复杂动态网络自适应有限时间同步控制

本文利用自适应控制的方法,研究了复杂动态网络有限时间同步控制问题.针对网络的耦合权重已知和耦合权重未知两种情况,分别设计了相应的自适应控制器和参数自适应律.利用有限时间稳定性定理和Lyapunov稳定性理论,证明了复杂动态网络的误差动态系统是有限时间稳定的,并给出了同步过渡时间上界的估计.最后,利用数值算例验证了本文结论的有效性.     

基于K-means聚类和数据场理论的复杂网络社团结构探寻

探寻社团结构是研究复杂网络结构与功能之间关系的基础.提出和分析了基于K-means聚类的社团探寻算法和基于数据场理论的社团探寻算法,并通过实验仿真验证了这两种算法的有效性.在仿真中发现并验证了社团内部比整个网络具有更加鲜明的小世界效应,这说明在网络控制中,在相同的耦合强度下,对社团的同步控制比对整个鲻网络的同步控制更容易实现.     

复杂网络特性对大规模多智能体协同控制的影响

随着分布式多智能体系统应用领域和系统规模的不断扩大,网络特性已成为影响系统性能的一个重要因素.通过研究和分析复杂网络特性对大规模分布式多智能体系统协同控制的影响,对多智能体系统性能的影响做出系统性分析,同时为提出大规模多智能体组织结构的优化算法提供依据.主要针对随机网络、小世界网络、网格网络和无尺度网络这4种典型复杂网络特性,从理论和仿真两方面进行分析.在理论方面,通过基于马尔可夫链的信息传输过程在不同网络结构下的建模,对比分析了信息无偏随机游走模型和智能决策模型下的传输效率.在仿真建模中,主要从智能体间信息传输效率、不同应用领域中集成协同控制效率、对网络故障恢复的影响这3个典型的多智能体系统协同控制应用对比分析复杂网络特性对系统性能的影响.研究结果表明,复杂网络特性如小世界和无尺度特性可以在相同的控制策略下形成明显的性能差异,如果设计合理的控制算法,复杂网络结构将有助于多智能体系统性能的提升.     

时变内耦合复杂网络的平衡态同步smart变结构控制

当前同步控制问题是复杂网络研究的热点之一. 本文针对具有时变内耦合结构的复杂网络, 利用结点混沌动态的各态历经性, 通过构造合适的滑模面, 提出了smart变结构控制器的设计策略. 该策略可使复杂网络动态行为趋向于所构造的全局吸引区域, 从而最终实现复杂网络在平衡态的渐近同步. 最后, 基于3种不同拓扑结构的Lorenz结点动态的复杂网络进行仿真实验表明该控制方案具有较好的鲁棒性和有效性.     

基于复杂网络理论的计算机网络拓扑研究

复杂网络理论是一门新兴学科。随着计算机网络的快速发展,网络结构日益复杂,使得传统的随机网络模型已很难对其拓扑特性作出客观的描述,因此,复杂网络理论为计算机网络拓扑的研究提供了一个新的视野和思路。文章对复杂网络理论作了介绍,综述了当前基于复杂网络理论计算机网络拓扑研究的状况并指出了其中存在的问题;强调将复杂网络理论应用到计算机网络拓扑研究当中的必要性。最后对复杂网络理论在未来计算机网络拓扑研究中的可能应用方向作了总结。     

时延复杂网络的自适应周期间歇同步控制

研究同时具有耦合时延和节点时延复杂网络的自适应周期间歇同步控制问题.运用 Lyapunov 稳定性理论,自适应控制、牵制控制和间歇控制方法,给出保证该时延复杂网络全局指数同步、且保守性更小的判定准则,并给出相应的自适应和牵制自适应间歇同步控制器设计,该控制策略对节点间的耦合强度和网络的拓扑结构等具有较强的鲁棒性.最后以时延非线性动力系统为节点对复杂网络进行数值仿真,验证了结论的正确性和有效性.     

复杂网络研究进展:模型与应用

作为研究各种复杂系统的一种通用工具,复杂网络已经在许多学科中产生了深刻地影响,引起了各领域学者的广泛关注.本文全面地介绍复杂网络的各种主要统计特性和最具有代表性的网络模型,并且对计算机科学中关注的语言网络,Internet和P2P这些现实网络,从复杂网络的角度进行分析,展示了复杂网络理论和方法在这些领域中的应用和得到的重要结果.     

网络安全的随机模型方法与评价技术

随着网络系统逐渐复杂和庞大,特别是网络攻击和破坏行为的日益普遍和多样,网络安全性面临严峻的挑战．网络安全性研究已经成为国际上重大的科学问题之一,也是影响社会经济发展和国家发展战略的重要因素．文章综述了网络安全性的随机模型与评价技术等方面的研究工作,介绍了该领域的研究现状与进展,总结了网络安全性随机模型的若干研究方法和评价技术,分析了网络的可生存性．基于这些讨论,展望了未来网络安全性研究的新方向．     

基于复杂网络的纽约轨道交通网络特性分析

现有的轨道交通网络建模研究大多建立无权网络模型,不能很好地反映网络特征。本文以纽约轨道交通网络为研究对象,采用复杂网络理论和Space L方法,考虑到2个站点之间可能存在多条线路的情况,构建纽约轨道交通加权网络模型,利用复杂网络的相关特性指标分析纽约轨道交通网络的特性。与无权网络相比可知,纽约轨道交通加权网络的权重与拓扑具有一定的关联性,该网络同时具有小世界和无标度特性。并通过随机攻击及多种蓄意攻击策略研究纽约轨道交通网络的鲁棒性。     

时变复杂动力学网络的同步控制

研究时变复杂动力学网络的同步控制问题.假定网络模型中的同步轨迹及耦合配置矩阵、内部耦合矩阵的各元素均有界,当这些界值可以预估或不确定时,分别应用线性反馈控制和自适应反馈控制策略使该网络实现全局同步.通过构造Lyapunov函数,证明了对于任意初始状态的时变复杂动力学网络模型在相应的控制手段下总可以实现渐近同步.特别是设计的自适应反馈控制策略对网络的拓扑结构、节点间的耦合强度及时滞等因素表现出较强的鲁棒性.数值仿真证实了上述结论的有效性.     

A time-varying complex dynamical network model and its controlled synchronization criteria

Today, complex networks have attracted increasing attention from various fields of science and engineering. It has been demonstrated that many complex networks display various synchronization phenomena. In this note, we introduce a time-varying complex dynamical network model. We then further investigate its synchronization phenomenon and prove several network synchronization theorems. Especially, we show that synchronization of such a time-varying dynamical network is completely determined by the inner-coupling matrix, and by the eigenvalues and the corresponding eigenvectors of the coupling configuration matrix of the network.     

变时滞随机忆阻器神经网络的同步控制

在实现实际的复杂人工神经网络模型以及大规模集成电路时,随机噪声是不可避免的.因此,随机忆阻器神经网络具有重要的现实研究意义.针对变时滞随机忆阻器神经网络的同步控制问题,基于非光滑分析以及集值映射、随机微分包含的理论,利用Lyapunov函数和基本不等式的方法,设计了一个线性反馈控制器.通过恰当选择控制器增益,实现了随机忆阻器神经网络驱动系统与相应的响应系统之间的指数同步,所得到的结果保守性更小.最后,给出数值例子验证了理论结果的有效性.     

Adaptive synchronization of uncertain coupled stochastic complex networks

In this paper, the problem of adaptive synchronization of uncertain coupled complex networks is investigated. Some controllers and adaptive laws are designed to ensure achieving synchronization of a general complex network model. In particular, synchronization of coupled stochastic networks subject to random perturbations is studied, with a referenced node introduced as the target node for synchronization. An example is simulated on delayed neural networks coupled in a small‐world network topology, which demonstrates the feasibility and effectiveness of the proposed adaptive control method. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

复杂网络理论研究综述

当前,复杂网络已迅速形成了一门贯穿多领域的交叉性学科,其相关理论被应用于诸多领域.为了解复杂网络的研究现状,首先从复杂网络的定义与统计特性两个角度介绍了复杂网络的基本概念,然后列举了几种典型的复杂网络模型,以及在此基础上对其进行改进后所建立的模型并讨论其优缺点,围绕复杂网络结构特性与网络动力学两个方面进一步分析了当前复杂网络的研究现状并列举了近几年的研究成果,最后得出结论并对复杂网络未来的热点研究方向做出展望.     

Stochastic distribution synchronization and pinning control for complex heterogeneous dynamical networks

This paper investigates the stochastic synchronization and pinning control in the sense of probability distribution for a general model of complex heterogeneous dynamical networks subjected to stochastic disturbances. Some generic stochastic synchronization criteria are established for both cases of undirected and directed topology by using the ergodic theory on stochastic dynamical systems. Compared with most existing studies on the stochastic synchronization in the sense of mean square, it is demonstrated that the concept of stochastic distribution synchronization can well characterize the realistic structure and essential nature of complex practical stochastic systems. Subsequently, two representative examples of complex heterogeneous dynamical networks, namely coupled stochastic Duffing oscillators and coupled FitzHugh‐Nagumo neuron oscillators, are given to illustrate and numerically verify the theoretical results.     

大系统控制论与复杂网络——探索与思考

随着通信技术和网络技术的飞速发展, 在社会、经济乃至日常生活领域中, 出现了越来越多的复杂动态网络. 网络科学作为一门新兴的交叉学科, 对复杂动态网络性能特征、演化进程和控制方法的研究已取得了丰富的成果. 大系统控制论以高维动态大系统的行为分析和控制优化为主要研究内容, 应该能为复杂网络的研究提供有益的借鉴. 本文针对复杂动态网络研究的一些热点问题, 探索了用大系统控制理论和方法解决复杂网络结构分析和控制的可能性, 分析了面临的困难和应对的思路. 针对大规模复杂动态网络的控制和优化, 提出了集网络科学的宏观分析方法、控制科学的定量设计方法和信息科学的智能处理方法于一体的多层递阶结构.     

Synchronization in complex networks of phase oscillators: A survey

The emergence of synchronization in a network of coupled oscillators is a fascinating subject of multidisciplinary research. This survey reviews the vast literature on the theory and the applications of complex oscillator networks. We focus on phase oscillator models that are widespread in real-world synchronization phenomena, that generalize the celebrated Kuramoto model, and that feature a rich phenomenology. We review the history and the countless applications of this model throughout science and engineering. We justify the importance of the widespread coupled oscillator model as a locally canonical model and describe some selected applications relevant to control scientists, including vehicle coordination, electric power networks, and clock synchronization. We introduce the reader to several synchronization notions and performance estimates. We propose analysis approaches to phase and frequency synchronization, phase balancing, pattern formation, and partial synchronization. We present the sharpest known results about synchronization in networks of homogeneous and heterogeneous oscillators, with complete or sparse interconnection topologies, and in finite-dimensional and infinite-dimensional settings. We conclude by summarizing the limitations of existing analysis methods and by highlighting some directions for future research.     

Global Synchronization for Discrete-Time Stochastic Complex Networks With Randomly Occurred Nonlinearities and Mixed Time Delays

In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: 1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; 2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and 3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results.      

精分EEG脑网络同步稳定性研究

为了深入表征和刻画精神分裂症患者大脑活动时各个电极通道的状态变化，通过利用复杂网络同步稳定理论以及精分工作记忆实验范式对EEG信号进行分析。从复杂网络角度出发构建脑功能网络，并利用特征谱比值法分析脑网络及其同步性随时间的演化过程。对比实验表明精分患者和正常对照组同步能力具有很大差异且差异主要源于对应脑网络的一个局部化区域S的不同，并通过设计对比实验进一步验证此区域对脑网络同步影响的有效性。脑网络同步稳定区域S的发现对研究神经精神性疾病下脑网络的演化过程提供了新的思路。     

Pinning adaptive synchronization of a general complex dynamical network

There are two challenging fundamental questions in pinning control of complex networks: (i) How many nodes should a network with fixed network structure and coupling strength be pinned to reach network synchronization? (ii) How much coupling strength should a network with fixed network structure and pinning nodes be applied to realize network synchronization? To fix these two questions, we propose a general complex dynamical network model and then further investigate its pinning adaptive synchronization. Based on this model, we attain several novel adaptive synchronization criteria which indeed give the positive answers to these two questions. That is, we provide a simply approximate formula for estimating the detailed number of pinning nodes and the magnitude of the coupling strength for a given general complex dynamical network. Here, the coupling-configuration matrix and the inner-coupling matrix are not necessarily symmetric. Moreover, our pinning adaptive controllers are rather simple compared with some traditional controllers. A Barabási-Albert network example is finally given to show the effectiveness of the proposed synchronization criteria.