MANIPULATION
Adaptive friction compensation for industrial robot control
Antonio Visioli, Riccardo Adamini, Giovanni Legnani
- 发表年份
- 2002
- 引用次数
- 17
摘要
We deal with the friction compensation in the model-based trajectory tracking control of an industrial robot manipulator. First it is shown that the variations of the friction term might significantly affect the control performances during the robot operations. Then, a simple adaptive scheme is proposed to solve the problem, allowing us to keep the trajectory tracking errors at a constant low level. Experimental results, obtained in a typical industrial environment, show the effectiveness of the method and how it is comparable with known neural-network-based techniques.
关键词
Compensation (psychology)TrajectoryControl theory (sociology)Industrial robotRobotTracking (education)Computer scienceArtificial neural networkAdaptive controlControl engineering
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 引用
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002