2025.07.017","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, the distributed estimation issues of state, unknown input and measurement noise are studied. First, the new auxiliary output matrices are constructed such that the auxiliary output is unaffected by measurement noise. Second, an event-triggered mechanism is developed, and a predefined-time distributed estimation method is proposed to estimate the auxiliary output matrices. Then, the unknown input is treated as the output of an external system, and the original system state together with external system state is augmented into a new state. Third, the event-triggered distributed observers are designed to estimate original system state and unknown input. In addition, the measurement noise is also reconstructed. Finally, the simulation shows that the system state and all disturbances are estimated asymptotically, which significantly reduces the communication burden.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.isatra.2025.07.017","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
In this paper, the distributed estimation issues of state, unknown input and measurement noise are studied. First, the new auxiliary output matrices are constructed such that the auxiliary output is unaffected by measurement noise. Second, an event-triggered mechanism is developed, and a predefined-time distributed estimation method is proposed to estimate the auxiliary output matrices. Then, the unknown input is treated as the output of an external system, and the original system state together with external system state is augmented into a new state. Third, the event-triggered distributed observers are designed to estimate original system state and unknown input. In addition, the measurement noise is also reconstructed. Finally, the simulation shows that the system state and all disturbances are estimated asymptotically, which significantly reduces the communication burden.