Robust Hybrid Position/Force Control with Adaptive Scheme
In-Chul Ha, Myoung-Chul Han
- 发表年份
- 2004
- 引用次数
- 4
- 访问权限
- 开放获取
摘要
When real robot manipulators are mathematically modeled, uncertainties are not avoidable. The uncertainties are often nonlinear and time varying. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance and etc. We proposed a class of robust hybrid position/force control of manipulators and provided the stability analysis in the previous work. In the work, we propose a class of adaptive robust hybrid position/force control of manipulators with bound estimation and the stability based on Lyapunov function is presented. Especially, this controller does not need the information of uncertainty bound. The simulation results are provided to show the effectiveness of the algorithm.
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