首页    期刊浏览 2024年10月06日 星期日
登录注册

文章基本信息

  • 标题:Distributed Fault Diagnosis for a Class of Time-Varying Systems over Sensor Networks with Stochastic Protocol
  • 本地全文:下载
  • 作者:Yuxia Liu ; Li Sheng ; Ming Gao
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:778-783
  • DOI:10.1016/j.ifacol.2020.12.830
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper is concerned with the distributed fault diagnosis problem for a class of time-varying systems over sensor networks with nonlinearity and uncertainty. For the purpose of solving the problem of data conflict, the stochastic protocol is used to determine which node has the right to send data to the estimator at a certain transmission time. The aim of this paper is to design a set of distributed estimators to detect, isolate and estimate fault signals. The upper bound of estimation error covariance is obtained by solving two recursive matrix equations and the upper bound can be minimized by designing appropriate estimator gain at each step. Finally, a numerical example is provided to show the effectiveness of the proposed design scheme.
  • 关键词:Keywordsdistributed fault diagnosisRiccati-like difference equationssensor networksstochastic protocol
国家哲学社会科学文献中心版权所有