Neural network-based nonlinear tracking control of kinematically redundant robot manipulators

被引：57
|
作者：
Kumar, Naveen [1 ]
Panwar, Vikas [2 ]
Sukavanam, N. [3 ]
Sharma, S. P. [3 ]
Borm, J. H. [1 ]
机构：
[1] Ajou Univ, Dept Mech Engn, Suwon 443749, South Korea
[2] CDL Univ, Dept Math, Sirsa 125055, Haryana, India
[3] IIT Roorkee, Dept Math, Roorkee 247667, Uttar Pradesh, India
来源：
MATHEMATICAL AND COMPUTER MODELLING | 2011年 / 53卷 / 9-10期
关键词：
Redundant manipulators; Feedforward neural network; Lyapunov stability; Subtask tracking; CRITERIA;
D O I：
10.1016/j.mcm.2011.01.014
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, neural network-based nonlinear dynamical control of kinematically redundant robot manipulators is considered. The neural network-based controller achieves end-effector trajectory tracking as well as subtask tracking effectively. A feedforward neural network is employed to learn the parametric uncertainties, existing in the dynamical model of the robot manipulator. The whole system is shown to be stable in the sense of Lyapunov. Numerical simulation studies are carried out for a 3R planar robot manipulator to show the effectiveness of the control scheme. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1889 / 1901
页数：13
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