Average consensus in networks of multi-agents with both switching topology and coupling time-delay

Lin, Peng; Jia, Yingmin

doi:10.1016/j.physa.2007.08.040

Cited by 339 publications

(245 citation statements)

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“…For example, the time it takes to synchronize Kuramoto oscillators upon any network scales with the inverse of µ N −1 [19,20,21,22]. In other words, larger values of µ N −1 enable synchronization in both discrete and continuous-time systems, even in the presence of transmission delays [23,24]. As a second application, graphs with "small" algebraic connectivity have a relatively clean bisection, i.e.…”

Section: Introductionmentioning

confidence: 99%

Algebraic connectivity of interdependent networks

Martı́n-Hernández

Wang

Mieghem

et al. 2014

Physica A: Statistical Mechanics and its Applications

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The algebraic connectivity µ N −1 , i.e. the second smallest eigenvalue of the Laplacian matrix, plays a crucial role in dynamic phenomena such as diffusion processes, synchronization stability, and network robustness. In this work we study the algebraic connectivity in the general context of interdependent networks, or network-of-networks (NoN). The present work shows, both analytically and numerically, how the algebraic connectivity of NoNs experiences a transition. The transition is characterized by a saturation of the algebraic connectivity upon the addition of sufficient coupling links (between the two individual networks of a NoN). In practical terms, this shows that NoN topologies require only a fraction of coupling links in order to achieve optimal diffusivity. Furthermore, we observe a footprint of the transition on the properties of Fiedler's spectral bisection.

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Section: Introductionmentioning

confidence: 99%

Algebraic connectivity of interdependent networks

Martı́n-Hernández

Wang

Mieghem

et al. 2014

Physica A: Statistical Mechanics and its Applications

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“…Moreover, they are all strongly connected, but not all graphs are required to be balanced, for instance, where G. and G4, are not balanced graphs. It is different from the situation in Refs.fg] and [10], where all digraphs are required to be balanced. Shown in Fig.2 is a finite state machine with four states {Go, Gt, G., Ga} representing the discrete-states of a network with switching topology as a hybrid system.…”

Section: Network Consensus With Switching Topologymentioning

confidence: 82%

Nonlinear consensus protocols for multi-agent systems based on centre manifold reduction

Guan

2009

Chinese Phys. B

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“…Some conclusions also were invesFor consensus pr tigated in [16][17][18]. otocol in (3), communication delay on er, we are interested in discussing the averly affects the agents who are transmitted.…”

Section: Control Protocol For Time Delaymentioning

confidence: 99%

“…Currently, consensus problem for multi-agent networks with time delay was studied using linear matrix inequality method, for example [17][18][19] and [20]. In time delay systems of multi-agent, the network topology of multi-agent is a key factor in the analysis of stability of multi-agent system.…”

Section: Introductionmentioning

confidence: 99%

“…In time delay systems of multi-agent, the network topology of multi-agent is a key factor in the analysis of stability of multi-agent system. Average consensus problem for multi-agent networks with both constant    and time-varying delay has been extensively considered for the cases of multi-agent undirected and/or direction networks with fixed and/or switching topology [17,18] and [19]. However, the studies on consensus problem of multi-agent networks with multiple timevarying delays are still sparse.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Average Consensus in Networks of Multi-Agent with Multiple Time-Varying Delays

Zhang¹,

2010

IJCNS

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The average consensus in undirected networks of multi-agent with both fixed and switching topology coupling multiple time-varying delays is studied. By using orthogonal transformation techniques, the original system can be turned into a reduced dimensional system and then LMI-based method can be applied conveniently. Convergence analysis is conducted by constructing Lyapunov-Krasovskii function. Sufficient conditions on average consensus problem with multiple time-varying delays in undirected networks are obtained via linear matrix inequality (LMI) techniques. In particular, the maximal admissible upper bound of time-varying delays can be easily obtained by solving several simple and feasible LMIs. Finally, simulation examples are given to demonstrate the effectiveness of the theoretical results.

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Average consensus in networks of multi-agents with both switching topology and coupling time-delay

Cited by 339 publications

References 10 publications

Algebraic connectivity of interdependent networks

Algebraic connectivity of interdependent networks

Nonlinear consensus protocols for multi-agent systems based on centre manifold reduction

Average Consensus in Networks of Multi-Agent with Multiple Time-Varying Delays

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