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Event-based leader-following consensus for uncertain non-linear multiagent systems. (English) Zbl 07907128

Summary: This study investigates a distributed leader-following consensus problem for a class of high-order uncertain non-linear multiagent systems. For the uncertain non-linear terms in the systems, the authors propose a less conservative Lipschitz condition, which the Lipschitz growth parameters are unknown. By using the adaptive method, the unknown Lipschitz growth parameters are estimated asymptotically. Furthermore, to lower the frequency of controller updates, a new dynamic event-triggered control strategy with the novel dynamic variable is constructed based on the event-triggered method. The distributed consensus protocol is proposed based only on the relative state information of neighbouring agents and the protocol can ensure that the Zeno-behaviour no longer occurred. Based on the Lyapunov stability theory, it is strictly proved that the state variables of the followers can track asymptotically those of the leader. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed theoretical results.
© 2021 The Authors. IET Control Theory & Applications published by John Wiley & Sons, Ltd. on behalf of The Institution of Engineering and Technology

MSC:

93C65 Discrete event control/observation systems
93D50 Consensus
93C41 Control/observation systems with incomplete information
93C10 Nonlinear systems in control theory
93A16 Multi-agent systems
Full Text: DOI

References:

[1] RenW.: ‘Consensus strategies for cooperative control of vehicle formations’, IET Control Theory Applic., 2007, 1, (2), pp. 505-512
[2] RenW., and AtkinsE.: ‘Distributed multi‐vehicle coordinated control via local information exchange’, Int. J. Robust Nonlinear Control, 2007, 17, (10‐11), pp. 1002-1033 · Zbl 1266.93010
[3] HeW., and CaoJ.: ‘Consensus control for high‐order multi‐agent systems’, IET Control Theory Applic., 2011, 5, (1), pp. 231-238
[4] PengZ.ZhaoY., and HuH.et al.: ‘Data‐driven optimal tracking control of discrete‐time multi‐agent systems with two‐stage policy iteration algorithm’, Inf. Sci., 2019, 481, (1), pp. 189-202 · Zbl 1451.93228
[5] DasA., and LewisF.L.: ‘Distributed adaptive control for synchronization of unknown nonlinear networked systems’, Automatica, 2010, 46, (12), pp. 2014-2021 · Zbl 1205.93045
[6] DasA., and LewisF.L.: ‘Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities’, Int. J. Robust Nonlinear Control, 2011, 21, (13), pp. 1509-1524 · Zbl 1227.93006
[7] DuD.FeiM., and CuiL.: ‘Event‐triggered cooperative compensation control for consensus of heterogeneous multi‐agent systems’, IET Control Theory Applic., 2016, 10, (13), pp. 1573-1582
[8] QinJ.ZhengW.X., and GaoH.: ‘Consensus control for high‐order multi‐agent systems’, IEEE Trans. Syst. Man Cybern., 2012, 42, (1), pp. 44-57
[9] LiS.FengG., and JuanW.et al.: ‘Adaptive control for cooperative linear output regulation of heterogeneous multi‐agent systems with periodic switching topology’, IET Control Theory Applic., 2015, 9, (1), pp. 34-41
[10] ZhangH., and LewisF.L.: ‘Adaptive cooperative tracking’, Automatica, 2012, 48, (7), pp. 1432-1439 · Zbl 1348.93144
[11] HuJ.CaoJ., and YuJ.: ‘Consensus of nonlinear multi‐agent systems with observer‐based protocols’, Syst. Control Lett., 2014, 72, (6), pp. 71-79 · Zbl 1297.93013
[12] XiaoF., and ChenT.: ‘Adaptive consensus in leader‐following networks of heterogeneous linear systems’, IEEE Trans. Control of Netw. Syst., 2018, 5, (3), pp. 1169-1176, DOI: 10.1109/TCNS.2017.2690403 · Zbl 1515.93152
[13] SunJ.GengZ., and LvY.et al.: ‘Distributed adaptive consensus disturbance rejection for multi‐agent systems on directed graphs’, IEEE Trans. Control Netw. Syst., 2018, 5, (1), pp. 629-639, DOI: 10.1109/TCNS.2016.2641800 · Zbl 1511.93118
[14] ShiK.WangS., and ZhongS.et al.: ‘New reliable nonuniform sampling control for uncertain chaotic neural networks under Markov switching topologies’, Appl. Math. Comput., 2019, 347, (1), pp. 169-193 · Zbl 1428.92015
[15] ShiK.WangJ., and TangY.et al.: ‘Reliable asynchronous sampled‐data filtering of T-S fuzzy uncertain delayed neural networks with stochastic switched topologies’, Fuzzy Sets Syst., 2018, in press
[16] HuW.LiuL., and FengG.: ‘Consensus of linear multi‐agent systems by distributed event‐triggered strategy’, IEEE Trans. Cybern., 2016, 46, (1), pp. 148-157
[17] LiuX.DuC., and LiuH.et al.: ‘Distributed event‐triggered consensus control with fully continuous communication free for general linear multi‐agent systems under directed graph’, Int. J. Robust Nonlinear Control, 2018, 28, (1), pp. 132-143 · Zbl 1387.93019
[18] GirardA.: ‘Dynamic triggering mechanisms for event‐triggered control’, IEEE Trans. Autom. Control, 2015, 60, (7), pp. 1992-1997 · Zbl 1360.93423
[19] HuW.YangC., and HuangT.et al.: ‘A distributed dynamic event‐triggered control approach to consensus of linear multiagent systems with directed networks’, IEEE Trans. Cybern., early access
[20] LuoS.DengF., and ChenW.: ‘Dynamic event‐triggered control for linear stochastic systems with sporadic measurements and communication delays’, Automatica, 2019, 107, (1), pp. 86-94 · Zbl 1429.93227
[21] MengX., and ChenT.: ‘Event based agreement protocols for multi‐agent networks’, Automatica, 2013, 49, (7), pp. 2125-2132 · Zbl 1364.93476
[22] FanY.FengG., and WangY.et al.: ‘Distributed event‐triggered control of multi‐agent systems with combinational measurements’, Automatica, 2013, 49, (2), pp. 671-675 · Zbl 1258.93004
[23] LiH.LiaoX., and HuangT.: ‘Event‐triggering sampling based leader‐following consensus in second‐order multi‐agent systems’, IEEE Trans. Autom. Control., 2015, 60, (7), pp. 1998-2003 · Zbl 1360.93031
[24] ChengY., and UgrinovskiiV.: ‘Event‐triggered leader‐following tracking control for multivariable multi‐agent systems’, Automatica, 2016, 70, pp. 204-210 · Zbl 1339.93075
[25] ZhuW.JiangZ, and FengG.: ‘Event‐based consensus of multi‐agent systems with general linear models’, Automatica, 2013, 50, (2), pp. 552-558 · Zbl 1364.93489
[26] HuA.CaoJ., and HuM.et al.: ‘Event‐triggered consensus of Markovian jumping multi‐agent systems via stochastic sampling’, IET Control Theory Applic., 2015, 9, (13), pp. 1964-1972
[27] LiuW., and HuangJ.: ‘Cooperative global robust output regulation for a class of nonlinear multi‐agent systems by distributed event‐triggered control’, Automatica, 2018, 93, pp. 138-148 · Zbl 1400.93069
[28] LiH.ChenG., and HuangT.: ‘Event‐triggered consensus in nonlinear multi‐agent systems with nonlinear dynamics and directed network topology’, Neurocomputing, 2016, 185, pp. 105-112
[29] WangF., and YangY.: ‘Leader‐following consensus of nonlinear fractional‐order multi‐agent systems via event‐triggered control’, Int. J. Syst. Sci., 2016, 48, (3), pp. 571-577 · Zbl 1358.93018
[30] ZhangX.ChenM., and WangL.: ‘Distributed event‐triggered consensus in multi‐agent systems with non‐linear protocols’, IET Control Theory Applic., 2015, 9, (18), pp. 2626-2633
[31] HuaC.LiuG., and ZhangL.et al.: ‘Output feedback tracking control for nonlinear time‐delay systems with tracking error and input constraints’, Neurocomputing, 2016, 73, pp. 751-758
[32] WangX., and JiH.: ‘Leader-follower consensus for a class of nonlinear multi‐agent systems’, Int. J. Control Autom. Syst., 2012, 10, (1), pp. 27-35
[33] NowzariC., and CortésJ.: ‘Distributed event‐triggered coordination for average consensus on weight‐balanced digraphs’, Automatica, 2016, 68, pp. 237-244 · Zbl 1334.93118
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