非连续Lur’e时滞网络的有限时间聚类同步与自适应控制

本文主要研究一类由非恒同非连续Lur’e系统耦合而成复杂动态网络的自适应有限时间聚类同步问题.首先,通过引入Filippov微分包含理论和测度选择定理,本文设计了一类有效的牵制反馈控制器,该控制器只控制当前聚类中与其他聚类有直接连接的部分节点.为了有效节省控制成本,本文基于反馈控制强度设计了一类自适应更新定律以获取实现网络同步的最优控制强度.其次,利用有限时间稳定性理论和Lyapunov稳定性定理,本文得到时变时滞耦合和非线性耦合Lur’e网络实现有限时间聚类同步的判定条件,并给出该网络达到聚类同步的收敛时间估计.最后,通过一个算例仿真验证了本控制方案和同步判据的有效性及正确性.     

时滞Lur'e网络的事件触发脉冲自适应同步控制

本文研究了一类带有混合时变时滞Lur''e网络的全局同步及其脉冲自适应控制问题. 首先, 为实现网络的全局指数同步并有效避免控制器连续控制, 设计了一类基于事件触发的脉冲反馈控制器. 同时, 为获得最优控制强度,针对反馈控制输入设计了一种自适应更新定律并实现脉冲控制与反馈控制的动态平衡. 其次, 基于推广的比较原理以及参数变分策略, 提出了该控制策略下的Lur’e网络实现全局指数同步的充分判定条件, 并精确给出了指数同步的收敛速度. 最后, 通过相应的仿真算例来验证本文提出的控制方案和理论分析的正确性和有效性.     

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.     

基于非线性牵制控制的分数阶混沌网络聚同步

针对分数阶混沌复杂网络,提出一种非线性牵制控制策略实现网络聚同步.根据网络结点的不同属性,只对群间点施加非线性控制,然后基于分数阶系统稳定性理论,给出了实现聚同步的充分条件.数值仿真验证了该聚同步方案的有效性和正确性,同时深入讨论了控制增益和耦合强度等对聚同步的影响.     

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.     

虚拟化网络奇异节点反馈牵制控制仿真

虚拟化网络分析有利于解决复杂系统的控制问题,但是现有虚拟化网络研究主要针对非奇异网络,无法有效应用于包含奇异节点的网络处理.为解决上述问题,基于节点间的多重关联关系构造了奇异网络模型,分析领导节点以及网络偏差模型.基于模型分析设计了牵制控制算法,利用节点状态以及彼此存在的关联关系,通过牵制节点的改变来实现对全部节点的整体控制.根据偏差系统推导出反馈控制器,利用Laplacian矩阵确定牵制节点,并利用克罗内克积与线性微分计算得到合理的反馈增益系数,从而确保反馈牵制控制效果.通过算例仿真,方法能够针对节点的奇异性准确构造虚拟化网络模型,并根据网络关联性与密度的具体情况对牵制控制强度进行调整,实现系统的快速有效同步控制,显著降低了系统控制的偏差,提高了系统控制的鲁棒性和平稳性.     

高阶网络牵制控制中单纯形的选择

随着网络科学的发展,普通网络无法描述多个个体间的交互作用,这就有必要引入高阶网络.高阶网络能够刻画普通网络无法描述的网络特征,其中单纯形(2阶以上)扮演着关键角色.牵制控制具有“四两拨千斤”的作用,在高阶网络中只需牵制一部分单纯形就能达到同步.但如何选取合适的单纯形进行牵制控制,是一个充满挑战而又全新的课题.本文给出高阶网络达到同步的自适应牵制控制律,并提出如何选择合适的单纯形进行牵制,选择方式由高阶网络广义Laplacian矩阵次小特征值对应的单位特征向量分量决定.数值仿真结果表明该方法简单有效,牵制控制效果与单纯形选择方式一致.     

一种基于能量指数的复杂网络牵制控制策略

针对复杂大系统控制中,现有牵制控制策略仅依据拓扑结构而存在的不足和控制器设计中控制参数选择简单(视为常数)的问题,引入了能量指数的概念,提出一种新的牵制控制策略—–能量指数法.该方法同时考虑节点对于网络的贡献力和节点的网络特性,给出了引入能量指数后的网络动态模型描述,并将节点能量指数用于自适应控制器设计,得到了控制律设计新方法.与现有方法比较,所提方法可使系统收敛更快,更容易实现同步,从而表明基于能量指数的牵制策略和自适应控制器设计方法均是有效的,在电力、交通以及传染病防治等各种复杂网络中都具有实际应用价值.     

一类具有多种耦合时滞的复杂动态网络的牵制同步

针对一类由Lur'e系统组成的具有多种耦合时滞的加权复杂动态网络,研究其同步问题.只对网络中的一部分节点进行控制,从而使整个被控网络达到同步.基于绝对稳定性理论.得到了保证复杂网络实现全局同步的时滞独立判据.仿真中以蔡氏振荡器组成的复杂网络为例,验证了所提方法的有效性,且表明在某些特殊情况下,只需控制一个节点便可使整个网络达到同步.     

不同节点动态的复杂网络外部同步牵制控制

研究节点动态不同的两个复杂网络的外部同步问题。运用牵制控制方法,网络模型选取节点输出线性耦合模型,基于输出控制思想,设计结构简单的牵制控制器,对响应网络中的部分节点施加输出反馈控制,使得两个复杂动态网络达到外部同步,即实现响应网络与驱动网络的渐近同步。根据李雅普诺夫稳定性理论,推出相应的同步准则,得到控制器参数选择条件。仿真时,驱动网络和响应网络分别选取Lorenz系统和Lu系统,对全局耦合网络和最近邻耦合网络两个典型网络拓扑进行仿真,验证了所提方法的有效性。     

基于自适应事件触发牵制控制的多时滞随机耦合神经网络簇同步

本文通过自适应事件触发牵制控制策略,研究了多时滞的随机耦合神经网络在均方意义下以指数速率进行簇同步的问题.在耦合神经网络中,同一簇中的节点只需与相应的孤立节点同步,而对于不同簇中节点之间的同步状态没有要求.首先,本文提出了一种事件触发牵制控制方法来解决耦合神经网络中节点数量众多、通讯复杂的问题.该方法不仅能减少耦合神经网络中控制器的数量,还可以减少控制信号的传输次数、减轻网络传输压力.然后根据M矩阵方法,建立了随机耦合神经网络均方指数稳定的充分条件.同时,利用自适应控制策略,给出了反馈增益的更新规律.最后,通过一个数值例子验证了所提出的自适应事件触发牵制控制策略的有效性和适用性.     

Distributed impulsive synchronization of Lur'e dynamical networks via parameter variation methods

This paper is devoted to investigating the exponential synchronization of coupled Lur'e dynamical networks with multiple time‐varying delays and stochastic disturbance. The problem studied in this paper could be regarded as a kind of leader‐following synchronization issue. As the networks may suffer from certain impulsive disturbance, an effective distributed impulsive control protocol is proposed to synchronize the stochastic Lur'e dynamical networks. According to the comparison principle, the average impulsive interval, and the extended formula for the variation of parameters, sufficient conditions are derived for successful achievement of the network synchronization with consideration to different functions of impulsive effects. Furthermore, the exponential convergence rate is obtained based on the impulsive solution equation. In addition, finally, some numerical simulations are given to illustrate the validity of the control scheme and the theoretical analysis.     

Pinning synchronization of complex delayed dynamical networks via generalized intermittent adaptive control strategy

In this paper, the problem of pinning synchronization for delayed complex directed networks via generalized intermittent adaptive control strategy is considered. First, a dynamical mode of delayed network is investigated. Second, a generalized intermittent adaptive control strategy which unified the traditional periodic intermittent control and the aperiodic case is introduced. Additionally, by constructing a piecewise Lyapunov auxiliary function and making use of piecewise analysis technique, some effective and novel criteria to ensure the global synchronization of delayed complex networks based on the designed control protocols are obtained. Finally, an example with numerical simulations is provided to demonstrate the validness of the theoretical results proposed scheme.     

Robust cooperative output regulation of heterogeneous Lur'e networks

In this paper, we study robust cooperative output regulation problems for a directed network of Lur'e systems that consist of a nominal linear dynamics with an unknown static nonlinearity around it through negative feedback. We assume that the linear part of each agent is identical, but the nonlinearities are allowed to be different for distinct agents. In this sense, the network is heterogeneous. As is common in the context of Lur'e systems, the unknown nonlinearities are assumed to be sector bounded within one given sector. The interconnection graph among these agents is assumed to contain a directed spanning tree. Similar to classical output regulation problems, there is a virtual exosystem generating a reference signal in which all the agents are required to track cooperatively. Our designed distributed dynamic state/output feedback protocol makes a copy of the reference signal at each agent asymptotically, and then the robust cooperative output regulation problem becomes a robust tracking problem that can be handled by each agent via local information. It turns out that our cooperative protocols are fully distributed. Sufficient conditions on the existence of output synchronization protocols are given along with some discussions on these conditions. Finally, two simulation examples illustrate our design. Copyright © 2016 John Wiley & Sons, Ltd.     

Synchronization of complex networks with coupling delays via adaptive pinning intermittent control

The problem of exponential synchronization for a class of general complex dynamical networks with nonlinear coupling delays by adaptive pinning periodically intermittent control is considered in this paper. We use the methods of the adaptive control, pinning control and periodically intermittent control. Based on the piecewise Lyapunov stability theory, some less conservative criteria are derived for the global exponential synchronization of the complex dynamical networks with coupling delays. And several corresponding adaptive pinning feedback synchronization controllers are designed. These controllers have strong robustness against the coupling strength and topological structure of the network. Using the delayed nonlinear system as the nodes of the networks, a numerical example of the complex dynamical networks with nonlinear coupling delays is given to demonstrate the effectiveness of the control strategy.     

Adaptive aperiodically intermittent control for pinning synchronization of directed dynamical networks

In this paper, we investigate the pinning synchronization of directed complex network with time‐varying delay under the adaptive aperiodically intermittent control. First, the model of a directed complex network is established, the interaction graph of which is not required to contain a directed spanning tree, and for which an adaptive aperiodically intermittent feedback controller is well designed. In addition, based on the Lyapunov function method and linear matrix inequality technique, several asymptotical synchronization criteria are derived via an aperiodically intermittent strategy, which is superior to the periodical scheme. Moreover, the adaptive strategy providing the exponential convergence rate and the pinning algorithm demonstrating how to select pinned nodes are presented. Finally, numerical examples are provided to illustrate the effectiveness of the derived theoretical results.     

Cluster synchronisation of directed complex dynamical networks with nonidentical nodes via pinning control

In this article, we study the cluster synchronisation problem of directed complex dynamical networks through controlling some specific nodes. This method explains which nodes should be chosen as pinned candidates. Owing to the special structure of cluster network, the number of such nodes is extremely small. In our model, we consider a directed network whose nodes in different clusters are nonidentical. Then some sufficient conditions to guarantee cluster synchronisation in the coupled network are presented. Finally, numerical examples are given to verify our theoretical analysis.     

Robust pinning synchronization of complex cyberphysical networks under mixed attack strategies

This paper is concerned with the robust pinning synchronization control problem in complex cyberphysical networks under mixed attacks. The channels for transmitting control input signals and receiving information agent are assumed to be independent of each other and both can be destroyed by frequently occurred attacks. After the attacks, a repairing cell will be instantly activated until the communication topology is restored to the initial state. Assume that broken‐down nodes remain partial function. Moreover, feedback gain matrices and coupling strengths will be designed by some algorithms. By dint of geometrical method and inequality technique, sufficient conditions are established to guarantee robust synchronization for the complex cyberphysical networks. Finally, a simulation example is utilized to illustrate the obtained results.     

一种新的复杂动态网络学习控制的自适应同步算法

提出了一种新的具有未知时变参数复杂动态网络同步的自适应学习控制方法.运用重新参数化技术,设计周期时变参数的自适应学习律、常参数的更新律以及自适应控制策略确保同步误差渐近收敛.通过构造复合能量函数给出同步的一个充分条件.最后给出一个复杂网络的例子验证所提方法的有效性.