Adaptive task-space regulation of rigid-link flexible-joint robots with uncertain kinematics
Chao Liu, Chien Chern Cheah, J.-J.E. Slotine
- Year
- 2006
- Citations
- 6
Abstract
Joint flexibility is an important factor to consider in the robot control design if high performance is expected for the robot manipulators. The research work on control of rigid-link flexible-joint (RLFJ) robot in the literature has assumed that the kinematics of the robot is known exactly. There have been no results so far that can deal with the kinematics uncertainty in RLFJ robot. In this paper, we present the first study on this problem and propose an adaptive regulation method which can deal with the kinematics uncertainty and uncertainties in both link and motor dynamics of the RLFJ robot system. An observer is designed to avoid the use of acceleration due to the fourth-order overall dynamics. Sufficient conditions are derived to guarantee the asymptotic stability of the closed-loop system. Simulation result illustrates the effectiveness of proposed control method
Keywords
Related papers
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