Event-triggered impulsive control for second-order nonlinear multi-agent systems under DoS attacks

Qiushi Wang; Hongwei Ren; Zhiping Peng; Qiushi Wang; Hongwei Ren; Zhiping Peng

doi:10.3934/math.2024680

AIMS Mathematics

2024, Volume 9, Issue 6: 13998-14011. doi: 10.3934/math.2024680

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Research article

Event-triggered impulsive control for second-order nonlinear multi-agent systems under DoS attacks

1.
School of Automation, Guangdong University of Petrochemical Technology, MaoMing, GuangDong, China
2.
School of Information and Control Engineering, Jilin Institute of Chemical Technology, JiLin, China

Received: 31 December 2023 Revised: 20 March 2024 Accepted: 29 March 2024 Published: 16 April 2024
MSC : 93C10, 93C27, 93D05, 93D50

We investigated impulsive consensus in second-order nonlinear multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. We consided scenarios where the communication network is subjected to DoS attacks, disrupting communication links and causing changes in the communication topology. An event-triggered impulsive control(ETIC) approach is proposed to flexibly address these issues. Additionally, an upper bound on the DoS attack period is introduced. Finally, a numerical example is given to verify the validity of the major results.
- DoS attack,
- event-triggered impulsive control,
- nonlinear multi-agent systems
Citation: Qiushi Wang, Hongwei Ren, Zhiping Peng. Event-triggered impulsive control for second-order nonlinear multi-agent systems under DoS attacks[J]. AIMS Mathematics, 2024, 9(6): 13998-14011. doi: 10.3934/math.2024680

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Abstract

We investigated impulsive consensus in second-order nonlinear multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. We consided scenarios where the communication network is subjected to DoS attacks, disrupting communication links and causing changes in the communication topology. An event-triggered impulsive control(ETIC) approach is proposed to flexibly address these issues. Additionally, an upper bound on the DoS attack period is introduced. Finally, a numerical example is given to verify the validity of the major results.

References

[1]	X. L. Wang, Y. G. Hong, J. Huang, Z. P. Jiang, A distributed control approach to a robust output regulation problem for multi-Agent linear systems, IEEE T. Automat. Contr., 55 (2010), 2891–2895. https://doi.org/10.1109/TAC.2010.2076250 doi: 10.1109/TAC.2010.2076250
[2]	A. Maidi, J. P. Corriou, Distributed control of nonlinear diffusion systems by input-output linearization, Int. J. Robust Nonlin. Contr., 24 (2014), 389–405. https://doi.org/10.1002/rnc.2892 doi: 10.1002/rnc.2892
[3]	Z. N. Zhang, Y. G. Niu, H. J. Zhao, Secure sliding mode control of interval type-2 fuzzy systems against intermittent denial-of-service attacks, Int. J. Robust Nonlin. Contr., 31 (2021), 1866–1884. https://doi.org/10.1002/rnc.5219 doi: 10.1002/rnc.5219
[4]	W. C. Cai, X. H. Liao, Y. D. Song, Indirect robust adaptive fault-tolerant control for attitude tracking of spacecraft, J. Guid. Control Dynam., 31 (2008), 1456–1463. https://doi.org/10.2514/1.31158 doi: 10.2514/1.31158
[5]	Y. J. Liu, X. Y. Zhao, J. H. Park, F. Fang, Fault-tolerant control for T-S fuzzy systems with an aperiodic adaptive event-triggered sampling, Fuzzy Set. Syst., 452 (2023), 23–41. https://doi.org/10.1016/j.fss.2022.04.019 doi: 10.1016/j.fss.2022.04.019
[6]	T. Yang, L. O. Chua, Impulsive control and synchronization of nonlinear dynamical systems and application to secure communication, Int. J. Bifurcat. Chaos, 7 (1997), 645–664. https://doi.org/10.1142/S0218127497000443 doi: 10.1142/S0218127497000443
[7]	H. G. Zhang, J. Fu, T. D. Ma, S. C. Tong, An improved impulsive control approach to nonlinear systems with time-varying delays, Chinese Phys. B, 18 (2009), 969–974. https://doi.org/10.1088/1674-1056/18/3/021 doi: 10.1088/1674-1056/18/3/021
[8]	Y. Chen, W. W. Yu, F. F. Li, S. S. Feng, Synchronization of complex networks with impulsive control and disconnected topology, IEEE T. Circuits-II, 60 (2013), 292–296. https://doi.org/10.1109/TCSII.2013.2251961 doi: 10.1109/TCSII.2013.2251961
[9]	X. Y. Zhang, C. D. Li, H. F. Li, Finite-time stabilization of nonlinear systems via impulsive control with state-dependent delay, J. Franklin I., 359 (2022), 1196–1214. https://doi.org/10.1016/j.jfranklin.2021.11.013 doi: 10.1016/j.jfranklin.2021.11.013
[10]	W. L. He, F. Qian, J. Lam, G. R. Chen, Q. L. Han, J. Kurths, Quasi synchronization of heterogeneous dynamic networks via distributed impulsive control: Error estimation, optimization and design, Automatica, 62 (2015), 249–262. https://doi.org/10.1016/j.automatica.2015.09.028 doi: 10.1016/j.automatica.2015.09.028
[11]	S. M. Chu, W. L. He, Q. L. Han, F. Qian, Pinning synchronization of delayed dynamical networks via impulsive control, IEEE, 2014,544–549. https://doi.org/10.1109/ICMC.2014.7231615 doi: 10.1109/ICMC.2014.7231615
[12]	W. L. He, G. R. Chen, Q. L. Han, F. Qian, Network-based leaderfollowing consensus of nonlinear multi-agent systems via distributed impulsive control, Inform. Sci., 380 (2017), 145–158. https://doi.org/10.1016/j.ins.2015.06.005 doi: 10.1016/j.ins.2015.06.005
[13]	C. Ke, C. D. Li, L. You, Consensus of nonlinear multi-agent systems with grouping via state-constraint impulsive protocols, IEEE T. Cybernetics, 51 (2021), 4162–4172. https://doi.org/10.1109/TCYB.2019.2953566 doi: 10.1109/TCYB.2019.2953566
[14]	S. S. Yang, X. F. Liao, Y. B. Liu, Second-order consensus in directed networks of identical nonlinear dynamics via impulsive control, Neurocomputing, 179 (2016), 290–297. https://doi.org/10.1016/j.neucom.2015.11.088 doi: 10.1016/j.neucom.2015.11.088
[15]	T. D. Ma, Z. L. Zhang, B. Cui, Impulsive consensus of nonlinear fuzzy multi-agent systems under DoS attack, Nonlinear Anal. Hybri., 44 (2022), 101155. https://doi.org/10.1016/j.nahs.2022.101155 doi: 10.1016/j.nahs.2022.101155
[16]	X. G. Tan, J. D. Cao, X. D. Li, Consensus of leader-following multiagent systems: A distributed event-triggered impulsive control strategy, IEEE T. Cybernetics, 49 (2019), 792–801. https://doi.org/10.1109/TCYB.2017.2786474 doi: 10.1109/TCYB.2017.2786474
[17]	X. D. Li, D. X. Peng, J. D, Cao, Lyapunov stability for impulsive systems via event-triggered impulsive control, IEEE T. Automat. Contr., 65 (2020), 4908–4913. https://doi.org/10.1109/TAC.2020.2964558 doi: 10.1109/TAC.2020.2964558
[18]	W. Y. Tang, K. Li, J. Wu, Y. F. Xie, Consensus of nonlinear multi-agent systems with distributed event-triggered impulsive control, J. Vib. Control, 28 (2022), 882–891. https://doi.org/10.1177/1077546320985978 doi: 10.1177/1077546320985978
[19]	H. H. Guo, J. Liu, C. K. Ahn, Y. B. Wu, W. X. Li, Dynamic event-triggered impulsive control for stochastic nonlinear systems with extension in complex networks, IEEE T. Circuits-II, 69 (2022), 2167–2178. https://doi.org/10.1109/TCSI.2022.3141583 doi: 10.1109/TCSI.2022.3141583
[20]	L. Chen, H. G. Liang, Y. N. Pan, T. S. Li, Human-in-the-loop consensus tracking control for UAV systems via an improved prescribed performance approach, IEEE T. Aero. Elec. Sys., 59 (2023), 8380–8391. https://doi.org/10.1109/TAES.2023.3304283 doi: 10.1109/TAES.2023.3304283
[21]	M. Wang, H. G. Liang, Y. N. Pan, X. P. Xie, A new privacy preservation mechanism and a gain iterative disturbance observer for multiagent systems, IEEE T. Netw. Sci. Eng., 11 (2024), 392–403. https://doi.org/10.1109/TNSE.2023.3299614 doi: 10.1109/TNSE.2023.3299614
[22]	Y. N. Pan, W. Y. Ji, H. K. Lam, L. Cao, An improved predefined-time adaptive neural control approach for nonlinear multiagent systems, IEEE T. Autom. Sci. Eng., 2023. https://doi.org/10.1109/TASE.2023.3324397 doi: 10.1109/TASE.2023.3324397
[23]	A. Parivallal, R. Sakthivel, F. Alzahrani, A. Leelamani, Quantized guaranteed cost memory consensus for nonlinear multi-agent systems with switching topology and actuator faults, Physica A, 539 (2020), 122946. https://doi.org/10.1016/j.physa.2019.122946 doi: 10.1016/j.physa.2019.122946
[24]	S. Han, S. K. Kommuri, S. Lee, Affine transformed it2 fuzzy event-triggered control under deception attacks, IEEE T. Fuzzy Syst., 29 (2021), 322–335. https://doi.org/10.1109/TFUZZ.2020.2999779 doi: 10.1109/TFUZZ.2020.2999779
[25]	D. R. Ding, Z. D. Wang, D. N. C. Ho, G. L. Wei, Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks, Automatica, 78 (2017), 231–240. https://doi.org/10.1016/j.automatica.2016.12.026 doi: 10.1016/j.automatica.2016.12.026
[26]	J. Cao, D. Ding, J. L. Liu, E. G. Tian, S. L. Hu, X. P. Xie, Hybridtriggered-based security controller design for networked control system under multiple cyber attacks, Inform. Sci., 548 (2021), 69–84. https://doi.org/10.1016/j.ins.2020.09.046 doi: 10.1016/j.ins.2020.09.046
[27]	X. L. Chen, Y. G. Wang, S. L. Hu, Event-based robust stabilization of uncertain networked control systems under quantization and denial-of-service attacks, Inform. Sci., 459 (2018), 369–386. https://doi.org/10.1016/j.ins.2018.05.019 doi: 10.1016/j.ins.2018.05.019
[28]	Y. T. Wang, W. L. He, Impulsive consensus of leader-following nonlinear multi-agent systems under DoS attacks, IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society, 2019, 6274–6279. https://doi.org/10.1109/IECON.2019.8927636 doi: 10.1109/IECON.2019.8927636
[29]	J. H. Qin, M. L. Li, L. Shi, X. H. Yu, Optimal denial-ofservice attack scheduling with energy constraint over packet-dropping networks, IEEE T. Automat. Contr., 63 (2018), 1648–1663. https://doi.org/10.1109/TAC.2017.2756259 doi: 10.1109/TAC.2017.2756259
[30]	Z. Feng, G. Q. Hu, Secure cooperative event-triggered control of linear multi-agent systems under DoS attacks, IEEE T. Contr. Syst. T., 28 (2020), 741–752. https://doi.org/10.1109/TCST.2019.2892032 doi: 10.1109/TCST.2019.2892032
[31]	H. Liu, Event-triggering-based leader-following bounded consensus of multi-agent systems under DoS attacks, Commun. Nonlinear Sci., 89 (2020), 105342. https://doi.org/10.1016/j.cnsns.2020.105342 doi: 10.1016/j.cnsns.2020.105342
[32]	L. Zhao, G. H. Yang, Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks, Inform. Sci., 526 (2020), 39–53. https://doi.org/10.1016/j.ins.2020.03.083 doi: 10.1016/j.ins.2020.03.083
[33]	D. Ye, Y. Y. Shao, Quasi-synchronization of heterogeneous nonlinear multi-agent systems subject to DoS attacks with impulsive effects, Neurocomputing, 366 (2019), 131–139. https://doi.org/10.1016/j.neucom.2019.07.095 doi: 10.1016/j.neucom.2019.07.095
[34]	Y. C. Sun, G. H. Yang, Event-triggered distributed state estimation for multiagent systems under DoS attacks, IEEE T. Cybernetics, 52 (2020), 6901–6910. https://doi.org/10.1109/TCYB.2020.3034456 doi: 10.1109/TCYB.2020.3034456
[35]	M. A. Shayman, Geometry of the algebraic Riccati equation, Part Ⅰ, SIAM J. Control Optim., 21 (1983), 375–394. https://doi.org/10.1137/0321021 doi: 10.1137/0321021
[36]	Z. D. Ai, L. H. Peng, G. D. Zong, K. B. Shi, Impulsive control for nonlinear systems under DoS attacks: A dynamic event-triggered method, IEEE T. Circuits-II, 69 (2022), 3839–3843. https://doi.org/10.1109/TCSII.2022.3170592 doi: 10.1109/TCSII.2022.3170592

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