分数阶超混沌系统的RBF神经网络自适应同步控制  

RBF neural network adaptive synchronization control for fractional-order hyper-chaotic systems

作　　者：邵克勇[1] 徐紫辉 黄欣宇 王婷婷[1] 张轶 SHAO Keyong;XU Zihui;HUANG Xinyu;WANG Tingting;ZHANG Yi(School of Electrical Engineering Information,Northeast Petroleum University,Daqing 163318,China;Oil and Gas Control Center of National Petroleum and Natural Gas Pipeline Group,Beijing 100020,China)

机构地区：[1]东北石油大学电气信息工程学院,黑龙江大庆163318 [2]国家石油天然气管网集团有限公司油气调控中心,北京100020

出　　处：《扬州大学学报（自然科学版）》2020年第5期58-62,共5页Journal of Yangzhou University：Natural Science Edition

基　　金：国家自然科学基金资助项目(51404073);中国博士后科学基金资助项目(2018M630335);黑龙江省自然科学基金资助项目(QC2017043);黑龙江省博士后面上基金资助项目(LBH-Z19008).

摘　　要：针对含有不确定参数变时滞分数阶超混沌系统的同步控制问题,设计了一种基于径向基函数(radial basis function,RBF)的自适应同步方案.通过选取自适应率神经网络控制器,解决分数阶超混沌系统内部不确定性和外界干扰问题,最终实现驱动系统和响应系统完全同步.仿真结果表明,该控制器是有效可行的且具有很强的鲁棒性,可实现分数阶超混沌Chen系统的同步.In order to solve the problem of the synchronization of fractional-order hyper-chaotic systems with variable delay time and uncertain parameters,a adaptive synchronization scheme based on radial basis function neural network is designed.It solves the fractional order hyper-chaos systems with internal uncertainty and external disturbance synchronization control problems by the selection rate of adaptive neural network controller,and finally realizes the synchronization,by which the drive system completely follows response system.The simulation results show that the controller which can realize the synchronization of fractional-order Chen hyper-chaotic system is effective,feasible and strongly robust.

关 键 词：分数阶超混沌系统 混沌同步 自适应控制 径向基神经网络 

分 类 号：TP273.3[自动化与计算机技术—检测技术与自动化装置]