Robust neural control for robotic manipulators

被引：63

作者：

Barambones, O

Etxebarria, V

机构：

[1] Univ Basque Country, Fac Ciencias, Dpto Elect & Elect, E-48080 Bilbao, Spain

[2] Univ Basque Country, Dpto Ingn Sistemas & Automat EUITI Bilbao, Bilbao 48012, Spain

来源：

AUTOMATICA | 2002年 / 38卷 / 02期

关键词：

robust control; robotics; neural control; sliding mode; Lyapunov stability;

D O I：

10.1016/S0005-1098(01)00191-1

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A robust neural control scheme for mechanical manipulators is presented. The design basically consists of an adaptive neural controller which implements a feedback linearization control law for a generic manipulator with unknown parameters, and a sliding-mode control which robustifies the design and compensates for the neural approximation errors. It is proved that the resulting closed-loop system is stable and that the trajectory-tracking control objective is achieved. Some simulation results are also provided to evaluate the design. (C) 2001 Elsevier Science Ltd. All rights reserved.

引用

页码：235 / 242

页数：8

共 14 条

[1]

Barambones O., 1999, Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375), P357, DOI 10.1109/CIRA.1999.810074

[2] Robust adaptive control for robot manipulators with unmodelled dynamics [J].