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Distributed robust estimation with dynamics uncertainties and random communication topologies

  • Peking University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper discusses the design of distributed structures and gains for estimation of sensor network with nonlinear uncertain dynamics. Each sensor estimates the system state not only on its own but also on its neighbors' information. Besides, these sensors communicate with their neighbors over a random communication topology, i.e., their measurements are transmitted randomly at every step. In addition, both the system uncertainties and its linearization errors are taken into consideration in this paper. It is strictly proved that an optimized upper bound of the estimation error covariance with respect to the proposed filtering method can be achieved.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Industrial Technology, ICIT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1767-1771
Number of pages5
ISBN (Electronic)9781538663769
DOIs
StatePublished - Feb 2019
Externally publishedYes
Event2019 IEEE International Conference on Industrial Technology, ICIT 2019 - Melbourne, Australia
Duration: 13 Feb 201915 Feb 2019

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2019-February

Conference

Conference2019 IEEE International Conference on Industrial Technology, ICIT 2019
Country/TerritoryAustralia
CityMelbourne
Period13/02/1915/02/19

Keywords

  • Distributed kalman filter
  • Random topology
  • Sensor network
  • System uncertainty

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