Pinning control and synchronization on complex dynamical networks

This article offers a survey of the recent research advances in pinning control and pinning synchronization on complex dynamical networks. The emphasis is on research ideas and theoretical developments. Some technical details, if deemed necessary for clarity, will be outlined as well.     

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.     

Pinning control of a generalized complex dynamical network model

This paper investigates the local and global synchronization of a generalized complex dynamical network model with constant and delayed coupling. Without assuming symmetry of the couplings, we proved that a single controller can pin the generalized complex network to a homogenous solution. Some previous synchronization results are generalized. In this paper, we first discuss how to pin an array of delayed neural networks to the synchronous solution by adding only one controller. Next, by using the Lyapunov functional method, some sufficient conditions are derived for the local and global synchronization of the coupled systems. The obtained results are expressed in terms of LMIs, which can be efficiently checked by the Matlab LMI toolbox. Finally, an example is given to illustrate the theoretical results.     

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.     

Passivity-based control and synchronization of general complex dynamical networks

This paper presents some sufficient conditions for complex dynamical networks with and without coupling delays in the state to be passive. Based on the passivity property and linearization, control and synchronization of the dynamical networks are also addressed. An example and simulation results are included.     

具有时延性质的复杂网络牵制控制

该文主要是利用牵制控制方法对一类具有时延性质的复杂网络进行同步控制。该方法不同于最早的全局控制,仅是对网络中的部分节点进行控制。将这些节点的输出量的差值作为控制器从而达到等同于全局控制的效果。同时根据最新的网络结构可控原理计算出牵制控制所需要的最少节点数目,继而通过设定合适的Lyapunov函数,并基于稳定性和线性矩阵不等式等理论得出满足要求的控制器设计准则。最后,采用小世界模型进行仿真,进一步验证了结论的正确性。     

Synchronization of uncertain complex dynamical networks via adaptive control

In this paper, synchronization of an uncertain dynamical network with time‐varying delay is investigated by means of adaptive control schemes. Time delays and uncertainties exist universally in real‐world complex networks. Especially, parameters of nodes in these complex networks are usually partially or completely uncertain. Considering the networks with unknown or partially known nodes, we design adaptive controllers for the corresponding complex dynamical networks, respectively. Several criteria guaranteeing synchronization of such systems are established by employing the Lyapunov stability theorem. Analytical and numerical results show that the proposed controllers have high robustness against parameter variations including network topologies, coupling structures, and strength. Copyright © 2008 John Wiley & Sons, Ltd.     

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.     

Comparison between pinning control of different chaotic complex dynamical networks

The stabilization properties of various typical complex dynamical networks composed of chaotic nodes are theoretically investigated and numerically simulated in detail. Some local stability properties of such pinned networks are derived and the valid stability regions are estimated based on eigenvalue analysis. Numerical simulations of such networks are given to explain why significantly less local controllers are needed by the specifically pinning scheme, which pins the most highly connected nodes in scale-free networks, than that required by the randomly pinning scheme. Also, it is explained why there is no significant difference between the two schemes for controlling random-graph networks and small-world networks.     

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.     

Stability analysis and decentralized control of a class of complex dynamical networks

In this paper, stability analysis and decentralized control problems are addressed for linear and sector-nonlinear complex dynamical networks. Necessary and sufficient conditions for stability and stabilizability under a special decentralized control strategy are given for linear networks. Especially, two types of linear regular networks, star-shaped networks and globally coupled networks, are studied in detail. A dynamical network is viewed as a large-scale system composing of some subsystems, based on which the relationship between the stability of a network and the stability of its corresponding subsystems is investigated. It is pointed out that some subsystems must be unstable for the whole network to be stable in some special cases. Moreover, a controller design method based on a parameter-dependent Lyapunov function is provided. Furthermore, interconnected Lur’e systems and symmetrical networks of Lur’e systems are similarly studied. The test of absolute stability of a network of Lur’e systems is separated into the test of absolute stability of several independent Lur’e systems. Finally, several numerical examples are given to illustrate the theoretical results.     

Control of nonlinear dynamical systems using neural networks:controllability and stabilization

An attempt is made to indicate how practically viable controllers can be designed using neural networks, based on results in nonlinear control theory. The problem of stabilization of a dynamical system around an equilibrium point when the state of the system is accessible is considered. Simulation results are included to complement the theoretical discussions.     

概率布尔控制网络的集可控

本文研究概率布尔控制网络的集可控性问题.首先,利用矩阵半张量积方法,得到概率布尔控制网络的代数表示.其次,借助一个新的算子构造不同的可控矩阵,进而通过可控矩阵考虑自由控制序列和网络输入控制下概率布尔控制网络的集可控性问题,得到了概率布尔控制网络集可控性的充要条件.最后,给出数值例子说明本文结果的有效性.     

布尔 控制 网络 的集 成集 可控

集群运动的自组织控制相较于控制理论方法更具鲁棒性与灵活性,其中具有强大自组织特性的生物种群多表现为单体的等级交互,其特点是交互双方各自影响互不对称,由于信息交互繁杂导致构建等级交互模型仍充满挑战.鉴于此,使用深度学习技术分析红鼻鱼的集群运动实验数据,构建多参数输入的单体等级交互模型,有针对地设计成对交互的深度网络结构,并进行合理训练以获取交互模型,基于视觉压力挑选出关键邻居,将此模型用于该邻居的等级交互,相较于其他邻居选择方式,所提出智能控制方法与真实鱼类的集群运动具有较一致的宏观特性.仿真实验表明:所提出方法能扩展应用到更大规模的集群聚合运动控制中,使得单体仅利用局部信息即可实现大规模的集群运动;该方法具有使用简单、规模灵活、计算快速的特点,在多机器人控制、智能交通系统、饱和集群攻击以及多智能体物流等领域具有广阔的应用前景.     

多值逻辑网络的输出跟踪牵制控制

本文利用代数状态空间方法,研究了多值逻辑控制网络的输出跟踪牵制控制.首先利用矩阵的半张量积给出了带牵制控制的多值逻辑控制网络的代数表示.其次基于该代数表示,定义了一组合适的能达集,并建立了多值逻辑控制网络输出跟踪牵制控制器的设计方法.再次,利用多值逻辑哑算子的性质,给出了多值逻辑控制网络分布式输出跟踪控制问题可解的充要条件.最后将所得的理论结果应用于网络演化博弈的演化行为分析.     

概率布尔控制网络的弱能控性

本文研究了概率布尔控制网络的弱能控性,系统的弱能控性是概率布尔网络精确能控的一个推广.首先利用矩阵的半张量积和逻辑变量的向量表示,概率布尔控制网络被表示为离散时间动态系统.接着给出概率布尔控制网络弱能控的定义,从离散时间系统的结构矩阵出发,构造了最大概率转移矩阵,矩阵中的元素表示相应状态之间可能发生转移的最大概率,在此基础上研究了概率布尔控制网络的弱能控的条件,同时给出了两个状态弱能达时控制序列的设计算法.最后通过例子进一步解释了弱能控的概念和控制序列设计算法的有效性.     

Synchronization of stochastic complex dynamical networks under self‐triggered control

In this paper, we investigate the mean square exponential synchronization of stochastic nonlinear complex dynamical networks with or without communication delays. A new self‐triggered mechanism is proposed to reduce the amount of communication while preserving the desired system's performance. Under this mechanism, the next sampling instant is dynamically determined by the latest transmitted state rather than the online detection of the event‐triggered condition. Meanwhile, we show that the inter‐execution time of self‐triggered mechanism is bounded by a strictly positive constant, and the maximal allowable delay of the underlying system is given. A simulation is provided to illustrate the effectiveness of the proposed self‐triggered scenario. Copyright © 2016 John Wiley & Sons, Ltd.     

Improved results on synchronisation of delayed complex dynamical networks via sampled-data control

This paper focuses on the synchronisation problem of delayed complex dynamical networks via sampled-data control. A novel input-delay-dependent Lyapunov–Krasovskii functional (LKF) is constructed for the first time, which can make full use of the information on the input delay. To strengthen the combinations of the vectors in the resulting augmented vector, a new zero value equality is founded. Based on the input-delay-dependent LKF and zero value equality, synchronisation criteria are established. In comparison with some existing synchronisation criteria, the criteria in this paper are less conservative. The desired sampled-data controller is designed by solving a set of linear matrix inequalities. Finally, numerical examples are given to demonstrate the superiorities of proposed results.     

On controllability and stabilizability of probabilistic Boolean control networks

The controllability of probabilistic Boolean control networks(PBCNs)is first considered.Using the input-state incidence matrices of all models,we propose a reachability matrix to characterize the joint reachability.Then we prove that the joint reachability and the controllability of PBCNs are equivalent,which leads to a necessary and sufcient condition of the controllability.Then,the result of controllability is used to investigate the stability of probabilistic Boolean networks(PBNs)and the stabilization of PBCNs.A necessary and sufcient condition for the stability of PBNs is obtained first.By introducing the control-fixed point of Boolean control networks(BCNs),the stability condition has finally been developed into a necessary and sufcient condition of the stabilization of PBCNs.Both necessary and sufcient conditions for controllability and stabilizability are based on reachability matrix,which are easily computable.Hence the two necessary and sufcient conditions are straightforward verifiable.Numerical examples are provided from case to case to demonstrate the corresponding theoretical results.