超混沌Chen系统和超混沌Rssler系统的异结构同步

用两种不同的方法———主动控制同步法和自适应控制同步法实现超混沌Chen系统和超混沌Rssler系统的异结构同步,各自设计了不同的控制器,使得响应系统与驱动系统同步.当参数已知时,采用主动控制法,方法简单有效且不需要构造Lyapunov函数,实现同步的时间短;当系统参数未知或结构不确定时,基于Lyapunov稳定性理论,给出自适应同步控制器的系统设计过程和参数自适应律,使得系统达到同步同时识别未知参数.数值模拟验证了两种方法的有效性.     

不确定Chen系统的参数辨识与自适应同步

研究了不确定Chen系统的自适应同步和参数辨识，设计了自适应控制器和参数更新规则，理论证明了该控制器可使得两个Chen系统——驱动系统和未知参数的响应系统渐进地达到同步，并且可以辨识出响应系统的未知参数.数值模拟结果证明了该控制器的有效性. 关键词： 不确定Chen系统 自适应同步 参数辨识 控制器     

一类输出耦合时延复杂动态网络故障诊断研究

文章针对一类输出耦合时延复杂动态网络模型,考虑节点动力学参数未知的情况,基于网络外部同步思想,提出一种对该类复杂动态网络进行故障诊断的方法.利用节点的输出变量作为反馈变量设计控制器,根据Lyapunov稳定性理论,推导网络达到外部同步的条件.该方法可以实时监控时延网络拓扑结构的变化情况,对网络进行故障诊断.通过仿真验证本文方法的有效性. 关键词： 复杂动态网络 时延 故障诊断 节点参数     

超混沌Chen系统和超混沌R(o)ssler系统的异结构同步

用两种不同的方法--主动控制同步法和自适应控制同步法实现超混沌Chen系统和超混沌R(o)ssler系统的异结构同步,各自设计了不同的控制器,使得响应系统与驱动系统同步.当参数已知时,采用主动控制法,方法简单有效且不需要构造Lyapunov函数,实现同步的时间短;当系统参数未知或结构不确定时,基于Lyapunov稳定性理论,给出自适应同步控制器的系统设计过程和参数自适应律,使得系统达到同步同时识别未知参数. 数值模拟验证了两种方法的有效性.     

超混沌Chen系统和超混沌Rössler系统的异结构同步

用两种不同的方法--主动控制同步法和自适应控制同步法实现超混沌Chen系统和超混沌R(o)ssler系统的异结构同步,各自设计了不同的控制器,使得响应系统与驱动系统同步.当参数已知时,采用主动控制法,方法简单有效且不需要构造Lyapunov函数,实现同步的时间短;当系统参数未知或结构不确定时,基于Lyapunov稳定性理论,给出自适应同步控制器的系统设计过程和参数自适应律,使得系统达到同步同时识别未知参数. 数值模拟验证了两种方法的有效性.     

融合复杂动态网络的模型参考自适应同步研究

本文根据融合复杂网络边性质的不同, 运用网络拆分的思想研究了多重边融合复杂网络的自适应同步问题.基于Lyapunov稳定性理论,采用自适应反馈控制方法,在网络节点相同和不同的情况下,分别给出了网络全局同步的准则以及相应的控制器.最后,数值仿真验证了本文方法的有效性. 关键词： 融合网络 自适应同步 Lyapunov稳定性理论     

超混沌Chen系统和超混沌Roessler系统的异结构同步

用两种不同的方法——主动控制同步法和自适应控制同步法实现超混沌Chen系统和超混沌Roessler系统的异结构同步，各自设计了不同的控制器，使得响应系统与驱动系统同步．当参数已知时，采用主动控制法，方法简单有效且不需要构造Lyapunov函数，实现同步的时间短；当系统参数未知或结构不确定时，基于Lyapunov稳定性理论，给出自适应同步控制器的系统设计过程和参数自适应律，使得系统达到同步同时识别未知参数，数值模拟验证了两种方法的有效性。     

不同结构混沌系统的自适应同步和反同步

针对不同结构混沌系统的同步与反同步问题进行了研究.在系统参数已知时,采用主动控制法实现混沌系统的同步与反同步,并将主动控制器的设计方法进行了推广.在参数未知时,基于Lyapunov稳定性理论和自适应控制方法,给出了自适应控制器和参数自适应律,实现了参数均未知且结构不同的驱动系统和响应系统的同步与反同步.在控制器的设计过程中,将驱动系统和响应系统进行互换,讨论了互换前后的控制器和自适应律之间的关系.数值仿真结果说明了所提出设计方法的有效性. 关键词： 混沌同步 反同步 主动控制法 自适应控制法     

多重边融合复杂动态网络的自适应同步

基于网络拆分的思想对多重边融合复杂动态网络局部和全局的自适应同步进行了研究.通过给出严格的数学定义及假设,运用Lyapunov稳定理论得出了网络局部和全局的同步准则,给出了更为简单的网络同步的控制器.最后以Lorenz 系统为例进行数值仿真,验证了结论的正确性和有效性. 关键词： 多重边融合复杂动态网络 自适应同步 网络拆分 时滞     

具有双重时滞的时变耦合复杂网络的牵制外同步研究

针对同时具有节点时滞和耦合时滞的时变耦合复杂网络的外同步问题, 提出一种简单有效的自适应牵制控制方法. 首先构建一种贴近实际的驱动-响应复杂网络模型, 在模型中引入双重时滞和时变不对称外部耦合矩阵. 进一步设计易于实现的自适应牵制控制器, 对网络中的一部分关键节点进行控制. 构造适当的Lyapunov泛函, 利用 LaSalle不变集原理和线性矩阵不等式, 给出两个复杂网络实现外同步的充分条件. 最后, 仿真结果表明所提同步方法的有效性, 同时揭示耦合时滞对同步收敛速度的影响.     

Structure identification and adaptive synchronization of uncertain general complex dynamical networks

This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.     

Adaptive function projective synchronization of uncertain complex dynamical networks with disturbance

We investigate the problem of function projective synchronization (FPS) in drive-response dynamical networks with non-identical nodes. An adaptive controller is proposed for the FPS of complex dynamical networks with uncertain parameters and disturbance. Not only are the unknown parameters of the networks estimated by the adaptive laws obtained from the Lyapunov stability theory and Taylor expansions, but the unknown bounded disturbances are also simultaneously conquered by the proposed control. Finally, a numerical simulation is provided to illustrate the feasibility and effectiveness of the obtained result.     

Robust projective lag synchronization in drive-response dynamical networks via adaptive control

This paper investigates the problem of projective lag synchronization behavior in drive-response dynamical networks (DRDNs) with identical and non-identical nodes. An adaptive control method is designed to achieve projective lag synchronization with fully unknown parameters and unknown bounded disturbances. These parameters were estimated by adaptive laws obtained by Lyapunov stability theory. Furthermore, sufficient conditions for synchronization are derived analytically using the Lyapunov stability theory and adaptive control. In addition, the unknown bounded disturbances are also overcome by the proposed control. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Simulation results show the effectiveness of the proposed method.     

Synchronization of spatiotemporal chaos in a class of complex dynamical networks

This paper studies the synchronization of complex dynamical networks constructed by spatiotemporal chaotic systems with unknown parameters. The state variables in the systems with uncertain parameters are used to construct the parameter recognizers, and the unknown parameters are identified. Uncertain spatiotemporal chaotic systems are taken as the nodes of complex dynamical networks, connection among the nodes of all the spatiotemporal chaotic systems is of nonlinear coupling. The structure of the coupling functions between the connected nodes and the control gain are obtained based on Lyapunov stability theory. It is seen that stable chaos synchronization exists in the whole network when the control gain is in a certain range. The Gray--Scott models which have spatiotemporal chaotic behaviour are taken as examples for simulation and the results show that the method is very effective.     

Robust adaptive synchronization of uncertain and delayed dynamical complex networks with faulty network

<正>This paper presents a new robust adaptive synchronization method for a class of uncertain dynamical complex networks with network failures and coupling time-varying delays.Adaptive schemes are proposed to adjust controller parameters for the faulty network compensations,as well as to estimate the upper and lower bounds of delayed state errors and perturbations to compensate the effects of delay and perturbation on-line without assuming symmetry or irreducibility of networks.It is shown that,through Lyapunov stability theory,distributed adaptive controllers constructed by the adaptive schemes are successful in ensuring the achievement of asymptotic synchronization of networks in the present of faulty and delayed networks,and perturbation inputs.A Chua's circuit network example is finally given to show the effectiveness of the proposed synchronization criteria.     

Time correlations and persistence probability of a Brownian particle in a shear flow

This paper presents an adaptive lag synchronization based method for simultaneous identification of topology and parameters of uncertain general complex dynamical networks with and without time delays. Based on Lyapunov stability theorem and LaSalle??s invariance principle, an adaptive controller is designed to realize lag synchronization between drive and response systems, meanwhile, identification criteria of network topology and system parameters are obtained. Numerical simulations illustrate the effectiveness of the proposed method.     

Outer synchronization between two nonidentical networks with circumstance noise

This paper regards the outer synchronization between two delay-coupled complex dynamical networks with nonidentical topological structures and a noise perturbation. Considering one network as the drive network and the other one as the response network, the drive-response system achieves synchronous states through a suitably designed adaptive controller. The stochastic LaSalle invariance principle is employed to theoretically prove the almost sure synchronization between two networks. Finally, two numerical examples are examined in order to illustrate the proposed synchronization scheme.     

Exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and mode-dependent probabilistic time-varying delays

In this paper, the problem of exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and Mode-dependent probabilistic time-varying coupling delays is investigated. The sam- pling period is assumed to be time-varying and bounded. The information of probability distribution of the time-varying delay is considered and transformed into parameter matrices of the transferred complex dynamical network model. Based on the condition, the design method of the desired sampled data controller is proposed. By constructing a new Lyapunov functional with triple integral terms, delay-distribution-dependent exponential synchronization criteria are derived in the form of linear matrix inequalities. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.     

Finite-time complex projective synchronization of fractional-order complex-valued uncertain multi-link network and its image encryption application

Multi-link networks are universal in the real world such as relationship networks, transportation networks, and communication networks. It is significant to investigate the synchronization of the network with multi-link. In this paper, considering the complex network with uncertain parameters, new adaptive controller and update laws are proposed to ensure that complex-valued multilink network realizes finite-time complex projective synchronization (FTCPS). In addition, based on fractional-order Lyapunov functional method and finite-time stability theory, the criteria of FTCPS are derived and synchronization time is given which is associated with fractional order and control parameters. Meanwhile, numerical example is given to verify the validity of proposed finite-time complex projection strategy and analyze the relationship between synchronization time and fractional order and control parameters. Finally, the network is applied to image encryption, and the security analysis is carried out to verify the correctness of this method.