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Robust Iterative Learning Control Design: Application to a Robot Manipulator
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DOI：10.1109/TMECH.2008.2004627.png)
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Abstract
En 中文
This paper deals with robust iterative learning control design for uncertain single-input-single-output linear time-invariant systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the mu-synthesis approachto obtain a feedback controller. Thereafter, a convergent iterative learning law is obtained by using the performance weighting function involved in the robust performance condition. Experimental results, on a CRS465 robot manipulator, are provided to illustrate the effectiveness of the proposed design method.
Keywords:
Iterative learning control (ILC)
robot manipulators
robust performance
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