Improved results on distributed observer-based positive edge consensus

This paper revisits the observer-based positive edge consensus problem for nodal networks. So far, existing positive edge consensus of directed networks with less conservative connectivity conditions have to use the global topology information. On the other hand, instead of using global topology information, the positive consensus conditions using the bounds of the eigenvalues of the Laplacian matrix are conservative. To tackle these problems, less conservative bounds of the eigenvalues of the Laplacian matrix are presented. Based on a general distributed observer-based approach, the necessary and sufficient conditions of the edge consensus are derived. And then, with the improved bounds of the Laplacian eigenvalues, less conservative sufficient conditions without using global topology information are given. By solving the algebraic Riccati inequalities, semi-definite programming algorithms are developed to obtain the solutions. Finally, simulation results are also given to illustrate the given results.     

Fast distributed algebraic connectivity estimation in large scale networks

This paper presents a distributed method to estimate the algebraic connectivity of fixed undirected communication graphs. The proposed algorithm uses bisection to estimate the second smallest eigenvalue of the Laplacian matrix associated to the graph. In order to decide the sub-interval in which the eigenvalue is contained, a distributed averaging algorithm based on Chebyshev polynomials is considered together with a max consensus algorithm. The information exchanged by neighbors in the graph each communication round is constant and independent of the size of the network, making it scalable to large networks. Besides, exploiting the convergence properties of Chebyshev polynomials we provide a direct estimation of the algebraic connectivity so that, instead of the midpoint of the bisection interval, the new approximation can be used. Finally, our algorithm also provides upper and lower bounds on the algebraic connectivity and an estimation of the Fiedler eigenvector associated to it. Simulations in large networks demonstrate the scalability and accuracy of the algorithm.     

How to facilitate knowledge diffusion in complex networks: The roles of network structure,knowledge role distribution and selection rule

The diffusion of knowledge within organizations provides opportunities for interpersonal co-operation, improves creative ability and therefore leads to competitive advantage. Focus of prior literature on knowledge diffusion has been on identifying factors that influence individuals' behavioral intentions to seek and share knowledge. However, knowledge diffusion as an enigmatic, emergent and organizational-level process is more than the simple aggregation of individual attributes and needs to be further investigated. Accordingly, this study focuses on three distinct system-level factors, i.e., architectures of connections among individuals, distributions of knowledge roles and designs of selection mechanisms and analyses their effects on knowledge diffusion. To be more specific, we examine three distinct knowledge roles: seekers, contributors and brokers. We also distinguish between three types of selection mechanisms: objective selection mechanisms, feedback-based selection mechanisms and random selection mechanisms. By conducting agent-based simulations on four representative networks, i.e., regular networks, random networks, small-world networks and scale-free networks, our results show that the optimal knowledge diffusion performance can be achieved on scale-free networks where all agents implement objective mechanisms and show characteristics of brokers. Moreover, our results (a) highlight the significance of brokers, (b) illustrate the superiority of objective selection rules and (c) demonstrate that scale-free networks provide an optimal framework for knowledge diffusion. Furthermore, we also find the interdependent relevance of these three factors to knowledge diffusion and propose a qualitative explanation of these findings.     

Couple-group consensus for multi-agent networks of agents with discrete-time second-order dynamics

This paper considers the couple-group consensus problem for multi-agent networks with fixed and directed communication topology, where all agents are described by discrete-time second-order dynamics. Consensus protocol is designed such that some agents in a network reach a consistent value, while other agents reach another consistent value. The convergence of the system matrix is discussed based on the tools from matrix theory. An algebraic condition is established to guarantee couple-group consensus. Moreover, for a given communication topology, a theorem is derived on how to select proper control parameters and sampling period for couple-group consensus to be reached. Finally, simulation examples are presented to validate the effectiveness of the theoretical results.     

基于知识模因级联网络的领域知识扩散模式分析

[目的/意义]知识经济时代,知识的生产、扩散和消费是社会经济发展的重要推动力。其中,知识扩散是充分发挥知识价值的重要过程,从微观层面理解知识扩散的规律对促进知识利用与创新具有重要意义。[方法/过程]以医学信息学领域的科学文献为例,文章基于知识模因的微观层面,采用知识模因识别方法从文献中提取出知识模因来表征知识单元,并基于文献引证网络构建各知识模因的扩散级联网络,计算分析扩散级联网络的基础特征及其特征分布情况,以考察不同知识模因在学科领域内的扩散模式。[结果/结论]医学信息学领域内发现了四种典型的知识模因扩散模式:单起源型、多起源-独立型、多起源-迭代型、多起源-融合型。此外,通过对级联网络的各项属性分布特征进行分析发现,网络呈现无标度性,医学信息学领域极少数的知识模因获得了大量的传播资源,领域内的研究集中于被少数知识模因所代表的研究方向上,而领域内各研究方向的生命周期长度则相对差异较小。     

Scaled group consensus in agent networks with finite sub-networks under continuous/discrete-time settings

We study scaled group consensus problems of the first/second-order multi-agent dynamics under continuous/discrete-time settings. For a directed multi-agent network with finite sub-networks, the scaled group consensus is concerned with this case that all the sub-networks reach consensus, separately, while maintain the given ratios among the multiple consensus. First/second-order distributed protocols with continuous/discrete data are designed to solve the scaled group consensus problems, and then necessary and sufficient criteria are established to guarantee the agents’ states reaching the scaled group consensus asymptotically applying both algebraic and analytical tools. Finally, the effectiveness of the theoretical results are verified by several simulation examples.     

基于复杂网络的技术创新扩散控制研究

企业间竞争日趋激烈,所有的企业都希望通过创新来提升竞争力.针对技术创新扩散问题,运用复杂网络方法构建技术创新级联扩散非线性模型;对ER随机网络、BA无标度网络、SW小世界网络分别进行仿真分析,阐述网络结构对技术创新扩散的影响,通过调节感知效用再分配系数可以更好地达到控制扩散的效果.     

基于产业网络的创新扩散机制研究

创新的真正价值在于其在产业网络上的扩散。影响创新在产业网络上扩散的因素有网络的拓扑结构和创新的扩散规则。产业网络是具有无标度特性和小世界特性的复杂网络,其结构对创新扩散的阈值、路径长度以及企业地位和创新分享有不同的影响;基于企业进行技术创新的成本以及对待技术创新风险的态度,本文还给出了产业网络上的"技术创新雪崩"扩散模型,并进一步作了分析。     

Consensus of linear multi-agent systems based on full-order observer

This paper considers distributed consensus problem of multi-agent systems consisting of general linear dynamics with a time-invariant communication topology. A distributed full-order observer type consensus protocol based on relative output measurements of neighbor agents is proposed. It is found that the consensus problem of linear multi-agent systems with a directed communication topology having a spanning tree can be solved if and only if all subsystems are asymptotically stable. Some necessary and sufficient conditions are obtained for ensuring consensus in multi-agent systems. The design technique is based on algebraic graph theory, Riccati inequality and linear control theory. Finally, simulation example is given to illustrate the effectiveness of the theoretical results.     

Leaderless consensus of multi-agent systems via an event-triggered strategy under stochastic sampling

This paper investigates mean square leaderless consensus of networked nonlinear multi-agent systems. An efficient distributed event-triggered mechanism based on stochastic sampling is introduced to reduce the communication cost and controller updates. The stochastic sampling interval randomly switches between two given values. Mean square consensus criteria for multi-agent systems with strongly connected networks or networks containing directed spanning trees are derived, respectively. Moreover, the case with a special event-triggered weighting matrix and the case without even-triggered strategies are also discussed. Finally, an example is given to verify the theoretical results.     

Analysis of distributed consensus protocols with multi-equilibria under time-delays

In this paper, we propose a novel method for addressing the multi-equilibria consensus problem for a network of n agents with dynamics evolving in discrete-time. In this method, we introduce, for the first time in the literature, two concepts called primary and secondary layer subgraphs. Then, we present our main results on directed graphs such that multiple consensus equilibria states are achieved, thereby extending the existing single-state consensus convergence results in the literature. Furthermore, we propose an algorithm to determine the number of equilibria for any given directed graph automatically by a computer program. We also analyze the convergence properties of multi-equilibria consensus in directed networks with time-delays under the assumption that all delays are bounded. We show that introducing communication time-delays does not affect the number of equilibria of the given network. Finally, we verify our theoretical results via numerical examples.     

Fixed-time bipartite consensus of nonlinear multi-agent systems under directed signed graphs with disturbances

This paper considers the fixed-time bipartite consensus of nonlinear multi-agent systems (MASs) subjected to external disturbances. Under the directed signed networks, several sufficient conditions are proposed to guarantee the fixed-time bipartite consensus of MASs with or without leaders, respectively. Some discontinuous control protocols are developed to realize fixed-time tracking bipartite consensus of MASs with a leader. Moreover, the fixed-time leaderless bipartite consensus under directed signed graph are discussed as well. Two numerical examples are given to verify the effectiveness of the theoretical results.     

基于网络中心点辐射导向的农村居民点体系重组与优化——以重庆市江津区燕坝村为例

村落空间网络是以农村居民点为节点、线性设施为依托、节点相互作用而构成的复杂网络。开展村落空间网络及其节点中心性研究能够理清节点在网络中的关键位置与影响范围,为农村居民点规划建设、整体网络结构优化提供理论借鉴。本文以重庆市江津区燕坝村为例,运用复杂网络理论与方法构建村落空间网络,进而辨析网络中心点及其辐射强度与辐射范围,厘定出农村居民点体系优化重组模式。结果表明：① 村落空间网络具有典型的非均衡层次结构、小世界特征与无标度特性,网络整体的联系程度较低;② 依据中心点的辐射能力划分其等级,形成Ⅰ级中心点、Ⅱ级中心点和Ⅲ级节点共同作用的网络节点体系;③ 基于此,从“整体-局部-个体”3个影响层次,构建了中心村（Ⅰ级中心点）扩散型、基层村（Ⅱ级中心点）增长型、散居农村居民点（Ⅲ级节点）挖潜型3类优化重组模式。     

基于复杂社会网络的创新扩散多智能体仿真研究

创新扩散是由潜在采纳者的微观采纳决策所共同涌现出的宏观动力学行为。以复杂社会网络为创新扩散建模载体,通过建立潜在采纳者在社会学习和规范压力双重影响下的创新采纳决策及扩散机制,运用基于多智能体的仿真研究方法,研究微观层面因素是如何影响创新的宏观扩散。研究发现：无标度社会网络下的创新扩散深度最大及扩散速度最快;潜在采纳者的创新信息评价策略会显著地影响创新扩散深度;初始采纳者比例的提高可加快创新扩散速度,但无法持续提高扩散深度;过强或过弱的观念领导者创新性,均不利于创新扩散的深度;不同的初始采纳者类型对创新扩散深度、以及观念领导者创新性的强弱对创新扩散速度的影响取决于社会网络的拓扑结构。研究结果对于制定创新推广策略具有一定的指导意义。     

Synchronization of hybrid-coupled heterogeneous networks: Pinning control and impulsive control schemes

In this paper, the synchronization control problem is considered for the delayed hybrid-coupled heterogeneous networks, i.e., complex networks with nonidentical dynamical nodes. Some effective control schemes are designed under which the whole network is globally asymptotically synchronized to an arbitrary objective trajectory. By imposing the open-loop control on the whole network together with the feedback control only on a small fraction of the nodes, an easy-to-verify sufficient condition is derived to guarantee the asymptotic synchronization of the complex network under study. Furthermore, to decrease the feedback control gains, the idea of adaptive control scheme is combined together, and the verified conditions are further weakened. Finally, by introducing the impulses to the open-loop network and using the improved Halanay inequality, other novel synchronization criteria are developed for the complex network. Comparisons of the obtained theoretical results as well as the detail pinning schemes are also given. Numerical examples of the undirected scale-free network and the directed small-world network are illustrated to demonstrate the applicability and efficiency of the proposed theoretical results.     

Explicit condition for consensus of third-order discrete-time multi-agent systems without accelerated velocity measurements

This paper investigates the consensus problem for third-order discrete-time multi-agent systems in directed networks. For the case when each agent can only receive the information of position and velocity from its neighbors, necessary and sufficient conditions for consensus have been proposed. In contrast to the preceding work, we not only present the exact consensus value, but also illustrate the influence of scaling parameters and nonzero eigenvalues of the involved Laplacian matrix on consensus. Two numerical examples are given to demonstrate the effectiveness of the obtained results.     

基于耦合网络的社交网络舆情传播模型研究

[目的]为了研究社交网络以及研究微博网络与微信网络之间舆情的传递过程。[方法]利用无标度有向网络和BA网络分别模拟微博网络和微信网络环境,通过特定的连接关系设计了耦合网络载体,在SEIR模型的基础上,充分分析了用户的传播心理,考虑到了个体具有兴趣衰减效应以及记忆效应等特征,构建了基于耦合网络的社交网络舆情传播模型。[结果]实验结果表明,构建的双层社交网络舆情传播模型能较好地反映现实生活中的舆情传播过程,用户在多层社交网络之间的互动加速了舆情信息的流动,扩大了舆情信息的影响力,层间传播阈值的控制是管理多层社交网络舆情传播的关键。     

Reset output feedback control of cluster linear multi-agent systems

In this study, the distributed output consensus control issue is investigated for a class of linear cluster multi-agent systems (CMASs) under the control strategy of the reset observer. We consider a communication network consisting of several clusters, each of which is directed and contains a leader. The interactions among agents include continuous-discrete hybrid communication. Specifically, an instantaneous connectivity only exists between the clusters at discrete moments, called the reset time sequence. At the reset time, an instantaneous fixed directed network is formed such that only the leaders will consider the available information of neighboring leaders to reset their own states. During non-reset intervals, only the intra-clusters are connected while the inter-clusters are equivalent to a disconnected network topology. Considering that in practice, the state information may be partially unavailable, only the relative output information is utilized to estimate the unavailable state and thus control protocols are developed with the help of the reset full-order and reduced-order observers, respectively. The stability of the closed-loop CMAS at both the reset time and non-reset intervals is studied based on Lyapunov analysis. The consensus value depends only on the initial conditions and the network topology involved, and not on the reset time sequence. Finally, numerical simulations are provided to illustrate the theoretical results.     

基于复杂网络的高技术企业联盟知识扩散AIDA模型与实证研究

知识通过网络可实现快速扩散,高技术企业联盟是知识扩散的重要主体。借鉴疾病传播的SIRS原理构建的高技术企业联盟知识扩散AIDA模型揭示了联盟网络的知识扩散机理与特性,以TD-SCDMA产业联盟为样本的实证分析表明高技术企业联盟知识扩散具有小世界性质、无标度特性和社区结构,对于探索增强联盟稳定性和知识创新效率,促进可持续发展具有重要启示。     

A new distributed Kalman filtering based on means-quare estimation upper bounds

In this paper, a novel distributed Kalman filter consisting of a bank of interlaced filters is proposed for a signal model whose dynamic equation and measurement equation are coupled. Each of the interlaced filters estimates a part of state rather than the global state using its and its neighbor information, which is different from other distributed filters already existed (e.g., distributed Kalman filter based on diffusion strategy or consensus strategy, distributed fuzzy filter and distributed particle filter with Gaussian mixer approximation, etc). This relieves the calculation and communication burden in networks. In addition, the proposed distributed Kalman filtering contains no consensus strategies, which is useful in some cases since consensus usually requires an infinite number of iterations.