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Distributed state estimation with state equality constraints in the presence of packet dropping

Xiaoyu Fu, Xinmin Song, Xiyu Liu and Min Zhang

Applied Mathematics and Computation, 2023, vol. 451, issue C

Abstract: In this paper, we investigate distributed Kalman consensus filter with state equality constraints in the presence of packet dropping. Firstly, the unconstrained distributed Kalman filter is designed by utilizing the local measurement information of each sensor node, and then the consensus term is added to it to derive the unconstrained distributed Kalman consensus filter. Secondly, we research the equality constrained distributed Kalman consensus filter based on the projection operator to achieve better filter performance, where the unconstrained estimation gain is calculated by solving a modified algebraic Riccati equation and a Lyapunov equation. Additionally, we design the second type of equality constrained distributed Kalman consensus filter by using time-stamping technology and projection operator to eliminate the effect of the Lyapunov equation in the infinite time domain on the convergence analysis, and its unconstrained estimation gain only requires solving a modified algebraic Riccati equation. Finally, the simulation experiments demonstrate that the equality constrained distributed Kalman consensus filter outperforms the unconstrained filter and that the second type of estimator exhibits superior performance compared to the first.

Keywords: Distributed Kalman filtering; Packet dropping; Distributed consensus filter; State equality constraints (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:451:y:2023:i:c:s0096300323002126

DOI: 10.1016/j.amc.2023.128043

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