Adaptive manipulator trajectory control using neural networks
作者:
L. BEHERA,
M. GOPAL,
期刊:
International Journal of Systems Science
(Taylor Available online 1994)
卷期:
Volume 25,
issue 8
页码: 1249-1265
ISSN:0020-7721
年代: 1994
DOI:10.1080/00207729408949276
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
A unified study of adaptive control and neural network based control schemes for the trajectory tracking problem of robot manipulators is presented. Efficacy of parametrized adaptive algorithms in compensating the structured uncertainties in robot dynamics is verified through extensive simulation. The ability of neural networks to provide a robust adaptive framework in the presence of both structured and unstructured uncertainties is investigated. A case study is carried out in support of a parametrized adaptive scheme using neural networks. Simulation results clearly indicate that the neural network based adaptive controller achieves better tracking in the presence of parametric uncertainties as well as unmodelled effects compared to the simple direct adaptive scheme.
点击下载:
PDF (436KB)
返 回