A sub-optimal distributed Kalman filter with fusion feedback for acyclic systems

S. M. Azizi, K. Khorasani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

In this paper, a new distributed Kalman filter is proposed for state estimation of systems with acyclic digraph, namely acyclic systems. This method can be applied to a number of large-scale systems including sensor networks and formation flying missions. An acyclic system can be represented by an overlapping block-diagonal state space (OBDSS) model, which requires an extensive communication overhead for implementing a centralized Kalman filter scheme. The OBDSS model is transformed into our proposed constrained-state block-diagonal state space (CSBDSS) model, which is purely diagonal and simplifies the implementation of a distributed Kalman filter scheme. Corresponding to each Kalman filter iteration a specific constrained-state condition needs to be satisfied that is embedded with a fusion feedback. Simulation results confirm the effectiveness of our proposed analytical work.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5151-5157
Number of pages7
ISBN (Print)9781424438716
DOIs
StatePublished - 2009
Externally publishedYes
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/TerritoryChina
CityShanghai
Period12/15/0912/18/09

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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