Consensus-based Distributed Kalman-Bucy Filter for Continuous-time Systems

Jingbo Wu, Anja Elser, Shen Zeng, Frank Allgöwer

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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.

Original languageEnglish
Pages (from-to)321-326
Number of pages6
JournalIFAC-PapersOnLine
Volume49
Issue number22
DOIs
StatePublished - 2016

Keywords

  • Coupled Riccati Equations
  • Distributed Estimation
  • Kalman Filter

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