TRAJECTORY TRACKING OF ROBOT MANIPULATOR USING GAUSSIAN NETWORKS

被引：2

作者：

BEHERA, L ^{[1
]}

GOPAL, M ^{[1
]}

CHAUDHURY, S ^{[1
]}

机构：

[1] INDIAN INST TECHNOL, DEPT ELECT ENGN, NEW DELHI 110016, INDIA

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 1994年 / 13卷 / 02期

关键词：

GAUSSIAN NETWORKS; INVERSE AND FORWARD DYNAMICS; LINEAR PERTURBATION MODEL;

D O I：

10.1016/0921-8890(94)90053-1

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a neural network based control scheme for robot tracking applications. Gaussian networks are used to model both the forward and the inverse dynamics of a robot arm. The feedforward torque is actuated by the output of inverse dynamic mapping while the feedback control law is derived using the linear perturbation model of the identified forward dynamics along the desired trajectory. The gradient based learning algorithm is used and the effectiveness of the proposed scheme is highlighted through simulation studies.

引用

页码：107 / 115

页数：9

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