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Zhang, Wenbing; Wang, Zidong; Liu, Yurong; Ding, Derui; Alsaadi, Fuad E.

Sampled-data consensus of nonlinear multiagent systems subject to cyber attacks. (English) Zbl 1387.93028

Int. J. Robust Nonlinear Control 28, No. 1, 53-67 (2018).
Summary: This paper is concerned with the sampled-data consensus problem for a class of nonlinear multiagent systems subject to cyber attacks. The considered attacks are assumed to be recoverable, which destroy the connectivity of the network topology with directed spanning tree. In light of the designed sampled-data control protocol, a more general switched system is proposed to model both the cyber attacks and the sampled-data mechanism within a unified framework. Then, by using the contradiction methods, the solution of a class of differential equations is provided to deal with the technical challenge resulting from the switching and sampling issues. Furthermore, in terms of such a solution combined with the constructed piecewise Lyapunov function, sufficient conditions are derived under which the nonlinear multiagent systems subject to attacks achieve the consensus exponentially. The relationship between the attack frequency and the sampling period is also revealed through the obtained conditions. Finally, simulations are given to show the effectiveness of the proposed results.

Cited in 35 Documents

MSC:

93A14 Decentralized systems
93C57 Sampled-data control/observation systems
68T42 Agent technology and artificial intelligence
93C10 Nonlinear systems in control theory
93C15 Control/observation systems governed by ordinary differential equations

Keywords:

consensus; cyber attacks; multiagent systems; sampled data; switched systems
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References:

[1] RenW, MooreK, ChenY. High‐order consensus algorithms in cooperative vehicle systems. In Proceedings of the IEEE International Conference on Networking, Sensing and Control, Fort Lauderdale, U.S.A., 2006; 457‐462.
[2] AbdollahiF, KhorasaniK. A decentralized Markovian jump \(H_\infty\) control routing strategy for mobile multi‐agent networked systems. IEEE Trans Control Syst Technol March 2011; 19(2):269‐283.
[3] DingD, WangZ, ShenB. Event‐triggered distributed \(h_\infty\) state estimation with packet dropouts through sensor networks. IET Control Theory Appl2015; 9(13):1948‐1955.
[4] ShenB, WangZ, HungYS. Distributed \(h_\infty \)‐consensus filtering in sensor networks with multiple missing measurements: the finite‐horizon case. Automatica2010; 46:1682‐1688. · Zbl 1204.93122
[5] JiZ, WangZ, LinH, WangZ. Interconnection topologies for multi‐agent coordination under leader‐follower framework. Automatica2009; 45:2857‐2863. · Zbl 1192.93013
[6] Olfati‐SaberR, MurrayR. Consensus problems in networks of agents with switching topology and time‐delays. IEEE T Automat Contr2004; 49:1520‐1533. · Zbl 1365.93301
[7] TangY, GaoH, ZhangW, KurthsJ. Leader‐following consensus of a class of stochastic delayed multi‐agent systems with partial mixed impulses. Automatica2015; 53:346‐354. · Zbl 1371.93020
[8] GuanZ, LiuZ, FengG, JianM. Impulsive consensus algorithms for second‐order multi‐agent networks with sampled information. Automatica2012; 48:1397‐1404. · Zbl 1246.93007
[9] MunzU, PapachristodoulouA, AllgowerF. Consensus in multi‐agent systems with coupling delays and switching topology. IEEE T Automat Contr2011; 56:2976‐2982. · Zbl 1368.93010
[10] DingD, WangZ, ShenB. Event‐triggered consensus control for discrete‐time stochastic multi‐agent systems: the input‐to‐state stability in probability. Automatica2015; 62:284‐291. · Zbl 1330.93155
[11] GuoG, DingL, HanQ‐L. A distributed event‐triggered transmission strategy for sampled‐data consensus of multi‐agent systems. Automatica2014; 50:1489‐1496. · Zbl 1296.93108
[12] ZhangW‐A, DongH, GuoG, YuL. Distributed sampled‐data filtering for sensor networks with nonuniform sampling periods. IEEE T Ind Inform May 2014; 10(2):871‐881.
[13] ShenB, WangZ, LiuX. Sampled‐data synchronization control of dynamical networks with stochastic sampling. IEEE T Automat Contr2012; 57:2644‐2650. · Zbl 1369.93047
[14] ChengL, WangY, HouZ, TanM, CaoZ. Sampled‐data based average consensus of second‐order integral multi‐agent systems: switching topologies and communication noises. Automatica2013; 49:1458‐1464. · Zbl 1319.93050
[15] WangY, WangHO, XiaoJ, GuanZ. Synchronization of complex dynamical networks under recoverable attacks. Automatica2010; 46:197‐203. · Zbl 1214.93101
[16] ZhuM, MartínezS. Stackelberg game analysis of correlated attacks in cyber‐physical system. In Proc. American Control Conf., San Francisco, CA, USA; June 2011; 4063‐4068.
[17] MaranoS, MattaV, TongL. Distributed detection in the presence of byzantine attacks. IEEE T Signal Proces Jan. 2009; 57(1):16‐29. · Zbl 1391.94534
[18] ShangY. Couple‐group consensus of continuous‐time multi‐agent systems under Markovian switching topologies. J Franklin Inst2015; 352:4826‐4844. · Zbl 1395.93068
[19] ShangY. Consensus seeking over Markovian switching networks with time‐varying delays and uncertain topologies. Appl Math Comput2016; 273:1234‐1245. · Zbl 1410.93113
[20] ZhangW, TangY, MiaoQ, DuW. Exponential synchronization of coupled switched neural networks with mode‐dependent impulsive effects. IEEE Trans Neural Netw Learn Syst2013; 24:1316‐1326.
[21] ZhaoJ, HillDJ, LiuT. Synchronization of complex dynamical networks with switching topology: a switched system point of view. Automatica2009; 45:2502‐2511. · Zbl 1183.93032
[22] GaoY, WangL. Sampled‐data based consensus of continuous‐time multi‐agent systems with time‐varying topology. IEEE T Automat Contr2011; 56:1226‐1231. · Zbl 1368.93424
[23] MajdandzicA, PodobnikB, BuldyrevSV, KenettDY, HavlinS, StanleyHE. Spontaneous recovery in dynamical networks. Nat Phys2014; 10:34‐38.
[24] Di MuroMA, La RoccaCE, StanleyHE, HavlinS, BraunsteinLA. Recovery of interdependent networks. Sci Rep2016; 6:22834. https://doi.org/10.1038/srep22834 · doi:10.1038/srep22834
[25] ShangY. Localized recovery of complex networks against failure. Sci Rep2016; 6:30521. https://doi.org/10.1038/srep30521 · doi:10.1038/srep30521
[26] HespanhaJP, MorseAS. stability of switched systems with average dwell time. In 38th Proc IEEE Conf. Decision Control, vol. 3, 1999; 2655‐2660.
[27] WuCW, ChuaLO. Synchronization in an array of linearly coupled dynamical systems. IEEE T Circuits‐I1995; 42:430‐447. · Zbl 0867.93042
[28] ChenH, LiangJ, WangZ. Pinning controllability of autonomous Boolean control networks. Sci China Inform Sci July 2016; 59(7):070107:1‐070107:14. https://doi.org/10.1007/s11432-016-5579-8. · doi:10.1007/s11432-016-5579-8
[29] LiW, WeiG, HanF, LiuY. Weighted average consensus‐based unscented Kalman filtering. IEEE Trans Cybern2016; 46(2):558‐567.
[30] LiuD, LiuY, AlsaadiFE. A new framework for output feedback controller design for a class of discrete‐time stochastic nonlinear system with quantization and missing measurement. Int J Gen Syst2016; 45(5):517‐531. · Zbl 1342.93100
[31] LiuW, WangZ, LiuX, ZengN, LiuY, AlsaadiFE. A survey of deep neural network architectures and their applications. Neurocomputing April 2017; 234:11‐26.
[32] LiuY, LiuW, ObaidMA, AbbasIA. Exponential stability of Markovian jumping Cohen‐Grossberg neural networks with mixed mode‐dependent time‐delays. Neurocomputing2016; 177:409‐415.
[33] ZengN, WangZ, ZhangH. Inferring nonlinear lateral flow immunoassay state‐space models via an unscented Kalman filter. Sci China Inform Sci Nov. 2016; 59(11):112204:1‐112204:10. https://doi.org/10.1007/s11432-016-0280-9. · doi:10.1007/s11432-016-0280-9
[34] ZhangJ, MaL, LiuY. Passivity analysis for discrete‐time neural networks with mixed time‐delays and randomly occurring quantization effects. Neurocomputing2016; 216:657‐665.
[35] ZhangW, WangZ, LiuY, DingD, AlsaadiFE. Event‐based state estimation for a class of complex networks with time‐varying delays: a comparison principle approach. Phys Lett A2017; 381(1):10‐18.
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