新三维混沌系统及其同步的电路实验研究

研究了一种新型三维混沌系统及采用连续控制法控制其同步的电路实现问题。给出了相图、单参数分岔图、庞卡莱映射以及李雅普诺夫指数,并利用运算放大器、模拟乘法器及线性器件设计电路验证了该系统参数变化时的各种状态的存在和系统的同步控制。     

CVE-2型混沌激振器运动的数值仿真和混沌识别

建立了使用滑动轴承的CVE－2型混沌激振器所产生的运动的数学模型,并对其进行了数值仿真和混沌识别,结果表明,激振器产生的运动中有混沌成分。     

Chen＇s混沌系统的同步控制

主要对非线性复杂动力系统——Chen＇s系统的同步控制作出了研究,主要利用驱动-响应同步原理,设计了4种不同的非线性反馈控制器来控制2个初始条件不同的Chen＇s系统达到同步。     

非线性耦合分数阶系统的异结构同步

针对异结构的分数阶混沌系统同步问题,提出了非线性耦合分数阶异结构混沌系统的同步方法,即在α＋β-1=0条件下,利用非线性耦合实现两个异结构分数阶混沌系统同步,并通过数值仿真证明了其有效性.仿真实验显示,随着耦合系数的变化,系统呈现多样性,分数阶混沌系统出现不同混沌状态,而分数阶超混沌系统不仅会出现超混沌状态,还会出现发散的现象.     

一类非自治混沌系统的时滞反馈控制

针对一类非自治混沌系统,提出一种时滞反馈控制方法,通过构造特殊的Lyapunov函数,利用时滞微分方程稳定性理论,分析和证明了受控系统的全局指数稳定性.最后将理论结果应用到典型的洛仑兹(Lorenz)系统和约瑟夫森(Josephson)系统,并给出数值模拟来验证结论的正确性.     

Exponential Stability Analysis for TS-model-based Fuzzy Chaotic Control Systems With Delays

The issue of exponential stability for TS-model-based fuzzy chaotic control systems with constant or time-varying delays is investigated. A linear-feedback fuzzy controller is designed using parallel dispersal compensation technique for a large class of chaotic control systems. By means of the Lyapunov-Krasovskii functional approach in combination of the linear matrix inequality and differential inequality techniques, the criteria for exponential stability of the TS-model-based fuzzy controller are derived, and the corresponding control laws are presented. The results are easy to be calculated numerically because of the linear matrix inequalities representation.     

企业家激励和经济增长的混沌同步研究

利用主动被动的混沌同步方法,分析了企业家激励和企业经济增长之间的混沌同步作用,建立了企业家激励和企业经济增长的混沌同步模型,并根据建立的混沌同步模型简要讨论了企业家激励的混沌同步策略。     

基于联合时序的混沌时用水量短期预测调度

针对给水优化调度的时用水量高精度短期预测难题,提出一种基于横向分时段和纵向残差修正的联合时序短期混沌预测方法.经模式识别获得关联度高的横向时序为研究样本,重构横向分时段相空间并分析典型时段流量数据的混沌特性,建立混沌预测模型,以在线最小二乘支持向量机作为混沌预测工具得出各时段用水流量;为了能动态跟踪用水突变,实时采集纵向数据序列做残差计算,进而用灰色模型进行残差预测修正以提高预测精度.依据杭州市萧山某大用户时用水量实例,对一段时间的正常用水和突变用水做连续24 h短期混沌预测,在不同方法下的时用水量预测精度作深入对比研究.仿真结果表明：该预测方法对这一类混沌时序短期预测具有良好的计算精度,能很好反映各典型用水日的特点和实时用水变化情况,预测效果明显优于其他预测方法,更易满足供水优化调度的需求.     

Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China.In the process of determining the structure of the chaotic neural network,the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension,and then the number of hidden layer nodes is estimated by trial and error.Finally,this model is applied to predict the retail prices of eggs and compared with ARIMA.The result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of eggs.The empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.