scholarly journals Fast Consensus Seeking on Networks with Antagonistic Interactions

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Jijun Qu ◽  
Zhijian Ji ◽  
Chong Lin ◽  
Haisheng Yu
Keyword(s):  
Convergence Rate ◽  
Multiagent System ◽  
Original System ◽  
Laplacian Matrix ◽  
Algebraic Connectivity ◽  
Nonzero Eigenvalue ◽  
Common Value ◽  
Communication Graphs ◽  
Delay Margin ◽  
Antagonistic Interactions

It is well known that all agents in a multiagent system can asymptotically converge to a common value based on consensus protocols. Besides, the associated convergence rate depends on the magnitude of the smallest nonzero eigenvalue of Laplacian matrix L. In this paper, we introduce a superposition system to superpose to the original system and study how to change the convergence rate without destroying the connectivity of undirected communication graphs. And we find the result if the eigenvector x of eigenvalue λ has two identical entries xi=xj, then the weight and existence of the edge eij do not affect the magnitude of λ, which is the argument of this paper. By taking advantage of the inequality of eigenvalues, conditions are derived to achieve the largest convergence rate with the largest delay margin, and, at the same time, the corresponding topology structure is characterized in detail. In addition, a method of constructing invalid algebraic connectivity weights is proposed to keep the convergence rate unchanged. Finally, simulations are given to demonstrate the effectiveness of the results.

scholarly journals On minimum algebraic connectivity of graphs whose complements are bicyclic

2019 ◽  
Vol 17 (1) ◽  
pp. 1490-1502 ◽  
Author(s):  
Jia-Bao Liu ◽  
Muhammad Javaid ◽  
Mohsin Raza ◽  
Naeem Saleem
Keyword(s):  
Connected Graph ◽  
Diffusion Processes ◽  
Laplacian Matrix ◽  
Group Differences ◽  
Algebraic Connectivity ◽  
Connected Graphs ◽  
Bicyclic Graph ◽  
Smallest Eigenvalue ◽  
Unique Graph ◽  
The Stability

Abstract The second smallest eigenvalue of the Laplacian matrix of a graph (network) is called its algebraic connectivity which is used to diagnose Alzheimer’s disease, distinguish the group differences, measure the robustness, construct multiplex model, synchronize the stability, analyze the diffusion processes and find the connectivity of the graphs (networks). A connected graph containing two or three cycles is called a bicyclic graph if its number of edges is equal to its number of vertices plus one. In this paper, firstly the unique graph with a minimum algebraic connectivity is characterized in the class of connected graphs whose complements are bicyclic with exactly three cycles. Then, we find the unique graph of minimum algebraic connectivity in the class of connected graphs $\begin{array}{} {\it\Omega}^c_{n}={\it\Omega}^c_{1,n}\cup{\it\Omega}^c_{2,n}, \end{array}$ where $\begin{array}{} {\it\Omega}^c_{1,n} \end{array}$ and $\begin{array}{} {\it\Omega}^c_{2,n} \end{array}$ are classes of the connected graphs in which the complement of each graph of order n is a bicyclic graph with exactly two and three cycles, respectively.

scholarly journals Eigenvalue Based Approach for Global Consensus in Multiagent Systems with Nonlinear Dynamics

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Wei Qian ◽  
Lei Wang
Keyword(s):  
Nonlinear Dynamics ◽  
Multiagent Systems ◽  
Multiagent System ◽  
Symmetric Matrix ◽  
Algebraic Connectivity ◽  
Communication Graph ◽  
Consensus Protocol ◽  
Global Consensus ◽  
The Common ◽  
Analytical Result

This paper addresses the global consensus of nonlinear multiagent systems with asymmetrically coupled identical agents. By employing a Lyapunov function and graph theory, a sufficient condition is presented for the global exponential consensus of the multiagent system. The analytical result shows that, for a weakly connected communication graph, the algebraic connectivity of a redefined symmetric matrix associated with the directed graph is used to evaluate the global consensus of the multiagent system with nonlinear dynamics under the common linear consensus protocol. The presented condition is quite simple and easily verified, which can be effectively used to design consensus protocols of various weighted and directed communications. A numerical simulation is also given to show the effectiveness of the analytical result.

scholarly journals Optimizing Pinned Nodes to Maximize the Convergence Rate of Multiagent Systems with Digraph Topologies

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yujuan Han ◽  
Wenlian Lu ◽  
Tianping Chen ◽  
Changkai Sun
Keyword(s):  
Convergence Rate ◽  
Multiagent Systems ◽  
Spanning Trees ◽  
Laplacian Matrix ◽  
Pinning Control ◽  
Left Eigenvector ◽  
Underlying Network ◽  
Eigenvalues Of The Laplacian ◽  
Eigenvalue Zero ◽  
Theoretical Results

This paper investigates how to choose pinned node set to maximize the convergence rate of multiagent systems under digraph topologies in cases of sufficiently small and large pinning strength. In the case of sufficiently small pinning strength, perturbation methods are employed to derive formulas in terms of asymptotics that indicate that the left eigenvector corresponding to eigenvalue zero of the Laplacian measures the importance of node in pinning control multiagent systems if the underlying network has a spanning tree, whereas for the network with no spanning trees, the left eigenvectors of the Laplacian matrix corresponding to eigenvalue zero can be used to select the optimal pinned node set. In the case of sufficiently large pinning strength, by the similar method, a metric based on the smallest real part of eigenvalues of the Laplacian submatrix corresponding to the unpinned nodes is used to measure the stabilizability of the pinned node set. Different algorithms that are applicable for different scenarios are develped. Several numerical simulations are given to verify theoretical results.

Resilient Design of Complex Engineered Systems

2013 ◽  
Author(s):  
Hoda Mehrpouyan ◽  
Brandon Haley ◽  
Andy Dong ◽  
Irem Y. Tumer ◽  
Chris Hoyle
Keyword(s):  
Complex Network ◽  
Adjacency Matrix ◽  
Laplacian Matrix ◽  
Algebraic Connectivity ◽  
Graph Spectra ◽  
Complex Engineered Systems ◽  
Resilient Design ◽  
Spectra Properties ◽  
Key Driver ◽  
Engineered Systems

This paper presents a complex network and graph spectral approach to calculate the resiliency of complex engineered systems. Resiliency is a key driver in how systems are developed to operate in an unexpected operating environment, and how systems change and respond to the environments in which they operate. This paper deduces resiliency properties of complex engineered systems based on graph spectra calculated from their adjacency matrix representations, which describes the physical connections between components in a complex engineered systems. In conjunction with the adjacency matrix, the degree and Laplacian matrices also have eigenvalue and eigenspectrum properties that can be used to calculate the resiliency of the complex engineered system. One such property of the Laplacian matrix is the algebraic connectivity. The algebraic connectivity is defined as the second smallest eigenvalue of the Laplacian matrix and is proven to be directly related to the resiliency of a complex network. Our motivation in the present work is to calculate the algebraic connectivity and other graph spectra properties to predict the resiliency of the system under design.

scholarly journals On Consensus of Star-Composed Networks with an Application of Laplacian Spectrum

2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Da Huang ◽  
Haijun Jiang ◽  
Zhiyong Yu ◽  
Qiongxiang Huang ◽  
Xing Chen
Keyword(s):  
Communication Network ◽  
Bipartite Graph ◽  
Complete Bipartite Graph ◽  
Laplacian Matrix ◽  
Convergence Speed ◽  
Laplacian Spectrum ◽  
Graph Spectra ◽  
Nonzero Eigenvalue ◽  
Insight Into

In this paper, we mainly study the performance of star-composed networks which can achieve consensus. Specifically, we investigate the convergence speed and robustness of the consensus of the networks, which can be measured by the smallest nonzero eigenvalue λ2 of the Laplacian matrix and the H2 norm of the graph, respectively. In particular, we introduce the notion of the corona of two graphs to construct star-composed networks and apply the Laplacian spectrum to discuss the convergence speed and robustness for the communication network. Finally, the performances of the star-composed networks have been compared, and we find that the network in which the centers construct a balanced complete bipartite graph has the most advantages of performance. Our research would provide a new insight into the combination between the field of consensus study and the theory of graph spectra.

Accelerate Convergence Rate of Distributed Consensus Algorithm with Optimized Topology

2014 ◽  
Vol 511-512 ◽  
pp. 950-953
Author(s):  
Huan Xin Peng ◽  
Wen Kai Wang ◽  
Bin Liu
Keyword(s):  
Convergence Rate ◽  
Large Scale ◽  
Nearest Neighbor ◽  
Consensus Algorithm ◽  
Algebraic Connectivity ◽  
Distributed Consensus ◽  
Consensus Algorithms ◽  
New Model ◽  
Accelerate Convergence ◽  
Topology Model

The convergence rate is very important in the distributed consensus problems, especially, for the distributed consensus algorithms based on large-scale complex networks. In order to accelerate the convergence rate of the distributed consensus algorithms, in the paper, we propose an optimized topology model by adding randomly a few shortcuts to the nearest neighbor coupling networks, and the shortcuts follow a normal distribution. By analyses and simulations, the results show that the algebraic connectivity of the new model is bigger than that of the NMW model, and the convergence rate of the distributed consensus based on the new model is higher than that based on the NMW model

scholarly journals Distributed Control for Multiagent Consensus Motions with Nonuniform Time Delays

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Mengji Shi ◽  
Kaiyu Qin
Keyword(s):  
Distributed Control ◽  
Time Delays ◽  
Original System ◽  
Complex Numbers ◽  
Control Problems ◽  
Rectilinear Motion ◽  
State Variables ◽  
Real Numbers ◽  
Numerical Examples ◽  
Delay Margin

This paper solves control problems of agents achieving consensus motions in presence of nonuniform time delays by obtaining the maximal tolerable delay value. Two types of consensus motions are considered: the rectilinear motion and the rotational motion. Unlike former results, this paper has remarkably reduced conservativeness of the consensus conditions provided in such form: for each system, if all the nonuniform time delays are bounded by the maximal tolerable delay value which is referred to as “delay margin,” the system will achieve consensus motion; otherwise, if all the delays exceed the delay margin, the system will be unstable. When discussing the system which is intended to achieve rotational consensus motion, an expanded system whose state variables are real numbers (those of the original system are complex numbers) is introduced, and corresponding consensus condition is given also in the form of delay margin. Numerical examples are provided to illustrate the results.

scholarly journals Balanced containment control and cooperative timing of a multiagent system over random communication graphs

2018 ◽  
Vol 28 (11) ◽  
pp. 3574-3588 ◽  
Author(s):  
Z. Kan ◽  
S. S. Mehta ◽  
J. M. Shea ◽  
J. W. Curtis ◽  
W. E. Dixon
Keyword(s):  
Multiagent System ◽  
Containment Control ◽  
Communication Graphs

scholarly journals The Orderings of Bicyclic Graphs and Connected Graphs by Algebraic Connectivity

10.37236/434 ◽  
2010 ◽  
Vol 17 (1) ◽  
Author(s):  
Jianxi Li ◽  
Ji-Ming Guo ◽  
Wai Chee Shiu
Keyword(s):  
Linear Algebra ◽  
Laplacian Matrix ◽  
Algebraic Connectivity ◽  
Connected Graphs ◽  
Unicyclic Graphs ◽  
Smallest Eigenvalue ◽  
Bicyclic Graphs

The algebraic connectivity of a graph $G$ is the second smallest eigenvalue of its Laplacian matrix. Let $\mathscr{B}_n$ be the set of all bicyclic graphs of order $n$. In this paper, we determine the last four bicyclic graphs (according to their smallest algebraic connectivities) among all graphs in $\mathscr{B}_n$ when $n\geq 13$. This result, together with our previous results on trees and unicyclic graphs, can be used to further determine the last sixteen graphs among all connected graphs of order $n$. This extends the results of Shao et al. [The ordering of trees and connected graphs by their algebraic connectivity, Linear Algebra Appl. 428 (2008) 1421-1438].

scholarly journals Evaluating the Cascade Effect in Interdependent Networks via Algebraic Connectivity

2015 ◽  
Vol 1 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Sotharith Tauch ◽  
William Liu ◽  
Russel Pears
Keyword(s):  
Network Structure ◽  
Topological Structure ◽  
Laplacian Matrix ◽  
Network Robustness ◽  
Node Degree ◽  
Algebraic Connectivity ◽  
Interdependent Networks ◽  
Cascade Effect ◽  
Underlying Network ◽  
Average Node Degree

Understanding how the underlying network structure and interconnectivity impact on the robustness of the interdependent networks is a major challenge in complex networks studies. There are some existing metrics that can be used to measure network robustness. However, different metrics such as the average node degree interprets different characteristic of network topological structure, especially less metrics have been identified to effectively evaluate the cascade performance in interdependent networks. In this paper, we propose to use a combined Laplacian matrix to model the interdependent networks and their interconnectivity, and then use its algebraic connectivity metric as a measure to evaluate its cascading behavior. Moreover, we have conducted extensive comparative studies among different metrics such as the average node degree, and the proposed algebraic connectivity. We have found that the algebraic connectivity metric can describe more accurate and finer characteristics on topological structure of the interdependent networks than other metrics widely adapted by the existing research studies for evaluating the cascading performance in interdependent networks.

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