磁场中轴向运动条形板强非线性超谐共振及混沌运动

针对磁场环境中周期外载作用下轴向运动导电条形板的非线性振动及混沌运动问题进行研究。应用改进多尺度法对横向磁场中条形板的强非线性振动问题进行求解,得到超谐波共振下系统的分岔响应方程。根据奇异性理论对非线性动力学系统的普适开折进行分析,求得含两个开折参数的转迁集及对应区域的拓扑结构分岔图。通过数值算例,分别得到以磁感应强度、轴向拉力、激励力幅值和激励频率为分岔控制参数的分岔图和最大李雅普诺夫指数图,以及反映不同运动行为区域的动力学响应图形,讨论分岔参数对系统呈现的倍周期和混沌运动的影响。结果表明,可通过相应参数的改变实现对系统复杂动力学行为的控制。     

A novel robust proportional-integral （PI） adaptive observer design for chaos synchronization

In this paper, chaos synchronization in the presence of parameter uncertainty, observer gain perturbation and exogenous input disturbance is considered. A nonlinear non-fragile proportional-integral (PI) adaptive observer is designed for the synchronization of chaotic systems; its stability conditions based on the Lyapunov technique are derived. The observer proportional and integral gains, by converting the conditions into linear matrix inequality (LMI), are optimally selected from solutions that satisfy the observer stability conditions such that the effect of disturbance on the synchronization error becomes minimized. To show the effectiveness of the proposed method, simulation results for the synchronization of a Lorenz chaotic system with unknown parameters in the presence of an exogenous input disturbance and abrupt gain perturbation are reported.     

异结构离散型混沌系统的延迟同步

以异结构离散型混沌系统为研究对象,设计了一种延迟同步控制器实现了离散型Henon混沌系统和Ikeda混沌系统之间的同步控制．根据稳定性定理,确定了延迟同步控制器的结构以及系统状态变量之间的误差方程．设计的延迟同步控制器对于不同的离散型混沌系统具有统一的形式,可以实现任意异结构离散型混沌系统之间的延迟同步．数值仿真模拟进一步验证了该控制器的有效性．     

Nonlinear and chaotic analysis of a financial complex system

In this paper,determination of the characteristics of futures market in China is presented by the method of the phase-randomized surrogate data.There is a significant difference in the obtained critical values when this method is used for random timeseries and for nonlinear chaotic timeseries.The singular value decomposition is used to reduce noise in the chaotic timeseries.The phase space of chaotic timeseries is decomposed into range space and null noise space.The original chaotic timeseries in range space is restructured.The method of strong disturbance based on the improved general constrained randomized method is further adopted to re-deternination.With the calculated results,an analysis on the trend of futures market of commodity is made in this paper.The results indicate that China＇s futures market of commodity is a complicated nonlinear system with obvious nonlinear chaotic characteristic.     

Elimination of spiral waves and spatiotemporal chaos by the synchronization transmission technology of network signals

A method to eliminate spiral waves and spatiotemporal chaos by using the synchronization transmission technology of network signals is proposed in this paper. The character of the spiral waves and the spatiotemporal chaos in the Fitzhugh—Nagumo model is presented. The network error evolution equation with spatiotemporal variables and the corresponding eigenvalue equation are determined based on the stability theory, and the global synchronization condition is obtained. Simulations are made in a complex network with Fitzhugh—Nagumo models as the nodes to verify the effectiveness of the synchronization transmission principle of the network signal.     

Adaptive lag synchronization and parameter identification of fractional order chaotic systems

This paper proposes a simple scheme for the lag synchronization and the parameter identification of fractional order chaotic systems based on the new stability theory. The lag synchronization is achieved and the unknown parameters are identified by using the adaptive lag laws. Moreover, the scheme is analytical and is simple to implement in practice. The well-known fractional order chaotic Lü system is used to illustrate the validity of this theoretic method.     

具有死区输入的分数阶多涡卷混沌系统的有限时间同步

基于滑模控制研究了具有死区输入的分数阶多涡卷系统的有限时间同步问题,根据分数阶微积分的相关理论,给出了系统取得同步的充分性条件,结果表明:在一定条件下,分数阶多涡卷混沌系统可取得有限时间同步.     

受污染混沌信号的协同滤波降噪

根据混沌吸引子的自相似分形特性,提出了一种利用协同滤波重构受污染混沌信号的降噪算法.所设计的降噪算法通过对相似片段的分组将一维混沌信号的降噪转化为一个二维联合滤波问题;然后,在二维变换域用阈值法衰减噪声;最后,通过反变换获得原始信号的估计.由于分组中的相似片段具有良好的相关性,与直接在一维变换域做阈值降噪相比,分组的二维变换能获得原信号更稀疏的表示,更好地抑制噪声.仿真结果表明,该算法对原始混沌信号的重构精度和信噪比的提升都优于小波阈值、局部曲线拟合等现有的混沌信号降噪方法,对相图的还原质量也更好.     

爆炸波中的混合不确定度量化方法

将认知不确定作为外层,偶然不确定作为内层,利用混合不确定理论处理爆炸波中的不确定度问题.分别使用非嵌入多项式混沌方法（NIPC）和Dempster-Shafer理论处理偶然不确定和认知不确定,用迎风格式求解确定系统.结果表明：NIPC和Dempster-Shafer结构为模型输入参数和初边值不确定性对输出响应量的影响提供一种有效方法,对各种建模与模拟不确定性评估和确认建模与模拟具有很好的参考价值.     

基于大脑情感学习模型和自适应遗传算法的混沌时间序列预测

针对传统神经网络预测精度不高、收敛速度慢的问题,提出一种基于大脑情感学习模型和自适应遗传算法的混沌时间序列预测方法.大脑情感学习模型模拟了哺乳动物大脑中杏仁体和眶额皮质之间的情感学习机制,具有计算复杂度低、运算速度快的特点,因此可以大大提高混沌预测的快速性.为了进一步提高大脑情感学习模型的预测精度,采用自适应遗传算法优化其参数,将待优化的权值与阈值分布在染色体基因序列上,用适应度函数选出最佳参数,从而增强了模型的逼近能力.基于Lorenz混沌时间序列和实际地磁Dst指数序列的预测结果表明,本文方法较其他传统方法在预测精度、运算速度和稳定性上均具有明显优势.