CLC number: TP13
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2023-12-07
Cited: 0
Clicked: 1268
Citations: Bibtex RefMan EndNote GB/T7714
Yajing MA, Yuan WANG, Zhanjie LI, Xiangpeng XIE. Event-triggered finite-time command-filtered tracking control for nonlinear time-delay cyber physical systems against cyber attacks[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(2): 225-236.
@article{title="Event-triggered finite-time command-filtered tracking control for nonlinear time-delay cyber physical systems against cyber attacks",
author="Yajing MA, Yuan WANG, Zhanjie LI, Xiangpeng XIE",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="25",
number="2",
pages="225-236",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300613"
}
%0 Journal Article
%T Event-triggered finite-time command-filtered tracking control for nonlinear time-delay cyber physical systems against cyber attacks
%A Yajing MA
%A Yuan WANG
%A Zhanjie LI
%A Xiangpeng XIE
%J Frontiers of Information Technology & Electronic Engineering
%V 25
%N 2
%P 225-236
%@ 2095-9184
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300613
TY - JOUR
T1 - Event-triggered finite-time command-filtered tracking control for nonlinear time-delay cyber physical systems against cyber attacks
A1 - Yajing MA
A1 - Yuan WANG
A1 - Zhanjie LI
A1 - Xiangpeng XIE
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 25
IS - 2
SP - 225
EP - 236
%@ 2095-9184
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2300613
Abstract: This article addresses the secure finite-time tracking problem via event-triggered command-filtered control for nonlinear time-delay cyber physical systems (CPSs) subject to cyber attacks. Under the attack circumstance, the output and state information of CPSs is unavailable for the feedback design, and the classical coordinate conversion of the iterative process is incompetent in relation to the tracking task. To solve this, a new coordinate conversion is proposed by considering the attack gains and the reference signal simultaneously. By employing the transformed variables, a modified fractional-order command-filtered signal is incorporated to overcome the complexity explosion issue, and the Nussbaum function is used to tackle the varying attack gains. By systematically constructing the Lyapunov–Krasovskii functional, an adaptive event-triggered mechanism is presented in detail, with which the communication resources are greatly saved, and the finite-time tracking of CPSs under cyber attacks is guaranteed. Finally, an example demonstrates the effectiveness.
[1]Chen WB, Chen YY, Zhang Y, 2022. Finite-time coordinated path-following control of leader-following multiagent systems. Front Inform Technol Electron Eng, 23(10):1511-1521.
[2]Chen WD, Li YX, Liu L, et al., 2022. Nussbaum-based adaptive fault-tolerant control for nonlinear CPSs with deception attacks: a new coordinate transformation tech-nology. IEEE Trans Cybern, early access.
[3]Choi YH, Yoo SJ, 2020. Neural-networks-based adaptive quantized feedback tracking of uncertain nonlinear strict-feedback systems with unknown time delays. J Franklin Inst, 357(15):10691-10715.
[4]Ding DR, Han QL, Ge XH, et al., 2021. Secure state estimation and control of cyber-physical systems: a survey. IEEE Trans Syst Man Cybern Syst, 51(1):176-190.
[5]Ge SS, Tee KP, 2007. Approximation-based control of nonlinear MIMO time-delay systems. Automatica, 43(1):31-43.
[6]Ge XH, Han QL, Zhong MY, et al., 2019. Distributed Krein space-based attack detection over sensor networks under deception attacks. Automatica, 109:108557.
[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]Guan YP, Ge XH, 2018. Distributed attack detection and secure estimation of networked cyber-physical systems against false data injection attacks and jamming attacks. IEEE Trans Signal Inform Process Netw, 4(1):48-59.
[10]Hu XY, Li YX, Tong SC, et al., 2023. Event-triggered adaptive fuzzy asymptotic tracking control of nonlinear pure-feedback systems with prescribed performance. IEEE Trans Cybern, 53(4):2380-2390.
[11]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.
[12]Kazemi Z, Safavi AA, Arefi MM, et al., 2022. Finite-time secure dynamic state estimation for cyber-physical systems under unknown inputs and sensor attacks. IEEE Trans Syst Man Cybern Syst, 52(8):4950-4959.
[13]Li M, Li S, Ahn CK, et al., 2022. Adaptive fuzzy eventtriggered command-filtered control for nonlinear timedelay systems. IEEE Trans Fuzzy Syst, 30(4):1025-1035.
[14]Li ZJ, Zhao J, 2021. Adaptive consensus of non-strict feedback switched multi-agent systems with input saturations. IEEE/CAA J Autom Sin, 8(11):1752-1761.
[15]Liu ZQ, Lou XY, Jia JJ, 2022. Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems. Front Inform Technol Electron Eng, 23(11):1684-1699.
[16]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.
[17]Samy SA, Ramachandran R, Anbalagan P, et al., 2023. Synchronization of nonlinear multi-agent systems using a non-fragile sampled data control approach and its application to circuit systems. Front Inform Technol Electron Eng, 24(4):553-566.
[18]Song S, Park JH, Zhang BY, et al., 2022a. Adaptive NN finite-time resilient control for nonlinear time-delay systems with unknown false data injection and actuator faults. IEEE Trans Neur Netw Learn Syst, 33(10):5416-5428.
[19]Song S, Park JH, Zhang BY, et al., 2022b. Event-based adaptive fuzzy fixed-time secure control for nonlinear CPSs against unknown false data injection and backlash-like hysteresis. IEEE Trans Fuzzy Syst, 30(6):1939-1951.
[20]Wang R, Li YH, Sun H, et al., 2021. Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network. Front Inform Technol Electron Eng, 22(1):51-67.
[21]Wang X, Zhou YH, Yang L, 2023. Event-triggered cooperative adaptive neural control for cyber-physical systems with unknown state time delays and deception attacks. IEEE Trans Syst Man Cybern Syst, 53(6):3540-3552.
[22]Wang YC, Qiu XJ, Zhang HG, et al., 2022. Data-drivenbased event-triggered control for nonlinear CPSs against jamming attacks. IEEE Trans Neur Netw Learn Syst, 33(7):3171-3177.
[23]Wang YN, Lin ZY, Liang X, et al., 2016. On modeling of electrical cyber physical systems considering cyber security. Front Inform Technol Electron Eng, 17(5):465-478.
[24]Wei Y, Luo J, Yan HC, et al., 2021. Event-triggered adaptive finite-time control for nonlinear systems under asymmetric time-varying state constraints. Front Inform Technol Electron Eng, 22(12):1610-1624.
[25]Xiao SY, Ge XH, Han QL, et al., 2022. Secure and collisionfree multi-platoon control of automated vehicles under data falsification attacks. Automatica, 145:110531.
[26]Xie ML, Ding DR, Ge XH, et al., 2023. Distributed platooning control of automated vehicles subject to replay attacks based on proportional integral observers. IEEE/CAA J Autom Sin, early access.
[27]Xu YG, Guo G, 2022. Event triggered control of connected vehicles under multiple cyber attacks. Inform Sci, 582:778-796.
[28]Yang D, Zong GD, Su SF, et al., 2022. Time-driven adaptive control of switched systems with application to electrohydraulic unit. IEEE Trans Cybern, 52(11):11906-11915.
[29]Yang SH, Tao G, Jiang B, et al., 2023. Modeling and adaptive control of air vehicles with partial nonlinear parametrization. Automatica, 149:110805.
[30]Zhang XM, Han QL, Ge XH, et al., 2020. Resilient control design based on a sampled-data model for a class of networked control systems under denial-of-service attacks. IEEE Trans Cybern, 50(8):3616-3626.
[31]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.
Open peer comments: Debate/Discuss/Question/Opinion
<1>