Robot trajectory control using neural networks-theory and PUMA simulations
Y. Jin, Tony Pipe, Alan Winfield
- 发表年份
- 2002
- 引用次数
- 9
摘要
In this paper we investigate neural network applications in trajectory control of robotic manipulators. Most research in the field remains at an empirical level. Although other authors have claimed very good simulation or even experiment results, lack of theoretical guarantee prevents application of the results in industry. In contrast, this paper presents a neural control method which has a strict theoretical basis. The whole system (manipulator and neural network) stability is guaranteed. Simulations in PUMA robot applications are also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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