Group consensus in multi-agent systems with switching topologies and communication delays

Yu, Junyan; Wang, Long

doi:10.1016/j.sysconle.2010.03.009

Cited by 465 publications

(285 citation statements)

References 20 publications

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“…In [10][11][12][13], based on the in-degree balance conditions(A1) and (A2), average group consensus problems of multi-agent networks with undirected, strongly connected and balanced topologies were investigated, respectively. The input protocol is as follows:…”

Section: Group Consensus Of Multi-agent Network With Multiple Dmentioning

confidence: 99%

“…In [9], couplegroup consensus problems of second-order networks with fixed and stochastic switching topologies were discussed, and the authors provided the sufficient and necessary condition for mean-square couple-group consensus. In [10,11], Yu studied group consensus of networks with undirected graphs and strongly connected and balanced topology. Furthermore, by applying double-tree-form transformation, they extended group consensus with communication delays and switching topologies [12,13].…”

Section: Introductionmentioning

confidence: 99%

“…In [10,11], Yu studied group consensus of networks with undirected graphs and strongly connected and balanced topology. Furthermore, by applying double-tree-form transformation, they extended group consensus with communication delays and switching topologies [12,13]. In [14], group consensus of networks with communication delays was investigated and the topology of the system was strongly connected and balanced.…”

Section: Introductionmentioning

confidence: 99%

“…From the relevant works mentioned above, it is not difficult to find out there are some more conservative assumptions in them. First, some related research works only consider communication delays, or only analyze the same communication and input delays, such in [10][11][12][13][15][16][17]. As mentioned above, the two delays between agents should be different and coexisting.…”

Section: Introductionmentioning

confidence: 99%

“…As mentioned above, the two delays between agents should be different and coexisting. Second, most of the works only focus on the networks with symmetrical topology, such as in [8,10,11,[14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Ji¹,

Zhao²

2016

Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling

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Abstract-In this paper, the problem of group consensus of second-order multi-agent networks with multiple time delays is investigated. Based on the theory of frequency-domain, some algebraic criteria are proposed analytically which can guarantee the multi-agent networks to achieve group consensus. Results show that input time delays of the agents, coupling weights and coupling strengths between the agents play a key role in reaching group consensus. Meanwhile, communication time delays can only affect the convergence rate of the systems. Finally, the validity and correctness of our theoretical results are verified by several numerical simulated examples.

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Section: Group Consensus Of Multi-agent Network With Multiple Dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Ji¹,

Zhao²

2016

Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling

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Adaptive control and signal processing literature survey (No. 20)

2010

Adaptive Control & Signal

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In order to keep the readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that although the list has been broadly categorized, these classifications are by no means strict and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Erfu Yang at erfu.yang@eee.strath.ac.uk. ADAPTIVE SYSTEMSAbramovich Y, Frazer G, Johnson B. Iterative adaptive Kronecker MIMO radar beamformer: description and convergence analysis. IEEE Transactions on Signal Processing 2010; 58(7):3681-3691. Badwe A, Singh A, Patwardhan S, Gudi R. A constrained recursive pseudo-linear regression scheme for on-line parameter estimation in adaptive control. Journal of Process Control 2010; 20(5):559-572. Cassimatis N, Bignoli P, Bugajska M, Dugas S, Kurup U, Murugesan A, Bello P. An architecture for adaptive algorithmic hybrids. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetic 2010; 40(3):903-914. Cheah C, Hou S, Zhao Y, Slotine J-J. Adaptive vision and force tracking control for robots with constraint uncertainty. IEEE/ASME Transactions on Mechatronics 2010; 15(3): 389-399. Cheah C, Liu C, Slotine J. Adaptive Jacobian vision based control for robots with uncertain depth information. Automatica 2010; 46(7):1228-1233. De Maio A, Conte E. Adaptive detection in Gaussian interference with unknown covariance after reduction by invariance. IEEE Transactions on Signal Processing 2010; 58(6):2925-2934. Fei J. Robust adaptive vibration tracking control for a micro-electro-mechanical systems vibratory gyroscope with bound estimation. control allocation for non-linear systems with internal dynamics. IET Control Theory and Applications 2010; 4(6):909-922. Liu L, Xie X-J. Decentralized adaptive stabilization for interconnected systems with dynamic input-output and nonlinear interactions. Automatica 2010; 46(6):1060-1067. Malloci I, Daafouz J, Iung C. Stability and stabilization of two time scale switched systems in discrete time. IEEE Transactions on Automatic Control 2010; 55(6):1434-1438. Mileounis G, Babadi B, Kalouptsidis N, Tarokh V. An adaptive greedy algorithm with application to nonlinear communications. IEEE Transactions on Signal Processing 2010; 58(6):2998-3007. Nguyen H-X, Nguyen H-H. Adaptive relaying in noncoherent cooperative networks. IEEE Transactions on Signal Processing 2010; 58(7):3938-3945. Pigg S, Bodson M. Adaptive algorithms for the rejection of sinusoidal disturbances acting on unknown plants. IEEE Transactions on Control Systems Technology 2010; 18(4): 822-836. Tucci M, Raugi M. Adaptive FIR neural model for centroid learning in self-organizing maps. IEEE Transactions on Neural Networks 2010; 21(6):948-960. Wang L, de Lamare R, Yukawa M. Adaptive reducedrank constrained constant modulus algorithms based on

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Pinning and self‐adaptive control to the couple‐group consensus of heterogeneous fractional multi‐agent systems with cooperative‐competitive relation

Cheng

2022

Adaptive Control & Signal

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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.

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Group consensus in multi-agent systems with switching topologies and communication delays

Cited by 465 publications

References 20 publications

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Adaptive control and signal processing literature survey (No. 20)

Pinning and self‐adaptive control to the couple‐group consensus of heterogeneous fractional multi‐agent systems with cooperative‐competitive relation

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