×

Pinning and self-adaptive control to the couple-group consensus of heterogeneous fractional multi-agent systems with cooperative-competitive relation. (English) Zbl 07841411

Summary: In this article, the couple-group consensus of a class of heterogeneous fractional multi-agent systems with time-varying delay (HFMASs) has been studied. Based on cooperative-competitive interaction, pinning and self-adaptive controller has been designed to realize the couple-group consensus for this system with single integrator and double integrator fractional-order dynamics. By using Lyapunov function, mode-dependent average dwell time (MDADT) technology, stability theory and delta operator method, some sufficient conditions have been obtained to guard the success of couple-consensus for this HFMASs with fixed or switching topologies. According to these sufficient conditions, the related feasible solutions can be solved by using liner matrix inequality (LMI). In addition, these results are also applicable to the system with weakly connected topology without containing a spanning tree or meeting the demand of equilibrium of degree. Finally, several simulation experiments have been presented to prove the validity of the related results.
{© 2022 John Wiley & Sons Ltd.}

MSC:

93A16 Multi-agent systems
93C40 Adaptive control/observation systems
93D50 Consensus
Full Text: DOI

References:

[1] BurmeisterB, HaddadiA, MatylisG. Application of multi‐agent systems in traffic and transportation. IEEE Proc Softw. 1997;144(1):51‐60.
[2] NegenbornR, SchutterB, HellendoornJ. Multi‐agent model predictive control for transportation networks: serial versus parallel schemes. Eng Appl Artif Intell. 2008;21(3):353‐366.
[3] FengZ, HuG. Distributed secure average consensus for linear multi‐agent systems under dos attacks. Proceedings of the 2017 American Control Conference (ACC); 2017:2261‐2266
[4] AmullenM, ShettyS, KeelH. Model‐based resilient control for a multi‐agent system against denial of service attacks. Proceedings of the 2016 World Automation Congress (WAC); 2016:1‐6
[5] WenG, DuanZ, YuW, ChenG. Consensus of second‐order multi‐agent systems with delayed nonlinear dynamics and intermittent communications. Int J Control. 2013;86(2):322‐331. · Zbl 1278.93016
[6] SunF, WangR, ZhuW. Flocking in nonlinear multi‐agent systems with time‐varying delay via event‐triggered control. Appl Math Comput. 2019;350:66‐77. · Zbl 1428.93012
[7] ZhouB, LiaoX, HuangT, ChenG. Leader‐following exponential consensus of general linear multi‐agent systems via event‐triggered control with combinational measurements. Appl Math Lett. 2015;40:35‐39. · Zbl 1310.93011
[8] YuJ, WangL. Group consensus in multi‐agent systems with swit ching topologies and communication delays. Syst Control Lett. 2010;59(6):340‐348. · Zbl 1197.93096
[9] YuJ, YuM, HuJ, LiuB. Group consensus in multi‐agent systems with sampled data, Proceedings of the 32nd Chinese Control Conference; 2013:7168‐7172
[10] YuJ, WangL. Group consensus of multi‐agent systems with undirected communication graphs. Proceedings of the 2009 7th Asian Control Conference; 2009:105‐110.
[11] ShangY. Group consensus of multi‐agent systems in directed networks with noises and time delays. Int J Syst Sci. 2015;46(14):2481‐2492. · Zbl 1332.93025
[12] JiL, YuX, LiC. Group consensus for heterogeneous multi‐agent systems in the competition networks with input time delays. IEEE Trans Syst Man Cybern Syst. 2018;99:1‐9.
[13] YinX, YueD, HuS. Consensus of fractional‐order heterogeneous multi‐agent systems. IET Control Theory Appl. 2013;7:314‐322.
[14] SunW, LiY, LiC, ChenY. Convergence speed of a fractional‐order consensus algorithm over undirected scale‐free network. Asian J Control. 2011;13:936‐946. · Zbl 1263.93013
[15] ShenJ, CaoJ. Necessary and sufficient conditions for consensus of delayed fractional‐order systems. Asian J Control. 2012;14:1690‐1697. · Zbl 1303.93017
[16] CaoY, LiY, RenW, ChenY. Distributed coordination of networked fractional‐order systems. IEEE Trans Syst Man Cybern. 2010;40(2):362‐370.
[17] XiaoB, LuoJ, BiX. Fractional discrete Tchebyshev moments and their applications in image encryption and watermarking. Inf Sci. 2020;516:545‐559. · Zbl 1460.94068
[18] OwolabiKM. High‐dimensional spatial patterns in fractional reaction‐diffusion system arising in biology. Chaos Soliton Fract. 2020;134:1‐12. · Zbl 1483.35117
[19] ZouC, ZhangL, HuX, WangZ, WikT, PechtM. A review of fractional‐order techniques applied to lithium‐ion batteries, lead‐acid batteries, and supercapacitors. J Power Sources. 2018;390:286‐296.
[20] GongP. Distributed tracking of heterogeneous nonlinear fractional‐order multi‐agent systems with an unknown leader. J Franklin Inst. 2017;354(5):2226‐2244. · Zbl 1398.93014
[21] WenG, ZhangY, PengZ, YuY, RahmaniA. Observer‐based output consensus of leader‐ following fractional‐order heterogeneous nonlinear multi‐agent systems. Int J Control. 2019;93(10):2516‐2524. · Zbl 1453.93225
[22] GaoZ, ZhangH, WangY, MuY. Time‐varying output formation‐containment control for homogeneous/heterogeneous descriptor fractional‐order multi‐agent systems. Inf Sci. 2021;567:146‐166. · Zbl 1526.93004
[23] BaleanuD, SajjadiSS, JajarmiA, AsadJH. New features of the fractional Euler‐Lagrange equations for a physical system within non‐singular derivative operator. Eur Phys J Plus. 2019;134(4):181‐191.
[24] GoulartA, LazoM, SuarezJ. A new parameterization for the concentration flux using the fractional calculus to model the dispersion of contaminants in the planetary boundary layer. Phys A Stat Mech Appl. 2019;518:38‐49. · Zbl 1514.76085
[25] RajagopalK, VaidyanathanS, KarthikeyanA, DuraisamyP. Dynamic analysis and chaos suppression in a fractional order brushless DC motor. Electr Eng. 2017;99(2):721‐733.
[26] KozlovskyY, CohenI, GoldingI, Ben‐JacobE. Lubricating bacteria model for branching growth of bacterial colonies. Phys RevE Stat Phys Plasmas Fluids Relat Interdiscip. 1999;59(6):7025‐7035.
[27] CohenI, GoldingI, RonIG, Ben‐JacobE. Biofluiddynamics of lubricating bacteria. Math Methods Appl Sci. 2001;24:17‐18. · Zbl 1097.76618
[28] HuX, ChenG, XuanQ. Second‐order consensus for heterogeneous agents in the cooperation‐competition network. Proceedings of the 27th Chin. Control Decision. Conf. (CCDC); 2015:267‐272
[29] PuX, LiuY, RenL, XiongC. The weighted couple‐group consensus for a kind of continuous heterogeneous multi‐agent systems based on self‐adaptive and cooperative‐competitive mechanism. IEEE Access. 2020;8:37321‐37333.
[30] PuX, RenL, RenLY, JiL. Group consensus of multi‐agent systems with cooperative‐competitive interaction and communication delay in switching topologies networks based on the delta operator method. Neurocomputing. 2020;390:57‐68.
[31] SongQ, LiuF, JbC. Pinning‐controllability analysis of complex networks: an M‐matrix approach. IEEE Trans Circuits Syst I Regul Pap. 2012;59(11):2692‐2701. · Zbl 1468.94810
[32] SongQ, LiuF, CaoJ. M‐matrix strategies for pinning‐controlled leader‐following consensus in multiagent systems with nonlinear dynamics. IEEE Trans Cybern. 2013;43(6):1688‐1697.
[33] LiH, XuL, XiaoL. Second‐orderleader‐following consensus of nonlinear multi‐agent systems via adaptive pinning control. Proceedings of the 26th Chinese Control and Decision Conference (CCDC); 2014:587‐592.
[34] LiX, YuZ, LiZ. Group consensus via pinning control for a class of heterogeneous multi‐agent systems with input constraints. Inf Sci. 2021;542:247‐262. · Zbl 1478.93633
[35] PuX, RenL, LiuY, PuR. Couple‐group consensus for heterogeneous MASs under switched topologies in cooperative‐competitive systems: a hybrid pinning and delta operator skills. Neurocomputing. 2021;441:335‐349.
[36] JiL, GaoT, LiaoX. Couple‐group consensus for cooperative‐competitive heterogeneous multi‐agent systems: hybrid adaptive and pinning methods. IEEE Trans Syst Man Cybern Syst. 2019;51(9):5367‐5376.
[37] LiK, JiL, YangS, LiH. Couple‐group consensus of cooperative‐competitive heterogeneous multi‐agent systems: a fully distributed event‐triggered and pinning control method. IEEE Trans Cybern. 2020;61(10):1‐9.
[38] MengF, ZengX, WangZ. Dynamical behavior and synchronization in time‐delay fractional‐order coupled neurons under electromagnetic radiation. Nonlinear Dyn. 2019;95(2):1615‐1625. · Zbl 1439.92017
[39] ZhuW, ChenB, YangJ. Consensus of fractional‐order multi‐agent systems with input time delay. Fract Fract Calcul Appl Anal. 2017;20(1):52‐70. · Zbl 1358.93026
[40] WangB, JianJ, ShenY. Consensus of fractional‐order multi‐agent systems with input delays and compounded orders. Proceedings of the Chinese Control Conference; 2014:1110‐1114; IEEE
[41] WangF, YangQ. Leader‐following exponential consensus of fractional order nonlinear multi‐agents system with hybrid time‐varying delay: a heterogeneous impulsive method. Phys A‐Stat Mech Appl. 2017;482:158‐172. · Zbl 1495.93011
[42] WangC. Existence and uniqueness of positive solution for a nonlinear multi‐order fractional differential equations. Math Appl. 2009;4(15):2137‐2154.
[43] WangH, ZhangC, ShuW. Positive solution of a nonlinear fractional differential equation involving caputo derivative. Discrete Dyn Nature Soc. 2012;26(4):1‐16. · Zbl 1248.34006
[44] GoodwinG, LealL, MayneDQ, MiddletonRH. Rapprochement between continuous and discrete model reference adaptive control. Automatica. 1986;22(2):199‐207. · Zbl 0614.93039
[45] KilbasAAA, SrivastavaH, TrujilloJ. Theory and Applications of Fractional Differential Equations. North Holland Mathematical Studies; 2006. · Zbl 1092.45003
[46] XieD, ZhangH, WangB. Exponential stability of switched systems with unstable subsystems: a mode‐dependent average dwell time approach. Circuits Syst Signal Process. 2013;32(6):3093‐3105.
[47] XiangZ, ChenQ, HuW, ZhangD. Robust stability analysis and control for fuzzy systems with uncertainties using the delta operator. Control Decis. 2003;18(6):720‐723. · Zbl 1498.93418
[48] JiangX, HanQ, YuX. Stability criteria for linear discrete‐time systems with interval‐like time‐varying delay. Proceedings of the 2005, American Control Conference; 2005:2817‐2822.
[49] LiuJ, QinK, LiP, et al. Distributed consensus control for double‐integrator fractional‐order multi‐agent systems with nonuniform time‐delays. Neurocomputing. 2018;321:369‐380.
[50] WangL, DongJ. Adaptive fuzzy consensus tracking control for uncertain fractional‐order multi‐agent systems with event‐triggered input. IEEE Trans Fuzzy Syst. 2022;30(2):310‐320. doi:10.1109/tfuzz.2020.3037957
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.