%0 Journal Article
%T Robust Neural-Network Compensating Control for Robot Manipulator Based on Computed Torque Control<br>基于计算转矩控制结构的机械手鲁棒神经网络补偿控制(英文)
%A BAI Ping
%A FANG Ting-jian
%A GE Yun-jian
%A <br>白 萍
%A 方廷健
%A 葛运建
%J 控制理论与应用
%D 2001
%I 
%X This paper proposes a new controller design approach for trajectory tracking of robot manipulator with uncertainties. The proposed controller is based on the computed torque control structure, and incorporates a compensator, which is realized by Functional Link Neural Network, and a robustifying term. In addition, when neural newtork reconstruction error is not uniformly bounded, an adaptive robustifying term is designed. It is shown that all the signals in the closed loop system are uniformly ultimately bounded. Compared with other approaches, no joint acceleration measurement and exactly known inertia matrix are required. Both theory and simulation results show the effectiveness of the proposed controller.
%K robot manipulator
%K computed torque control
%K neural network
%K robust
%K adaptive<br>机械手
%K 计算转矩控制
%K 神经网络
%K 自适应
%K 鲁棒控制
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=498DF626257FCB05&yid=14E7EF987E4155E6&vid=13553B2D12F347E8&iid=B31275AF3241DB2D&sid=547650636788ED84&eid=E23857687CD2EE51&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=7&reference_num=6