Cited By
View all- Tang WMo HWu JXia Y(2023)Neural network‐based event‐triggered cluster quasi‐consensus for unknown multiagent systems with directed topologyAsian Journal of Control10.1002/asjc.299325:4(2838-2852)Online publication date: 2-Jul-2023
New methods to realize the cluster consensus for multi‐agent networks
Abstract
This paper investigates the cluster consensus problem for multi‐agent networks via a new method. Firstly, a distributed cluster consensus protocol is proposed by constructing a new Laplacian matrix, which is not required to be row‐zero‐sum. It is shown that the cluster consensus of directed multi‐agent networks can be achieved under the presented protocol, and the final cluster consensus values of the considered system are also given in this paper, which only depend on the initial states of all agents. Next, a pinning cluster consensus law is provided to force the dynamics of the agents to the desired trajectory. Furthermore, it is found that the cluster consensus of directed networks can be reached even in presence of arbitrary finite communication delays. Finally, effectiveness of the obtained results is demonstrated by numerical examples.
References
[1]
K. Fregene, Unmanned aerial vehicles and control: Lockheed Martin Advanced Technology Laboratories, IEEE Control Syst. Mag. 32 (2012), 32–34.
[2]
R. Olfati‐Saber, Flocking for multi‐agent dynamic systems: Algorithms and theory, IEEE Trans. Autom. Control 51 (2006), 401–420.
[3]
J. Zhu, J. Lü, and X. Yu, Flocking of multi‐agent non‐holonomic systems with proximity graphs, IEEE Trans. Circuits Syst. I‐Regul. Pap. 60 (2013), 199–210.
[4]
J. R. Wertz and G. Gurevich, Applications of autonomous on‐board orbit control, Adv. Astronaut. Sci. 108 (2001), 1911–1925.
[5]
L. Ma et al., Consensus control of stochastic multi‐agent systems: A survey, Sci. China‐Inf. Sci. 60 (2017), 120201.
[6]
S.‐L. Du et al., Sampled‐data‐based consensus and L2‐gain analysis for heterogeneous multiagent systems, IEEE T. Cybern. 47 (2017), 1523–1531.
[7]
S.‐L. Du et al., Pursuing an evader through cooperative relaying in multi‐agent surveillance networks, Automatica 83 (2017), 155–161.
[8]
M. Park et al., Closed‐centrality‐based synchronization criteria for complex dynamical networks with interval time‐varying coupling delays, IEEE T. Cybern. 48 (2018), 2192–2202.
[9]
M.‐J. Park et al., Betweenness centrality‐based consensus protocol for second‐order multiagent systems with sampled‐data, IEEE T. Cybern. 47 (2017), 2067–2078.
[10]
M.‐J. Park, O.‐M. Kwon, and A. Seuret, Weighted consensus protocols design based on network centrality for multi‐agent systems with sampled‐data, IEEE Trans. Autom. Control 62 (2017), 2916–2922.
[11]
M. Pirani, E. M. Shahrivar, and S. Sundaram, Coherence and convergence rate in networked dynamical systems, IEEE 54th Ann. Conf. Decision and Control, Osaka, Japan, 2015, pp. 968–973.
[12]
J. Hofbauer and J. W.‐H. So, Diagonal dominance and harmless off‐diagonal delays, Proc. Am. Math. Soc. 128 (2000), 2675–2682.
[13]
J. V. Walle et al., Practical consensus guidelines for the management of enuresis, Eur. J. Pediatr. 171 (2012), 971–983.
[14]
M. Huang and J. H. Manton, Stochastic consensus seeking with noisy and directed inter‐agent communication: Fixed and randomly varying topologies, IEEE Trans. Autom. Control 55 (2010), 235–241.
[15]
D. W. Casbeer, R. Beard, and A. L. Swindlehurst, Discrete double integrator consensus, Proc. 47th IEEE Conf. Decis. Control, Cancun, Mexico, 2008, pp. 2264–2269.
[16]
L. Wang and X. Feng, Finite‐time consensus problems for networks of dynamic agents, IEEE Trans. Autom. Control 55 (2010), 950–955.
[17]
Y. Shang, Finite‐time cluster average consensus for networks via distributed iterations, Int. J. Control Autom. Syst. 15 (2017), 933–938.
[18]
X. Wan et al., Finite‐time H∞ state estimation for discrete time‐delayed genetic regulatory networks under stochastic communication protocols, IEEE Trans. Circuits Syst. I‐Regul. Pap. 65 (2018), 3481–3491.
[19]
S. E. Parsegov, A. E. Polyakov, and P. S. Shcherbakov, Fixed‐time consensus algorithm for multi‐agent systems with integrator dynamics, 4th IFAC Workshop Distributed Estimation and Control in Networked Systems, Koblenz, Germany, 2013, pp. 110–115.
[20]
S. Roy, Scaled consensus, Automatica 51 (2015), 259–262.
[21]
W. Wu, W. Zhou, and T. Chen, Cluster synchronization of linearly coupled complex networks under pinning control, IEEE Trans. Circuits Syst. I‐Regul. Pap. 56 (2009), 829–839.
[22]
Z. Wang and H. Li, Cluster consensus in multiple Lagrangian systems under pinning control, IEEE Access 5 (2017), 11291–11297.
[23]
X. Guo, J. Liang, and J. Lu, Asymmetric bipartite consensus over directed networks with antagonistic interactions, IET Contr. Theory Appl. 12 (2018), 2295–2301.
[24]
D. Liu, A. Hu, and D. Zhao, Distributed consensus of multi‐agent networks via event‐triggered pinning control, Asian J. Control 19 (2017), 614–624.
[25]
S. Yang et al., Consensus of delayed multi‐agent systems via intermittent impulsive control, Asian J. Control 19 (2017), 941–950.
[26]
L. Wang et al., Observer‐based consensus control for discrete‐time multiagent systems with coding‐decoding communication protocol, 2018. https://doi.org/10.1109/TCYB.2018.2863664
[27]
D. Zhang et al., Pinning consensus analysis for nonlinear second‐order multi‐agent systems with time‐varying delays, Asian J. Control 20 (2018), 2343–2350.
[28]
S. Wang, Y. Jiang, and Y. Li, Distributed H∞ consensus fault detection for uncertain T‐S fuzzy systems with time‐varying delays over lossy sensor networks, Asian J. Control 20 (2018), 2171–2184.
[29]
A. Hu, M. Hu, and L. Guo, Event‐triggered control for cluster consensus in multi‐agent networks, Asian J. Control 18 (2016), 1836–1844.
[30]
X. Liu, T. Chen, and W. Lu, Cluster synchronization for linearly coupled complex networks, J. Ind. Manag. Optim. 7 (2011), 87–101.
[31]
X. Liu and T. Chen, Finite‐time and fixed‐time cluster synchronization with or without pinning control, IEEE T. Cybern. 48 (2018), 240–252.
[32]
Z. Ma, Z. Liu, and G. Zhang, A new method to realize cluster synchronization in connected chaotic networks, Chaos 16 (2006), 23103.
[33]
W. Xu and D. W. C. Ho, Clustered event‐triggered consensus analysis: An impulsive framework, IEEE Trans. Ind. Electron. 63 (2016), 7133–7143.
[34]
J. Zhan and X. Li, Cluster consensus in networks of agents with weighted cooperative–competitive interactions, IEEE Trans. Circuits Syst. II‐Express Briefs 65 (2018), 241–245.
[35]
J.‐W. Yi, Y.‐W. Wang, and J.‐W. Xiao, Reaching cluster consensus in multi‐agent systems, 2nd Int. Conf. Intell. Control Inform. Process., Harbin, China, 2011, pp. 569–573.
[36]
X.‐Q. Lu, F. Austin, and S.‐H. Chen, Cluster consensus of second‐order multi‐agent systems via pinning control, Chin. Phys. B 19 (2010), 120506.
[37]
Y. Han, W. Lu, and T. Chen, Achieving cluster consensus in continuous‐time networks of multi‐agents with inter‐cluster non‐identical inputs, IEEE Trans. Autom. Control 60 (2015), 793–798.
[38]
J. Qin and C. Yu, Cluster consensus control of generic linear multi‐agent systems under directed topology with acyclic partition, Automatica 49 (2013), 2898–2905.
[39]
W. Ren and R. W. Beard, Consensus seeking in multiagent systems under dynamically changing interaction topologies, IEEE Trans. Autom. Control 50 (2005), 655–661.
[40]
J Qin et al., Robust H∞ group consensus for interacting clusters of integrator agents, IEEE Trans. Autom. Control 62 (2017), 3559–3566.
[41]
C. Altafini, Consensus problems on networks with antagonistic interactions, IEEE Trans. Autom. Control 58 (2013), 935–946.
[42]
C. Ma, W. Zhao, and Y.‐B. Zhao, Bipartite linear χ‐consensus of double‐integrator multi‐agent systems with measurement noise, Asian J. Control 20 (2018), 577–584.
[43]
R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, England, 1990.
[44]
R. Olfati‐Saber and R. M. Murray, Consensus problems in networks of agents with switching topology and time‐delays, IEEE Trans. Autom. Control 49 (2004), 1520–1533.
[45]
J. Lu, D. W. C. Ho, and J. Kurths, Consensus over directed static networks with arbitrary finite communication delays, Phys. Rev. E 80 (2009), 66121.
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© 2019 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd.
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John Wiley & Sons, Inc.
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Publication History
Published: 01 December 2020
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View all- Tang WMo HWu JXia Y(2023)Neural network‐based event‐triggered cluster quasi‐consensus for unknown multiagent systems with directed topologyAsian Journal of Control10.1002/asjc.299325:4(2838-2852)Online publication date: 2-Jul-2023
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