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SVM-based learning control of space robots in capturing operation
文献类型:期刊
作者:Huang, Panfeng[1]  Xu, Yangsheng[2]  
机构:[1]College of Astronautics, Northwestern Polytechnical University, Xi'an, 710072, China
[2]Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong, Hong Kong
通讯作者:Huang, P.(pfhuang@nwpu.edu.cn)
年:2007
期刊名称:International journal of neural systems影响因子和分区
卷:17
期:6
页码范围:467-77
增刊:增刊
收录情况:EI(20080411051009)  (18186596)  
所属部门:航天学院
人气指数:450
浏览次数:444
摘要:
In this paper, we presents a novel approach for tracking and catching operation of space robots using learning and transferring human control strategies (HCS). We firstly use an efficient support vector machine (SVM) to parametrize the model of HCS. Then we develop a new SVM-based learning structure to better implement human control strategy learning in tracking and capturing control. The approach is fundamentally valuable in dealing with some problems such as small sample data and local minima, ...More
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