CLC number: TP273
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2020-09-28
Cited: 0
Clicked: 5876
Citations: Bibtex RefMan EndNote GB/T7714
Xiang Hu, Zufan Zhang, Chuandong Li. Consensus of multi-agent systems with dynamic join characteristics under impulsive control[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(1): 120-133.
@article{title="Consensus of multi-agent systems with dynamic join characteristics under impulsive control",
author="Xiang Hu, Zufan Zhang, Chuandong Li",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="1",
pages="120-133",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000062"
}
%0 Journal Article
%T Consensus of multi-agent systems with dynamic join characteristics under impulsive control
%A Xiang Hu
%A Zufan Zhang
%A Chuandong Li
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 1
%P 120-133
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000062
TY - JOUR
T1 - Consensus of multi-agent systems with dynamic join characteristics under impulsive control
A1 - Xiang Hu
A1 - Zufan Zhang
A1 - Chuandong Li
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 1
SP - 120
EP - 133
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000062
Abstract: We study how to achieve the state consensus of a whole multi-agent system after adding some new agent groups dynamically in the original multi-agent system. We analyze the feasibility of dynamically adding agent groups under different forms of network topologies that are currently common, and obtain four feasible schemes in theory, including one scheme that is the best in actual industrial production. Then, we carry out dynamic modeling of multi-agent systems for the best scheme. Impulsive control theory and Lyapunov stability theory are used to analyze the conditions so that the whole multi-agent system with dynamic join characteristics can achieve state consensus. Finally, we provide a numerical example to verify the practicality and validity of the theory
[1]Cao YF, Sun YG, 2016. Consensus of third-order multiagent systems with time delay in undirected networks. Math Probl Eng, 2016:6803927.
[2]Cheng S, Dong H, Yu L, et al., 2019. Consensus of second-order multi-agent systems with directed networks using relative position measurements only. Int J Contr Autom Syst, 17(1):85-93.
[3]Geng HL, Duan GR, 2007. Stability of linear constant system with linear impulse. Chinese Control Conf, p.76-79.
[4]Han YY, Li CD, 2018. Second-order consensus of discrete-time multi-agent systems in directed networks with nonlinear dynamics via impulsive protocols. Neurocomputing, 286:51-57.
[5]Hao F, Chen X, 2012. Event-triggered average consensus control for discrete-time multi-agent systems. IET Contr Theory Appl, 6(16):2493-2498.
[6]Hu W, Zhu QX, 2018. Moment exponential stability of stochastic nonlinear delay systems with impulse effects at random times. Int J Rob Nonl Contr, 29(12):3809-3820.
[7]Huang C, Zhang X, Lam H, et al., 2020. Synchronization analysis for nonlinear complex networks with reaction-diffusion terms using fuzzy-model-based approach. IEEE Trans Fuzzy Syst, in press.
[8]Huang J, Cao M, Zhou N, et al., 2017. Distributed behavioral control for second-order nonlinear multi-agent systems. IFAC-PapersOnLine, 50(1):2445-2450.
[9]Huang TW, Li CD, Duan SK, et al., 2012. Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects. IEEE Trans Neur Netw Learn Syst, 23(6):866-875.
[10]Jiang FC, Wang L, Xie GM, 2010. Consensus of high-order dynamic multi-agent systems with switching topology and time-varying delays. J Contr Theory Appl, 8(1):52-60.
[11]Lee K, Bhattacharya R, 2016. Convergence analysis of asynchronous consensus in discrete-time multi-agent systems with fixed topology. https://arxiv.org/abs/1606.04156.
[12]Li CJ, Liu GP, 2018a. Consensus for heterogeneous networked multi-agent systems with switching topology and time-varying delays. J Franklin Inst, 355(10):4198-4217.
[13]Li CJ, Liu GP, 2018b. Data-driven leader-follower output synchronization for networked non-linear multi-agent systems with switching topology and time-varying delays. J Syst Sci Compl, 31(1):87-102.
[14]Li XD, Zhang XL, Song SJ, 2017. Effect of delayed impulses on input-to-state stability of nonlinear systems. Automatica, 76:378-382.
[15]Li YL, Li HT, Ding XY, et al., 2019. Leader-follower consensus of multiagent systems with time delays over finite fields. IEEE Trans Cybern, 49(8):3203-3208.
[16]Li YM, Sun YY, Hua J, et al., 2015. Indirect adaptive type-2 fuzzy impulsive control of nonlinear systems. IEEE Trans Fuzzy Syst, 23(4):1084-1099.
[17]Liu XL, Xiao JW, Chen DX, et al., 2019. Dynamic consensus of nonlinear time-delay multi-agent systems with input saturation: an impulsive control algorithm. Nonl Dynam, 97(2):1699-1710.
[18]Lu ZH, Zhang L, Wang L, 2019. Controllability analysis of multi-agent systems with switching topology over finite fields. Sci China Inform Sci, 62(1):12201.
[19]Luo J, Cao CY, 2015. Flocking for multi-agent systems with unknown nonlinear time-varying uncertainties under a fixed undirected graph. Int J Contr, 88(5):1051-1062.
[20]Schoukens J, Godfrey K, Schoukens M, 2018. Nonparametric data-driven modeling of linear systems: estimating the frequency response and impulse response function. IEEE Contr Syst Mag, 38(4):49-88.
[21]Sesekin AN, Nepp AN, 2015. Impulse position control algorithms for nonlinear systems. 41st Int Conf on Applications of Mathematics in Engineering and Economics, p.040002-1-040002-5.
[22]Shahrrava B, 2018. Closed-form impulse responses of linear time-invariant systems: a unifying approach [lecture notes]. IEEE Signal Process Mag, 35(4):126-132.
[23]Shang YL, 2012. Finite-time consensus for multi-agent systems with fixed topologies. Int J Syst Sci, 43(3):499-506.
[24]Shi M, Yu YJ, Xu Q, 2019. Delay-dependent consensus condition for a class of fractional-order linear multi-agent systems with input time-delay. Int J Syst Sci, 50(4):669-678.
[25]Wang AJ, Liao XF, He HB, 2019. Event-triggered differentially private average consensus for multi-agent network. IEEE/CAA J Autom Sin, 6(1):75-83.
[26]Wang H, Yu WW, Wen GH, et al., 2018. Finite-time bipartite consensus for multi-agent systems on directed signed networks. IEEE Trans Circ Syst I, 65(12):4336-4348.
[27]Wang H, Yu WW, Ren W, et al., 2019. Distributed adaptive finite-time consensus for second-order multiagent systems with mismatched disturbances under directed networks. IEEE Trans Cybern, in press.
[28]Wang JR, Luo ZJ, Shen D, 2018. Iterative learning control for linear delay systems with deterministic and random impulses. J Franklin Inst, 355(5):2473-2497.
[29]Wang S, Xie D, 2012. Consensus of second-order multi-agent systems via sampled control: undirected fixed topology case. IET Contr Theory Appl, 6(7):893-899.
[30]Wang X, Li CD, Huang TW, et al., 2014. Impulsive control and synchronization of nonlinear system with impulse time window. Nonl Dynam, 78(4):2837-2845.
[31]Wang XM, Wang T, Xu CB, et al., 2018. Average consensus for multi-agent system with measurement noise and binary-valued communication. Asian J Contr, 21(3):1043-1056.
[32]Wang YQ, Lu JQ, Lou YJ, 2019. Halanay-type inequality with delayed impulses and its applications. Sci China Inf Sci, 62(9):192206.
[33]Wang ZM, Zhang H, Wang WS, 2016. Robust consensus for linear multi-agent systems with noises. IET Contr Theory Appl, 10(17):2348-2356.
[34]Wen GG, Zhang YL, Peng ZX, et al., 2019. Observer-based output consensus of leader-following fractional-order heterogeneous nonlinear multi-agent systems. Int J Contr, in press.
[35]Wen GH, Zheng WX, 2019. On constructing multiple Lyapunov functions for tracking control of multiple agents with switching topologies. IEEE Trans Autom Contr, 64(9):3796-3803.
[36]Wu T, Hu J, Chen DY, 2019. Non-fragile consensus control for nonlinear multi-agent systems with uniform quantizations and deception attacks via output feedback approach. Nonl Dynam, 96(1):243-255.
[37]Xie DM, Wang SK, 2012. Consensus of second-order discrete-time multi-agent systems with fixed topology. J Math Anal Appl, 387(1):8-16.
[38]Xu Y, Luo DL, Li DY, et al., 2019. Affine formation control for heterogeneous multi-agent systems with directed interaction networks. Neurocomputing, 330(22):104-115.
[39]Ye YY, Su HS, 2019. Leader-following consensus of nonlinear fractional-order multi-agent systems over directed networks. Nonl Dynam, 96(2):1391-1403.
[40]Yuan S, Cheng Z, Lei G, 2018. Uncoupled PID control of coupled multi-agent nonlinear uncertain systems. J Syst Sci Compl, 31(1):4-21.
[41]Zhai SD, Yang XS, 2014. Consensus of second-order multi-agent systems with nonlinear dynamics and switching topology. Nonl Dynam, 77(4):1667-1675.
[42]Zhang WB, Ho DWC, Tang Y, et al., 2019. Quasi-consensus of heterogeneous-switched nonlinear multiagent systems. IEEE Trans Cybern, in press.
[43]Zhang Y, Tian YP, 2014. Allowable delay bound for consensus of linear multi-agent systems with communication delay. Int J Syst Sci, 45(10):2172-2181.
[44]Zheng M, Liu CL, Liu F, 2019. Average-consensus tracking of sensor network via distributed coordination control of heterogeneous multi-agent systems. IEEE Contr Syst Lett, 3(1):132-137.
[45]Zhou B, Liao XF, 2014. Leader-following second-order consensus in multi-agent systems with sampled data via pinning control. Nonl Dynam, 78(1):555-569.
[46]Zhu W, Wang DD, Zhou QH, 2019. Leader-following consensus of multi-agent systems via adaptive event-based control. J Syst Sci Compl, 32(3):846-856.
[47]Zou WC, Xiang ZR, Ahn CK, 2019. Mean square leader-following consensus of second-order nonlinear multiagent systems with noises and unmodeled dynamics. IEEE Trans Syst Man Cybern Syst, 49(12):2478-2486.
Open peer comments: Debate/Discuss/Question/Opinion
<1>