Robust flocking for non-identical second-order nonlinear multi-agent systems

Xiuxian Li, Housheng Su, Li Li

Autonomous Intelligent Systems ›› 2021, Vol. 1 ›› Issue (1) : 7. DOI: 10.1007/s43684-021-00007-x
Original Article

Robust flocking for non-identical second-order nonlinear multi-agent systems

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Abstract

This paper investigates the robust flocking problem for second-order nonlinear systems with a leader and external disturbances. In contrast with most of second-order systems in the literature, the intrinsic dynamics here are nonlinear and non-identical that depend not only on the velocity but also on the position, which is more realistic. Moreover, the interaction topology is undirected and switching. Provided that the leader’s velocity may be constant or time-varying, two distributed flocking control laws have been proposed for two cases to make the differences of the velocities between all followers and the leader approach to zero asymptotically. The proposed distributed flocking control laws are both model-independent which results in the effectiveness of the controllers to cope with the different intrinsic dynamics of the followers and the leader under some assumptions on boundedness of several states. An example is given to illustrate the validity of the theoretical results.

Keywords

Flocking / Multi-agent systems / Second-order nonlinear systems / Non-identical dynamics

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Xiuxian Li, Housheng Su, Li Li. Robust flocking for non-identical second-order nonlinear multi-agent systems. Autonomous Intelligent Systems, 2021, 1(1): 7 https://doi.org/10.1007/s43684-021-00007-x

References

[1]
Olfati-SaberR.. Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Trans. Autom. Control, 2006, 51: 401-420
CrossRef Google scholar
[2]
SuH., ZhangN., ChenM. Z. Q., WangH., WangX.. Adaptive flocking with a virtual leader of multiple agents governed by locally Lipschitz nonlinearity. Nonlinear Anal. Real World Appl., 2013, 14: 798-806
CrossRef Google scholar
[3]
ChandraJ., LaddeG. S.. Collective behavior of multi-agent network dynamic systems under internal and external random perturbations. Nonlinear Anal. Real World Appl., 2010, 11: 1330-1344
CrossRef Google scholar
[4]
LiuH., WangX., LiX., LiuY.. Finite-time flocking and collision avoidance for second-order multi-agent systems. Int. J. Syst. Sci., 2020, 51: 102-115
CrossRef Google scholar
[5]
LiuC., WangM., ZengQ., HuangfuW.. Leader-following flocking for unmanned aerial vehicle swarm with distributed topology control. Sci. China Inf. Sci., 2020, 63: 140312
CrossRef Google scholar
[6]
LiX., SuH., ChenM. Z. Q.. Flocking of networked Euler–Lagrange systems with uncertain parameters and time-delays under directed graphs. Nonlinear Dyn., 2016, 85: 415-424
CrossRef Google scholar
[7]
W. Ren, R. W. Beard, Formation feedback control for multiple spacecraft via virtual structures (IEE Proceedings - Control Theory and Applications, 2004).
[8]
LiX., XieL.. Dynamic formation control over directed networks using graphical Laplacian approach. IEEE Trans. Autom. Control, 2018, 63: 3761-3774
CrossRef Google scholar
[9]
Z. Yang, C. Chen, S. Zhu, X. Guan, G. Feng, Distributed entrapping control of multi-agent systems using bearing measurements. IEEE Trans. Autom. Control, in press (2020).
[10]
ZhangD., TangY., ZhangW., WuX.. Hierarchical design for position-based formation control of rotorcraft-like aerial vehicles. IEEE Trans. Control Netw. Syst., 2020, 7: 1789-1800
CrossRef Google scholar
[11]
LuJ., CaoJ.. Adaptive synchronization in tree-like dynamical networks. Nonlinear Anal. Real World Appl., 2007, 8: 1252-1260
CrossRef Google scholar
[12]
Olfati-SaberR., FaxJ. A., MurrayR. M.. Consensus and cooperation in networked multi-agent systems. Proc. IEEE, 2007, 97: 215-233
CrossRef Google scholar
[13]
SuH., ChenM. Z. Q., WangX., LamJ.. Semi-global observer-based leader-following consensus with input saturation. IEEE Trans. Ind. Electron., 2014, 61: 2842-2850
CrossRef Google scholar
[14]
LiZ., RenW., LiuX., FuM.. Consensus of multi-agent systems with general linear and Lipschitz nonlinear dynamics using distributed adaptive protocols. IEEE Trans. Autom. Control, 2013, 58: 1786-1791
CrossRef Google scholar
[15]
SuH., ChenM. Z. Q., ChenG.. Robust semi-global coordinated tracking of linear multi-agent systems with input saturation. Int. J. Robust Nonlinear Control, 2014, 25: 2375-2390
CrossRef Google scholar
[16]
JadbabaieA., LinJ., MorseA.. Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Trans. Autom. Control, 2003, 48: 988-1001
CrossRef Google scholar
[17]
YuW., ChenG., CaoM., KruthsJ.. Second-order consensus for multi-agent systems with directed topologies and nonlinear dynamics, IEEE Transactions on Systems, Man, and Cybernetics. B: Cybern., 2010, 40: 881-891
[18]
SuH., WangX., ChenG.. Rendezvous of multiple mobile agents with preserved network connectivity. Syst. Control Lett., 2010, 59: 313-322
CrossRef Google scholar
[19]
C. W. Reynolds, in Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques. Flocks, herds and schools: a distributed behavioral model, (1987), pp. 25–34.
[20]
SuH., WangX., LinZ.. Flocking of multi-agents with a virtual leader. IEEE Trans. Autom. Control, 2009, 54: 293-307
CrossRef Google scholar
[21]
LuoX., LiS., GuanX.. Flocking algorithm with multi-target tracking for multi-agent systems. Pattern Recogn. Lett., 2010, 31: 800-805
CrossRef Google scholar
[22]
ZhouJ., YuW., WuX., SmallM., LuJ.. Flocking of multi-agent dynamical systems based on pseudo-leader mechanism. Syst. Control Lett., 2012, 61: 195-202
CrossRef Google scholar
[23]
WangJ., XinM.. Flocking of multi-agent systems using a unified optimal control approach. J. Dyn. Syst. Meas. Control., 2013, 135: 1-11
[24]
AtrianfarH., HaeriM.. Adaptive flocking control of nonlinear multi-agent systems with directed switching topologies and saturation constraints. J. Frankl. Inst., 2013, 350: 1545-1561
CrossRef Google scholar
[25]
WangH.. Flocking of networked uncertain Euler-Lagrange systems on directed graphs. Automatica, 2013, 49: 2774-2779
CrossRef Google scholar
[26]
BarveA., NeneM. J.. Survey of flocking algorithms in multi-agent systems. Int. J. Comput. Sci. Issues, 2013, 10: 110-117
[27]
ShiP., YanB.. A survey on intelligent control for multi-agent systems. IEEE Trans. Syst. Man Cybern. Syst., 2021, 51: 161-175
CrossRef Google scholar
[28]
HeX., WangQ., HaoY.. Finite-time adaptive formation control for multi-agent systems with uncertainties under collision avoidance and connectivity maintenance. Sci. China Technol. Sci., 2020, 63: 2305-2314
CrossRef Google scholar
[29]
MengZ., LinZ., RenW.. Robust cooperative tracking for multiple non-identical second-order nonlinear systems. Automatica, 2013, 49: 2363-2372
CrossRef Google scholar
[30]
ShevitzD., PadenB.. Lyapunov stability theory of nonsmooth systems. IEEE Trans. Autom. Control, 1994, 39: 1910-1914
CrossRef Google scholar
[31]
DasA., LewisF. L.. Cooperative adaptive control for synchronization of second-order systems with unknown nonlinearities. Int. J. Robust Nonlinear Control, 2011, 21: 1509-1524
CrossRef Google scholar
[32]
CaoY., RenW.. Distributed coordinated tracking with reduced interaction via a variable structure approach. IEEE Trans. Autom. Control, 2012, 57: 33-48
CrossRef Google scholar

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