Repetitive learning control: A Lyapunov-based approach

被引:174
|
作者
Dixon, WE [1 ]
Zergeroglu, E
Dawson, DM
Costic, BT
机构
[1] Oak Ridge Natl Lab, Robot & Proc Syst Div, Oak Ridge, TN 37831 USA
[2] Bell Lab Innovat Opt Fiber Solut, Sturbridge, MA 01566 USA
[3] Clemson Univ, Dept Elect & Comp Engn, Clemson, SC 29634 USA
[4] Clemson Univ, Dept Elect & Comp Engn, Clemson, SC 29634 USA
关键词
adaptive control; learning control; repetitive update law; robot manipulator;
D O I
10.1109/TSMCB.2002.1018772
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learning-based feedforward term is generated from a straightforward Lyapunov-like stability analysis, the control designer can utilize other Lyapunov-based design techniques to develop hybrid control schemes that utilize learning-based feedforward terms to compensate for periodic dynamics and other Lyapunov-based approaches (e.g., adaptive-based feedforward terms) to compensate for nonperiodic dynamics. To illustrate this point, a hybrid adaptive/learning control scheme is utilized to achieve global asymptotic link position tracking for a robot manipulator.
引用
收藏
页码:538 / 545
页数:8
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