用截面映象非线性延时反馈控制混沌

提出了利用相空间Poincare截面上的非线性延时反馈稳定微分动力系统混沌吸引子中不稳定周期轨道的新方法.以Henon映象和带注入信号的双光子激光系统为例，给出了理论分析和数值模拟结果．这种方法的主要特点是不需要获取混沌系统中不稳定周期轨道的任何信息，并且可以在混沌态的任意时刻施加控制作用．     

陈氏混沌系统的非反馈控制

通过对陈氏混沌系统施加非共振参数激励实现非反馈混沌控制.将远大于系统特征频率的周期信号作为控制输入，利用平均法和Lyapunov方法证明控制方案的可行性，并得出控制参数应满足的条件.数值研究表明此方法可以使受控系统迅速达到稳定状态，且具有较强的抗干扰性能.     

混沌神经网络的控制

提出了一种针对混沌神经网络的钉扎控制方法.利用此方法对混沌神经网络进行控制,使网络的输出稳定在网络的一个存储的模式上.实现了混沌神经网络的信息搜索,并对影响混沌神经网络控制效果的几个因素进行了讨论. 关键词： 混沌控制 混沌神经网络 钉扎控制方法     

简易混沌振荡器的混沌特性及其反馈控制电路的设计

研究了一个新的简易混沌振荡电路系统的稳定性和混沌特性,从理论上推导了该混沌振荡电路系统的稳定和混沌的条件,并对该系统进行了精确反馈线性化控制.最后,通过电路仿真实验和硬件实验验证了理论分析的准确性.     

不确定混沌系统的径向基函数神经网络反馈补偿控制

对不确定混沌系统控制问题, 研究了一种基于径向基函数神经网络(radial basis function neural network, RBFNN)的反馈补偿控制方法. 该方法首先用RBFNN对混沌系统的动力学特性进行学习, 然后用训练好的RBFNN模型对混沌系统进行反馈补偿控制. 该方法的特点是不需要被控混沌系统的数学模型,可以快速跟踪任意给定的参考信号. 数值仿真试验表明了该控制方法不仅具有响应速度快、控制精度高, 而且具有较强的抑制混沌系统参数摄动能力和抗干扰能力.     

混沌神经网络的动态阈值控制

提出了混沌神经网络的动态阈值控制方法, 将大脑脑电波的主要成分, 正弦信号作为控制变量实现对混沌神经网络内部状态的阈值动态改变, 从而达到了控制混沌神经网络混沌的目的. 利用该方法可以将混沌神经网络的输出稳定在一个与网络初始模式相关的存储模式和其反相模式上, 从而使混沌神经网络在模式识别、信息搜索等信息处理功能得以实现. 该控制方法不需要事先指定阈值, 是一种自适应方法, 符合实际人脑的思维运动. 关键词： 混沌控制 混沌神经网络 动态阈值控制 信息处理     

陈氏混沌系统的采样数据反馈控制

提出了基于采样数据反馈控制技术对陈氏混沌系统进行控制的理论.以给定的采样速率对陈氏混沌系统的输出进行采样.利用采样数据去构造离散时间控制算法,以达到将陈氏混沌系统控制到原点的目的.给出了被控制系统渐近稳定的理论证明,并给出了数值试验的结果. 关键词：     

混沌系统的遗传神经网络控制

提出遗传神经网络控制混沌新方法.将小扰动技术和周期控制技术结合起来，用遗传算法训练神经网络，使之成为混沌控制器.对Henon映射和Logistic映射的仿真结果说明控制器能产生小扰动控制序列信号，将混沌振荡转变成规则运动状态.该方法无需了解动态系统数学模型，具有一定抗噪声干扰能力，可将它推广应用到其他混沌系统的控制中. 关键词： 遗传算法 神经网络 混沌 周期控制     

全光学型延时反馈法控制外腔式半导体激光器的混沌

根据Pyragas连续反馈法控制混沌的原理，提出一种全光学型延时反馈法控制半导体激光器混沌的方案，用相干理论分析了该方案实现混沌控制的机理和条件，进行了计算机数值模拟，结果证明了该方案的有效性. 关键词：     

耦合映像格子中时空混沌的状态反馈控制

利用状态反馈的方法，实现了耦合映像格子中时空混沌的稳定控制.反馈方式可以是没有延迟的，也可以是有延迟的；控制方式可以是连续的，也可以是脉冲的.数值模拟结果证明了状态反馈方法的有效性. 关键词： 耦合映像格子 时空混沌 状态反馈控制     

Controlling chaos by a delayed continuous feedback in a gas discharge plasma

Control of chaos by a delayed continuous feedback is studied experimentally in a gas discharge plasma. The power spectrum, the maximum of Lyapunov exponents and the time series of the signals all indicate that the period-1 unstable periodic orbit is controlled successfully. The dependence of the control on the delay time and the feedback gain as well as the strength of white noise is also investigated in detail. The experimental results show that the scaling index of the control versus the strength of white noise is 1.995, which is very close to that obtained from the simple logistic map.     

Global impulsive exponential synchronization of stochastic perturbed chaotic delayed neural networks

In this paper, the global impulsive exponential synchronization problem of a class of chaotic delayed neural networks (DNNs) with stochastic perturbation is studied. Based on the Lyapunov stability theory, stochastic analysis approach and an efficient impulsive delay differential inequality, some new exponential synchronization criteria expressed in the form of the linear matrix inequality (LMI) are derived. The designed impulsive controller not only can globally exponentially stabilize the error dynamics in mean square, but also can control the exponential synchronization rate. Furthermore, to estimate the stable region of the synchronization error dynamics, a novel optimization control algorithm is proposed, which can deal with the minimum problem with two nonlinear terms coexisting in LMIs effectively. Simulation results finally demonstrate the effectiveness of the proposed method.     

Bifurcations and chaos control in discrete small-world networks

An impulsive delayed feedback control strategy to control period-doubling bifurcations and chaos is proposed. The control method is then applied to a discrete small-world network model. Qualitative analyses and simulations show that under a generic condition, the bifurcations and the chaos can be delayed or eliminated completely. In addition, the periodic orbits embedded in the chaotic attractor can be stabilized.     

Time-delay feedback control in a delayed dynamical chaos system and its applications

The feedback control of a delayed dynamical system, which also includes various chaotic systems with time delays, is investigated. On the basis of stability analysis of a nonautonomous system with delays, some simple yet less conservative criteria are obtained for feedback control in a delayed dynamical system. Finally, the theoretical result is applied to a typical class of chaotic Lorenz system and Chua circuit with delays. Numerical simulations are also given to verify the theoretical results.     

混沌时滞神经网络系统的反同步

利用状态观测器方法研究了一类带时滞的混沌神经网络系统的反同步问题.与应用于其他混沌系统的反同步方法相比,提出的方法更为简便,并且利用极点配置技术,只要通过调整特征值来实现反同步速率的快慢.最后,给出了数值例子和计算机仿真结果来验证该方案的有效性. 关键词： 混沌神经网络 状态观测器 极点配置技术 反同步     

随机参数Duffing系统中的随机混沌及其延迟反馈控制

研究了谐和激励下含有界随机参数Duffing系统(简称随机Duffing系统)中的随机混沌及其延迟反馈控制问题.借助Gegenbauer多项式逼近理论，将随机Duffing系统转化为与其等效的确定性非线性系统.这样，随机Duffing系统在谐和激励下的混沌响应及其控制问题就可借等效的确定性非线性系统来研究.分析阐明了随机混沌的主要特点，并采用Wolf算法计算等效确定性非线性系统的最大Lyapunov指数，以判别随机Duffing系统的动力学行为.数值计算表明，恰当选取不同的反馈强度和延迟时间，可分别达到抑制或诱发系统混沌的目的，说明延迟反馈技术对随机混沌控制也是十分有效的. 关键词： 随机Duffing系统 延迟反馈控制 随机混沌 Gegenbauer多项式     

Controlling chaos in RCL-shunted Josephson junction by delayed linear feedback

The resistively-capacitively-inductively-shunted （RCL-shunted） Josephson junction （RCLSJJ） shows chaotic behaviour under some parameter conditions. Here a scheme for controlling chaos in the RCLSJJ is presented based on the linear feedback theory. Numerical simulations show that this scheme can be effectively used to control chaotic states in this junction into stable periodic states. Moreover, the different stable period states with different period numbers can be obtained by appropriately adjusting the feedback intensity and delay time without any pre-knowledge of this system required.     

Controlling chaos in RCL-shunted Josephson junction by delayed linear feedback

The resistively--capacitively--inductively-shunted (RCL-shunted) Josephson junction (RCLSJJ) shows chaotic behaviour under some parameter conditions. Here a scheme for controlling chaos in the RCLSJJ is presented based on the linear feedback theory. Numerical simulations show that this scheme can be effectively used to control chaotic states in this junction into stable periodic states. Moreover, the different stable period states with different period numbers can be obtained by appropriately adjusting the feedback intensity and delay time without any pre-knowledge of this system required.