%0 Journal Article
%T Robust H-infinity tracking-control for robotic system based on recurrent fuzzy-neural-networks<br>基于递归模糊神经网络的机器人鲁棒H∞跟踪控制
%A PENG Jin-zhu
%A WANG Yao-man
%A WANG Jie
%A <br>彭金柱
%A 王耀南
%A 王杰
%J 控制理论与应用
%D 2010
%I 
%X Using recurrent fuzzy-neural-networks(RFNN) to approximate the nonlinear functions in a robotic manipulator system, we develop an adaptive H-infinity controller. The proposed controller can attenuate the effect of external disturbance and reduce the reconstruction-error of the recurrent fuzzy neural network to a prescribed level. Meanwhile, it also ensures all signals in the closed-loop system to be bounded. Simulation experiments of this control strategy are performed; the results show that this control strategy has better tracking-performance than the computed-torque-control method under external disturbances.
%K recurrent fuzzy-neural-network
%K robotic manipulator system
%K robust H-infinity control
%K tracking-control<br>递归模糊神经网络
%K 机器人系统
%K 鲁棒H∞控制
%K 跟踪控制
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=67F8E28DF7EB4E2DEF3013E05E03380D&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=9CF7A0430CBB2DFD&sid=F9AB8F3D624A89DB&eid=D291DCA663E1D24D&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=16