时滞神经网络双周期间歇控制滞后同步

提出了一个时滞神经网络周期间歇控制滞后同步策略,其间歇控制周期为两个不同的周期。利用Lyapunov稳定性理论,证明了时滞神经网络在此控制策略下能够实现同步,并获得了同步解全局指数稳定的充分条件。给出了一个仿真实例验证了控制方案的有效性。     

Exponential synchronization of Cohen-Grossberg neural networks via periodically intermittent control

In this paper, a class of Cohen-Grossberg neural networks with time-varying delays are studied by designing a periodically intermittent controller. Some novel and effective exponential synchronization criteria are derived by applying some analysis techniques. These results generalize a few previous known results and remove some restrictions on control width and time-delays. Finally, a chaotic Cohen-Grossberg neural network is represented to show the effectiveness and feasibility of our results.     

Exponential synchronization of inertial neural network with mixed delays via intermittent pinning control

This article considers the problem of exponential synchronization of inertial neural networks (INNs) with mixed delays via a novel hybrid control scheme consisting of pinning and periodic intermittent control. Both the discrete delay and distributed delay are taken into account in the network model. Through the proper variable substitution, the original system is transferred into a simply formed differential equation. Meantime, some new sufficient conditions are derived by the Lyapunov stability theory for the exponential synchronization of INNs. Eventually, numerical simulations are given to present the effectiveness of the theoretical method.     

具有间歇耦合的复杂动态网络量化同步分析

讨论了基于量化控制信号的间歇耦合复杂动态网络的同步动力学,根据脉冲间隔周期和量化器的特征,并利用稳定性理论和 Razumikhin 定理,分别给出了含时滞和不含时滞下的复杂动态网络同步化准则.网络节点间在一系列分段周期内有耦合,耦合过程中控制作用通过“对数量化器”对同步误差的反馈控制瞬态信号进行量化.所得理论结果进一步应用于由 Chua 混沌系统为动力节点所构成的复杂动态网络,数值模拟表明了所获理论结果的有效性.     

惯性忆阻神经网络固定时间抗干扰聚类同步控制

本文研究了具有外部干扰的惯性忆阻神经网络固定时间聚类同步控制问题. 通过设计一类经济型的固定 时间控制器, 保证了耦合网络系统在固定时间内以较少的能量消耗实现聚类同步. 为提高网络的普适性, 文中神经 网络的激活函数为非连续函数. 基于Filippov解理论以及固定时间控制理论, 获得了耦合网络的同步性判据, 给出了 收敛时间的具体上界, 验证了网络抗干扰能力. 最后, 通过数值仿真说明了理论结果的有效性.     

Semiglobal finite‐time synchronization of complex networks with stochastic disturbance via intermittent control

This paper focuses on the problem of semiglobal finite‐time synchronization of stochastic complex networks via an intermittent control strategy. By establishing a finite‐time criterion condition and a novel finite‐time ‐operator differential inequality, combined with convex techniques, some sufficient conditions are obtained to ensure finite‐time synchronization for stochastic complex networks with time delays. An effective controller is given to guarantee inner finite‐time synchronization, especially for a nondelayed dynamic system. This paper provides a simple controller. Finally, a numerical simulation is given to demonstrate the effectiveness of our results.     

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.     

事件触发下马尔可夫跳跃神经网络的随机同步

本文研究了事件触发机制下带有随机噪声的马尔可夫跳跃神经网络的随机同步问题.为了更有效地降低数据传输量和节约网络资源,本文采用了一种事件触发控制.当传输误差和状态误差满足触发条件时,数据才能够被传输,使得主从系统可以在有限的资源和带宽下实现同步.通过构建新的Lyapunov泛函,以及使用广义Dynkin公式和不等式分析方...     

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.     

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.     

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.     

具有时滞的Liao混沌神经元系统的自适应同步

针对一类具有时滞的部分参数未知的Liao混沌神经元系统,研究不同结构时滞Liao混沌神经元系统的自适应同步问题．基于Lyapunov稳定理论,给出了自适应控制器的设计方法及参数自适应律的解析表达式．所设计的控制器实用有效,易于实现,能够使具有时滞的两个不同结构的Liao混沌神经元系统渐近同步．仿真示例验证了该方法的有效性．     

Fixed‐time synchronization for complex‐valued BAM neural networks with time delays

In this paper, the fixed‐time synchronization for complex‐valued bidirectional associative memory (BAM) neural networks with time delays is studied. Based on the fixed‐time stability, the Lyapunov functional method and some inequality techniques, a new criterion is presented to guarantee that the addressed systems achieve synchronization in fixed time and a more accurate estimation independent of the initial conditions is given for the settling time. Meanwhile, a new nonlinear delayed controller different from the existing ones is designed. In the end, two numerical examples are provided to illustrate the effectiveness of the obtained result.     

具有混合时滞的四元数神经网络全局同步性控制

本文研究了具有混合时滞的四元数神经网络的全局同步性问题. 在不要求网络的激活函数可分离为两个复数或四个实数的情况下, 通过选取合适的 Lyapunov -Krasovskii 泛函, 并运用驱动-响应同步、自由权矩阵方法和矩阵不等式技巧, 给出了网络全局同步性的充要条件, 建立了同步控制器的设计方法. 给出的同步性判据是四元数和复数两种形式的线性矩阵不等式, 同时与已有的结果进行了对比. 最后通过一个数值仿真算例验证了所得结论的有效性.     

Stochastic synchronization of delayed multiagent networks with intermittent communications: An impulsive framework

This paper investigates the stochastic synchronization problem of delayed multiagent networks with intermittent communications. Two kinds of impulsive effects are taken into account, ie, impulsive controller (positive impulsive effect) and impulsive disturbance (negative impulsive effect). Impulsive controller allows the synchronization to be realized and requires only state information exchange at discrete time instants such that the communication cost of bandwidth is reduced. Meanwhile, impulsive disturbance is inevitable in most of practical systems and therefore is taken into consideration at discrete time instants. Sufficient conditions for synchronization are given in terms of the graph topology, the control coupling gains, and the individual agent dynamics parameters, which indicates that synchronization can be realized if the impulsive effects coefficients and communication rate are suitably selected. Simulation results verify the effectiveness of the proposed synchronization protocol.     

Exponential stabilisation of memristive neural networks under intermittent output feedback control

In this paper, the exponential stabilisation problem is studied for a general class of memristive time-varying delayed neural networks under periodically intermittent output feedback control. First, the periodically intermittent output feedback control rule is designed for the exponential stabilisation of the memristive time-varying delayed neural networks. Then, we derive stabilisation criteria so that the memristive time-varying delayed neural networks are exponentially stable. By the mathematical induction method and constructing suitable Lyapunov–Krasovskii functionals, some easy-to-check criteria are obtained to ensure the exponential stabilisation of memristive time-varying delayed neural networks. Finally, two numerical simulation examples are given to illustrate the validity of the obtained results.     

一类具有时滞的广义Hopf ield 神经网络的全局稳定性

通过引入能量泛函，分析了一类具有时滞的广义Hopfield神经网络的全局稳定性．从理论上给出了该类网络为全局稳定的充分条件，证明了当时滞满足一个可计算的边界条件时，具有时滞的该类神经网络与相应的无时滞网络具有同样的全局稳定特性．仿真结果进一步证明了结论的有效性。     

Cluster synchronization in an array of coupled stochastic delayed neural networks via pinning control

In this paper, cluster synchronization problem is studied for an array of coupled stochastic delayed neural networks by using pinning control strategy. Based on the free matrix approach and stochastic analysis techniques, some sufficient criteria are derived to ensure cluster synchronization of the network model if a single linear or adaptive feedback controller is added to each cluster. Furthermore, two specific methods are given to achieve desired cluster synchronization pattern. Finally, a numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.     

Passivity and robust synchronisation of switched interval coupled neural networks with time delay

This paper is concerned with passivity and robust synchronisation of switched coupled neural networks with uncertain parameters. First, the mathematical model of switched coupled neural networks with interval uncertain parameters is established, which consists of L modes and switches from one mode to another according to the switching rule. Second, by employing passivity theory and linear matrix inequality techniques, delay-independent and delay-dependent conditions are derived to guarantee the passivity of switched interval coupled neural networks. Moreover, based on the proposed passivity results, global synchronisation criteria can be obtained for switched coupled neural networks with or without uncertain parameters. Finally, an illustrative example is provided to demonstrate the effectiveness of the obtained results.     

多链接复杂网络指数同步的间歇事件触发控制

本文研究了基于间歇事件触发控制策略的延迟多链接复杂网络的指数同步问题, 设计了一种间歇动态事 件触发控制策略. 相比于间歇静态事件触发控制策略, 本文提出的控制策略是基于控制区间内的动态事件触发, 极 大地减少了事件触发次. 并且, 考虑的间歇控制的控制增益是自适应的, 这具有动态调整的作用. 基于图论和李雅 普诺夫方法, 本文给出了实现延迟多链接复杂网络指数同步的充分条件. 此外, 本文设计的控制策略能够排除Zeno 现象. 并且, 将理论结果应用于一类振子系统的指数同步问题. 最后, 文章给出相应的数值仿真来验证理论结果的有 效性和可行性.