Full Text:   <230>

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CLC number: TP212;TN713

On-line Access: 2024-02-23

Received: 2023-07-28

Revision Accepted: 2024-02-23

Crosschecked: 2023-09-15

Cited: 0

Clicked: 384

Citations:  Bibtex RefMan EndNote GB/T7714


Jun HU




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Frontiers of Information Technology & Electronic Engineering  2024 Vol.25 No.2 P.237-249


Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

Author(s):  Zhibin HU, Jun HU, Cai CHEN, Hongjian LIU, Xiaojian YI

Affiliation(s):  Department of Applied Mathematics, Harbin University of Science and Technology, Harbin 150080, China; more

Corresponding email(s):   jhu@hrbust.edu.cn, chencailee@hrbust.edu.cn

Key Words:  Distributed fusion filtering, Multi-sensor nonlinear singular systems, Dynamic event-triggered scheme, Outlier-resistant filter, Uniform boundedness

Zhibin HU, Jun HU, Cai CHEN, Hongjian LIU, Xiaojian YI. Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(2): 237-249.

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%T Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme
%A Zhibin HU
%A Jun HU
%A Hongjian LIU
%A Xiaojian YI
%J Frontiers of Information Technology & Electronic Engineering
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%@ 2095-9184
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300508

T1 - Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme
A1 - Zhibin HU
A1 - Jun HU
A1 - Cai CHEN
A1 - Hongjian LIU
A1 - Xiaojian YI
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 25
IS - 2
SP - 237
EP - 249
%@ 2095-9184
Y1 - 2024
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2300508

This paper investigates the problem of outlier-resistant distributed fusion filtering (DFF) for a class of multi-sensor nonlinear singular systems (MSNSSs) under a dynamic event-triggered scheme (DETS). To relieve the effect of measurement outliers in data transmission, a self-adaptive saturation function is used. Moreover, to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization, a DETS is adopted to regulate the frequency of data transmission. For the addressed MSNSSs, our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS; the local upper bound (UB) on the filtering error covariance (FEC) is derived by solving the difference equations and minimized by designing proper filter gains. Furthermore, according to the local filters and their UBs, a DFF algorithm is presented in terms of the inverse covariance intersection fusion rule. As such, the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers, thereby improving the estimation performance. Moreover, the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is presented. Finally, the validity of the developed algorithm is checked using a simulation example.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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