Adaptive neurofuzzy control of a robotic gripper with external disturbances
J. A. Domínguez-Lopez, Richard Crowder, R.I. Damper, C.J. Harris
- 发表年份
- 2005
- 引用次数
- 4
摘要
Robotic grippers are commonly required to grasp and manipulate loads under a wide range of conditions, without the from the end effector, and avoiding damage to the load. We have previously demonstrated the adaptive neurofuzzy control of a simple gripper with a two-input, one-output action. When the robotic gripper is integrated with a multi-degree of freedom robot, the controller could face the curse of dimensionality. To show that satisfactory control was still feasible, we undertook extensive simulations of this gripper mounted on a multi-degree of freedom robot. We also report enhanced control by using the gripper's acceleration as an additional input.
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