Full Text:   <489>

Summary:  <136>

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: 616

Citations:  Bibtex RefMan EndNote GB/T7714


Jun HU




-   Go to

Article info.
Open peer comments

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.

@article{title="Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme",
author="Zhibin HU, Jun HU, Cai CHEN, Hongjian LIU, Xiaojian YI",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%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
%V 25
%N 2
%P 237-249
%@ 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
ER -
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


[1]Alessandri A, Zaccarian L, 2018. Stubborn state observers for linear time-invariant systems. Automatica, 88:1-9.

[2]Cai LJ, Chang XH, 2023. Reduced-order filtering for discretetime singular systems under fading channels. Int J Syst Sci, 54(1):99-112.

[3]Chen XM, Xu ZB, Shang L, 2023. Satellite Internet of Things: challenges, solutions, and development trends. Front Inform Technol Electron Eng, 24(7):935-944.

[4]Dai LY, 1989. Singular Control Systems. Springer, Heidelberg, Germany.

[5]Dou YF, Ran CJ, 2019. WMF self-tuning Kalman estimators for multisensor singular system. Int J Syst Sci, 50(10):1873-1888.

[6]Ge XH, Xiao SY, Han QL, et al., 2022. Dynamic event-triggered scheduling and platooning control co-design for automated vehicles over vehicular ad-hoc networks. IEEE/CAA J Autom Sin, 9(1):31-46.

[7]Ge XH, Han QL, Wu Q, et al., 2023a. Resilient and safe platooning control of connected automated vehicles against intermittent denial-of-service attacks. IEEE/CAA J Autom Sin, 10(5):1234-1251.

[8]Ge XH, Han QL, Zhang XM, et al., 2023b. Communication resource-efficient vehicle platooning control with various spacing policies. IEEE/CAA J Autom Sin, early access.

[9]Girard A, 2015. Dynamic triggering mechanisms for event-triggered control. IEEE Trans Autom Contr, 60(7):1992-1997.

[10]Hajmohammadi R, Mobayen S, 2019. An efficient observer design method for singular discrete-time systems with time delays and nonlinearity: LMI approach. Sci Iran, 26(3):1690-1699.

[11]Hu J, Wang C, Caballero-Águila R, et al., 2023a. Distributed optimal fusion filtering for singular systems with random transmission delays and packet dropout compensations. Commun Nonl Sci Numer Simul, 119:107093.

[12]Hu J, Hu ZB, Caballero-Águila R, et al., 2023b. Distributed resilient fusion filtering for nonlinear systems with multiple missing measurements via dynamic event-triggered mechanism. Inform Sci, 637:118950.

[13]Hu J, Li JX, Yan HC, et al., 2023c. Optimized distributed filtering for saturated systems with amplify-and-forward relays over sensor networks: a dynamic event-triggered approach. IEEE Trans Neur Netw Learn Syst, early access.

[14]Hu J, Li JX, Liu GP, et al., 2023d. Optimized distributed filtering for time-varying saturated stochastic systems with energy harvesting sensors over sensor networks. IEEE Trans Signal Inform Process Netw, 9:412-426.

[15]Jiang B, Gao HY, Han F, et al., 2021. Recursive filtering for nonlinear systems subject to measurement outliers. Sci China Inform Sci, 64(7):172206.

[16]Jiang B, Shen YX, Dong HL, et al., 2022. Dynamic eventbased recursive filtering for networked systems under the encoding-decoding mechanism. J Franklin Inst, 359(12):6503-6522.

[17]Jin H, Sun SL, 2022. Distributed filtering for multi-sensor systems with missing data. Inform Fusion, 86-87:116-135.

[18]Ju YM, Ding DR, He X, et al., 2022. Consensus control of multi-agent systems using fault-estimation-in-the-loop: dynamic event-triggered case. IEEE/CAA J Autom Sin, 9(8):1440-1451.

[19]Li JX, Hu J, Cheng J, et al., 2022. Distributed filtering for time-varying state-saturated systems with packet disorders: an event-triggered case. Appl Math Comput, 434:127411.

[20]Li Q, Shen B, Wang ZD, et al., 2020. Recursive distributed filtering over sensor networks on Gilbert–Elliott channels: a dynamic event-triggered approach. Automatica, 113:108681.

[21]Li XG, Feng S, Hou N, et al., 2022. Surface microseismic data denoising based on sparse autoencoder and Kalman filter. Syst Sci Contr Eng, 10(1):616-628.

[22]Ma L, Wang ZD, Cai CX, et al., 2020. Dynamic event-triggered state estimation for discrete-time singularly perturbed systems with distributed time-delays. IEEE Trans Syst Man Cybern Syst, 50(9):3258-3268.

[23]Ma LF, Wang ZD, Hu J, et al., 2021. Probability-guaranteed envelope-constrained filtering for nonlinear systems subject to measurement outliers. IEEE Trans Autom Contr, 66(7):3274-3281.

[24]Meng XY, Chen Y, Ma LF, et al., 2022. Protocol-based variance-constrained distributed secure filtering with measurement censoring. Int J Syst Sci, 53(15):3322-3338.

[25]Nikoukhah R, Willsky AS, Levy BC, 1992. Kalman filtering and Riccati equation for descriptor systems. IEEE Trans Autom Contr, 37(9):1325-1342.

[26]Ning BD, Han QL, Zuo ZY, et al., 2023. Fixed-time and prescribed-time consensus control of multiagent systems and its applications: a survey of recent trends and methodologies. IEEE Trans Ind Inform, 19(2):1121-1135.

[27]Noack B, Sijs J, Reinhardt M, et al., 2017. Decentralized data fusion with inverse covariance intersection. Automatica, 79:35-41.

[28]Shen YX, Wang ZD, Shen B, et al., 2021. Outlier-resistant recursive filtering for multisensor multirate networked systems under weighted try-once-discard protocol. IEEE Trans Cybern, 51(10):4897-4908.

[29]Sun JB, Zhang CJ, Gu J, 2012. Decentralized optimal fusion filtering for multi-sensor multi-delay singular systems. Circ Syst Signal Process, 31(1):163-176.

[30]Sun SL, Ma J, 2007. Optimal filtering and smoothing for discrete-time stochastic singular systems. Signal Process, 87(1):189-201.

[31]Sun Y, Tian X, Wei GL, 2022. Finite-time distributed resilient state estimation subject to hybrid cyber-attacks: a new dynamic event-triggered case. Int J Syst Sci, 53(13):2832-2844.

[32]Tan HL, Shen B, Liu YR, et al., 2017. Eventtriggered multi-rate fusion estimation for uncertain system with stochastic nonlinearities and colored measurement noises. Inform Fusion, 36:313-320.

[33]Wang X, Sun SL, 2017. Optimal recursive estimation for networked descriptor systems with packet dropouts, multiplicative noises and correlated noises. Aerosp Sci Technol, 63:41-53.

[34]Wang XL, Sun Y, Ding DR, 2022. Adaptive dynamic programming for networked control systems under communication constraints: a survey of trends and techniques. Int J Netw Dyn Intell, 1(1):85-98.

[35]Wang YZ, Wang ZD, Zou L, et al., 2022. H proportionalintegral state estimation for T-S fuzzy systems over randomly delayed redundant channels with partly known probabilities. IEEE Trans Cybern, 52(10):9951-9963.

[36]Wen PY, Li XR, Hou N, et al., 2022. Distributed recursive fault estimation with binary encoding schemes over sensor networks. Syst Sci Contr Eng, 10(1):417-427.

[37]Xie ML, Ding DR, Ge XH, et al., 2022. Distributed platooning control of automated vehicles subject to replay attacks based on proportional integral observers. IEEE/CAA J Autom Sin, early access.

[38]Yao F, Ding YL, Hong SG, et al., 2022. A survey on evolved LoRa-based communication technologies for emerging Internet of Things applications. Int J Netw Dyn Intell, 1(1):4-19.

[39]Zhan DZ, Wang ST, Cai SG, 2023. Acoustic localization with multi-layer isogradient sound speed profile using TDOA and FDOA. Front Inform Technol Electron Eng, 24(1):164-175.

[40]Zhang XM, Han QL, Ge XH, et al., 2023. Sampled-data control systems with non-uniform sampling: a survey of methods and trends. Annu Rev Contr, 55:70-91.

[41]Zhao D, Wang ZD, Han QL, et al., 2022. Proportionalintegral observer design for uncertain time-delay systems subject to deception attacks: an outlier-resistant approach. IEEE Trans Syst Man Cybern Syst, 52(8):5152-5164.

[42]Zou L, Wang ZD, Hu J, et al., 2021. Communicationprotocol-based analysis and synthesis of networked systems: progress, prospects and challenges. Int J Syst Sci, 52(14):3013-3034.

[43]Zou L, Wang ZD, Hu J, et al., 2022. Ultimately bounded filtering subject to impulsive measurement outliers. IEEE Trans Autom Contr, 67(1):304-319.

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE