Full Text:   <340>

Summary:  <104>

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: 522

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jun HU

https://orcid.org/0000-0002-7852-5064

Cai CHEN

https://orcid.org//0000-0001-7006-5027

-   Go to

Article info.
Open peer comments

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

http://doi.org/10.1631/FITEE.2300508


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",
volume="25",
number="2",
pages="237-249",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300508"
}

%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 Cai CHEN
%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

TY - JOUR
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


Abstract: 
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.

动态事件触发策略下非线性离散奇异系统的抗野值分布式融合滤波


胡志斌1,2,胡军1,2,3,陈才3,刘宏建4,伊枭剑5,6,7
1哈尔滨理工大学应用数学系,中国哈尔滨市,150080
2哈尔滨理工大学黑龙江省复杂系统优化控制与智能分析重点实验室,中国哈尔滨市,150080
3哈尔滨理工大学自动化学院,中国哈尔滨市,150080
4安徽工程大学数理学院,中国芜湖市,241000
5北京理工大学机电学院,中国北京市,100081
6北京理工大学长三角研究院,中国嘉兴市,314003
7北京理工大学唐山研究院,中国唐山市,063099
摘要:本文研究一类多传感器非线性奇异系统在动态事件触发策略下的抗野值分布式融合滤波问题。采用自适应饱和函数设计滤波器可以有效减轻数据传输中测量野值的影响。为进一步节省每个传感器节点的能耗,提高资源利用效率,利用动态事件触发策略调节数据传输频率。对于所处理的非线性奇异系统,本文主要目的是在测量野值和动态事件触发策略影响下构造局部抗野值滤波器,并通过求解差分方程得到滤波误差协方差矩阵的局部上界。同时,所设计的滤波器增益可以确保该局部上界迹取值最小。此外,根据局部滤波器及其上界、逆协方差交叉融合准则,提出可以降低数据传输频率和测量野值的影响的分布式融合滤波算法。在均方意义下,讨论滤波误差的一致有界性并给出相应的充分条件。最后,通过仿真例子验证算法的有效性。

关键词:分布式融合滤波;多传感器非线性奇异系统;动态事件触发策略;抗野值滤波器;一致有界

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

Reference

[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

<1>

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