Projects per year
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.
Original language | English |
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Pages (from-to) | 11571-11580 |
Journal | IEEE Transactions on Cybernetics |
Volume | 52 |
Issue number | 11 |
Online published | 16 Jun 2021 |
DOIs | |
Publication status | Published - Nov 2022 |
Research Keywords
- Decoupling strategy
- distributed Kalman filtering
- interconnected dynamic systems (IDSs)
- stability analysis
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Dive into the research topics of 'Distributed Kalman Filtering for Interconnected Dynamic Systems'. Together they form a unique fingerprint.Projects
- 2 Finished
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GRF: Nonlinear Fusion Estimation for Networked Sensor Systems
HO, W. C. D. (Principal Investigator / Project Coordinator)
1/01/20 → 8/02/24
Project: Research
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GRF: Secure Estimation and Control of Networked Systems under Cyber-attacks
HO, W. C. D. (Principal Investigator / Project Coordinator)
1/12/17 → 3/11/21
Project: Research