%0 Journal Article
%T Hybrid genetic neural networks for chaotic system control<br>混沌系统的混合遗传神经网络控制
%A TAN Wen
%A WANG Yao-nan
%A HUANG Dan
%A ZENG Zhao-fu
%A ZHOU Shao-wu
%A LIU Zu-run
%A <br>谭　文
%A 王耀南
%A 黄　丹
%A 曾照福
%A 周少武
%A 刘祖润
%J 控制理论与应用
%D 2004
%I 
%X By incorporating the temporal difference prediction technique with the genetic algorithm, a novel hybrid genetic neural network (known as HyGANN) for controlling nonlinear chaotic system based on the scheme of small perturbations was presented . The HyGANN trained by reinforcement learning algorithm could generate small perturbation time series signals to suppress the chaotic states. The computer simulations on Henon map chaotic system have shown that the behavior of period 1 and period 2 can be controlled effectively and the high period orbit can be directed towards desired periodic trajectory.
%K genetic algorithm
%K reinforcement learning
%K temporal difference prediction
%K chaos control
%K neural networks<br>遗传算法
%K 增强学习
%K 暂态误差预测
%K 混沌控制
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=1175A66F839784E1&yid=D0E58B75BFD8E51C&vid=659D3B06EBF534A7&iid=E158A972A605785F&sid=DDDA4F26E8AD3C0E&eid=8566B4AE2A8832E3&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=16