%0 Journal Article
%T Repetitive Learning Control for Time-varying Robotic Systems: A Hybrid Learning Scheme<br>时变机器人系统的重复学习控制: 一种混合学习方案
%A SUN Ming-Xuan
%A HE Xiong-Xiong
%A CHEN Bing-Yu
%A <br>孙明轩
%A 何熊熊
%A 陈冰玉
%J 自动化学报
%D 2007
%I 
%X Repetitive learning control is presented for finitetime-trajectory tracking of uncertain time-varying robotic systems. A hybrid learning scheme is given to cope with the constant and time-varying unknowns in system dynamics, where the time functions are learned in an iterative learning way, without the aid of Taylor expression, while the conventional differential learning method is suggested for estimating the constant ones. It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle, and the time-varying unknowns are not necessary to be periodic. It is shown that with the adoption of hybrid learning, the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases. The effectiveness of the proposed scheme is demonstrated through numerical simulation.
%K Adaptive control
%K iterative learning control
%K repetitive control
%K robotic systems
%K time-varying systems<br>重复学习控制
%K 机器人
%K 时序变化系统
%K 混合学习计划
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=8AAB85D4E43D93E390E8938F7ECC301C&yid=A732AF04DDA03BB3&vid=27746BCEEE58E9DC&iid=708DD6B15D2464E8&sid=53A4507B400B4E65&eid=C1F642278C6E9D3E&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=17