Experimental evaluation of an adaptive iterative learning control scheme on a 5-DOF robot manipulator
Abdelhamid Tayebi, Shafiqul Islam
- 发表年份
- 2005
- 引用次数
- 15
摘要
In this paper, two adaptive iterative learning control schemes are tested experimentally on a five-degrees-of-freedom (5-DOF) robot manipulator CATALYST5. The control strategy consists of using a classical PD structure plus an additional iteratively updated term designed to cope with the unknown parameters and disturbances. The control design is very simple in the sense that the only requirement on the PD and learning gains is the positive definiteness condition. In contrast with classical iterative learning control schemes, where the number of iterative variables is generally equal to the number of control inputs, the proposed controllers use just one or two iterative variables. In this framework, the acceleration measurements and the bounds of the robot parameters are not needed.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002