Distributed Kalman Filtering for Interconnected Dynamic Systems

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

22 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)11571-11580
Journal / PublicationIEEE Transactions on Cybernetics
Volume52
Issue number11
Online published16 Jun 2021
Publication statusPublished - Nov 2022

Abstract

This article is concerned with the distributed Kalman filtering problem for interconnected dynamic systems, where the local estimator of each subsystem is designed only by its own information and neighboring information. A decoupling strategy is developed to minimize the impact of interconnected terms on the estimation performance, and then the recursive and distributed Kalman filter is derived in the minimum mean-squared error sense. Moreover, by using Lyapunov criterion for linear time-varying systems, stability conditions are presented such that the designed estimator is bounded. Finally, a heavy duty vehicle platoon system is employed to show the effectiveness and advantages of the proposed methods.

Research Area(s)

  • Decoupling strategy, distributed Kalman filtering, interconnected dynamic systems (IDSs), stability analysis

Citation Format(s)

Distributed Kalman Filtering for Interconnected Dynamic Systems. / Zhang, Yuchen; Chen, Bo; Yu, Li et al.
In: IEEE Transactions on Cybernetics, Vol. 52, No. 11, 11.2022, p. 11571-11580.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review