具有时变拓扑结构的复杂网络的牵制控制

研究了一类具有时变拓扑结构的线性延迟耦合的复杂网络模型,网络的内、外耦合矩阵都具有时变性,建立了一个新的混沌动力学模型,结合线性反馈控制、牵制控制等方法,运用Lyapunov稳定性理论得到了新的网络同步准则,数值仿真验证了结论的有效性。     

离散和分布时变时滞混沌神经网络广义投影同步

研究一类离散和分布时变时滞的混沌神经网络的广义投影同步问题.利用非线性观测器方法实现同步十分简单,且利用极点配置技术,可通过调整特征值来调节同步速率的快慢.与一般混沌神经网络模型相比,带有离散和分布时变时滞的混沌神经网络模型更为一般,同时反同步和完全同步是广义投影同步的特例.最后,提出基于广义投影同步的离散和分布时变时滞混沌神经网络的保密通信方案,给出两个数值仿真例子验证结果的有效性.     

Almost Automorphic Solutions for Quaternion-Valued Hopfield Neural Networks with Mixed Time-Varying Delays and Leakage Delays

This paper considers a class of quaternion-valued Hopfield neural networks with mixed time-varying delays and leakage delays. By utilizing the exponential dichotomy of linear differential equations, Banach's fixed point theorem and differential inequality techniques, the authors obtain some sufficient conditions to ensure the existence and global exponential stability of almost automorphic solutions for this class of quaternion-valued neural networks. The results are completely new. Finally,the authors give an example to illustrate the feasibility of the results.     

Finite-Time and Fixed-Time Synchronization of Inertial Neural Networks with Mixed Delays

This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities,some new and effective criteria are obtained for ensuring the finite-time synchronization. Finally, three numerical examples are also given at the end of this paper to show the effectiveness of the results.     

General Decay Synchronization for Recurrent Neural Networks with Mixed Time Delays

This paper studies the general decay synchronization(GDS) of a class of recurrent neural networks(RNNs) with general activation functions and mixed time delays. By constructing suitable Lyapunov-Krasovskii functionals and employing useful inequality techniques, some sufficient conditions on the GDS of considered RNNs are established via a type of nonlinear control. In addition, one example with numerical simulations is presented to illustrate the obtained theoretical results.     

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs, a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents’ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered. The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.     

The Module-Phase Synchronization of Complex-Valued Neural Networks with Time-Varying Delay and Stochastic Perturbations

The problem of exponential module-phase synchronization of complex-valued neural networks (CVNNs) with time-varying delay and stochastic perturbations was investigated. The model of CVNNs with time-varying delay and stochastic perturbations was considered. The error system was deduced and the module-phase synchronization was defined. Based on the principle of Lyapunov stability theory, the appropriate controller was designed to control the CVNNs. Finally, the effectiveness and reliability of the method were verified by the numerical simulations.

     

复杂网络的同步和拓扑结构的识别

简要介绍中国在复杂网络同步和拓扑结构识别方面的研究进展,特别是课题组在这些方面的工作.     

复杂网络的同步与复杂多个体系统的一致性

简要的回顾过去10年课题组在复杂网络的同步与复杂多个体系统的一致性研究方面的主要进展,同时展望该领域将来发展的趋势与挑战.     

Pinning Synchronization of Coupled Oscillators with Paired Topologies

This paper investigates the pinning synchronization of a group of coupled oscillators, where both the dissipative and restorative interactions are taken into consideration. The paired coupling topologies are introduced to capture this feature of the dynamics. To realize the synchronization of the coupled oscillators, the pinning control is introduced, and two pinning criteria are proposed to ensure the synchronization. Both these two proposed criteria provide sufficient and necessary conditions for pinning synchronization of the coupled oscillators with paired topologies. Simulation examples are illustrated to verify the proposed theoretical results.

     

不确定复杂网络的广义矩阵投影同步

基于Lyapunov稳定性理论,研究了不确定复杂网络的广义矩阵投影同步,每个网络的拓扑结构不恒等且维数也不同。在节点参数未知的情况下,通过设计自适应控制器实现了两个不同的变时滞复杂网络的广义矩阵投影同步,未知参数可以辨识。此外,对于未知的驱动网络及给定的广义矩阵,构造了实现广义矩阵投影同步的响应网络,不仅可以对该驱动网络进行同步控制达到预期效果,而且能对未知参数进行辨识确定网络结构。最后数值仿真验证了方法的有效性和可行性。     

复杂网络输出同步及稳定性分析

针对现实复杂网络系统的状态经常难以观测,甚至观测不到,而有时仅部分状态能达到同步就能满足需要的情况,讨论了复杂网络输出同步问题.首先提出了复杂网络的输出同步概念,然后考虑了输出矩阵为奇异和非奇异的两种情况下的稳定性问题,给出了输出达到同步的几个充分条件.最后给出算例表明了在不满足状态同步的情况下,可实现复杂网络系统输出同步.     

复杂动力网络的数学模型与同步准则

许多自然和人造的网络都属于复杂网络,它们具有复杂的招朴结构和大量的节点.人们提出了许多数学模型来描述各种各样的复杂网络,探讨复杂网络的动力和集群行为.简要地回顾几个典型的复杂动力网络模型.基于提出的时变复杂动力网络模型,给出了几个基本的网络同步准则.最后给出了一个简单的例子加以说明.     

Global Asymptotic Synchronization of a Class of BAM Neural Networks with Time Delays via Integrating Inequality Techniques

In this paper, the authors are concerned with global asymptotic synchronization for a class of BAM neural networks with time delays. Instead of using Lyapunov functional method, LMI method and matrix measure method which are recently widely applied to investigating global exponential/asymptotic synchronization for neural networks, two novel sufficient conditions on global asymptotic synchronization of above BAM neural networks are established by using a kind of new study method of global synchronization: Integrating inequality techniques. The method and results extend the study of global synchronization of neural networks.     

Predictive Control of High-Order Fully Actuated Nonlinear Systems with Time-Varying Delays

Journal of Systems Science and Complexity - This paper investigates the control problem of high-order fully actuated nonlinear systems with time-varying delays in the discrete-time domain. To make...     

离散神经网络的全局收敛性

应用能量函数,建立了离散的细胞神经网络与离散的Ｈｏｐｆｉｅｌｄ 神经网络全局收敛的充分条件,其结果推广了最近文献中某些已知的结果。     

Fixed-Time Synchronization of Complex Networks via Intermittent Control Without Sign Function

This paper investigates the fixed-time synchronization problem of complex networks. A novel switching controller is proposed to solve the problem. The designed controller in this paper only needs intermittently to pin a few of nodes, which could reduce the control time and save the system’s energy. Moreover, compared with the existing control methods for the fixed-time synchronization,the novel controller does not use the sign function, which could avoid the chattering behaviors. By constructing...     

Finite-Time Synchronization for a Class of Dynamical Complex Networks with Nonidentical Nodes and Uncertain Disturbance

This paper investigates the finite-time synchronization for a class of linearly coupled dynamical complex networks with both nonidentical nodes and uncertain disturbance. A set of controllers are designed such that the considered system can be finite-timely synchronized onto the target node.Based on the stability of the error equation, the Lyapunov function method and the linear matrix inequality technique, several sufficient conditions are derived to ensure the finite-time synchronization,and applied to the case of identical nodes and the one without uncertain disturbance. Also the adaptive finite-time synchronization is discussed. A numerical example is given to show the effectiveness of the main results obtained.     

群结构时空网络的同步

为了研究群结构时空网络中的同步现象,运用线性稳定性分析方法和强耦合极限近似,得到时空网络中群同步的本征值关系、拓扑条件及比值条件,给出了判断时空网络是否能发生群同步的判据,并在具体的一般网络中得到验证。发现了小集团结构的重要性,它们可以决定如何在各个群之间加入连接才能达到群同步以及达到群同步的最好的连接方式。通过观察其中最大的小集团,可以判断群同步发生的临界耦合强度。给出了同步相图,整个时空网络存在5个状态：完全不同步状态（US）、群同步状态（GrS）、群内同步状态（IS）、完全同步状态（CS）和过渡状态。当把两个群构成的网络扩展到多个群,扩展到整个二维时空,可以看到不同的斑图转换,得到网络从完全不同步到完全同步的多种路径。     

基于模糊模型的不确定时变时滞混沌系统同步

针对存在参数摄动、外扰动等不确定因素的时变时滞混沌系统的同步问题,基于Lyapunov-计的模糊控制器结构简单,且该方法适用于绝大多数变时滞混沌系统的同步控制.仿真结果表明所提出的控制方法是有效的.