Development of a general friction identification framework for industrial manipulators
Marina Indri, Stefano Trapani, Ivan Lazzero
- 发表年份
- 2016
- 引用次数
- 4
摘要
The paper proposes a general friction identification framework for industrial manipulators, including the automatic handling of all the required phases, from data acquisition and processing up to parameters identification. A complete static friction model is used, with the insertion of a rough approximation of the hysteretic behavior of friction; switching to a possible simpler model is also automatically executed when possible. The proposed solution has been implemented in a software module, which has been integrated into the control architecture of an industrial robot, and experimentally tested. The results have shown that a very accurate reconstruction of the actual motor currents is provided, when the friction estimated using the proposed framework is inserted in the robot dynamic model.
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