Distributed Kalman Filtering for Interconnected Dynamic Systems
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 11571-11580 |
Journal / Publication | IEEE Transactions on Cybernetics |
Volume | 52 |
Issue number | 11 |
Online published | 16 Jun 2021 |
Publication status | Published - Nov 2022 |
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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.
In: IEEE Transactions on Cybernetics, Vol. 52, No. 11, 11.2022, p. 11571-11580.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review