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  • 标题:Consensus-based Distributed Kalman-Bucy Filter for Continuous-time Systems
  • 本地全文:下载
  • 作者:Jingbo Wu ; Jingbo Wu ; Anja Elser
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:22
  • 页码:321-326
  • DOI:10.1016/j.ifacol.2016.10.417
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Abstract: In this paper we introduce a distributed consensus-based Kalman filter for distributed state estimation of continuous-time systems. In particular, we achieve stability of the estimation error only assuming that all agents together are able to observe the system, which is in contrast to each agent possessing this property individually. The algorithm is implementable without any precomputation of filter parameters, such as coupling strength, or global knowledge about the graph.
  • 关键词:KeywordsDistributed EstimationKalman FilterCoupled Riccati Equations
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