Design of a robust adaptive neural tracking controller

被引：3

作者：

Song, Q ^{[1
]}

Xiao, J ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2000年 / 27卷 / 04期

关键词：

adaptive dead zone; convergence; neural network; robust tracking control;

D O I：

10.1023/A:1008119010058

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A robust neural tracking controller is designed based on the conic sector theory. An adaptive dead zone scheme is employed to enhance robustness of the system. The proposed algorithm does not require knowledge of either the upper bound of disturbance or the bound on the norm of the estimate parameter. A complete convergence proof is provided based on the sector theory to deal with the nonlinear system. Simulation results are presented to control a two-link direct drive robot and show the performance of the tracking controller.

引用

页码：363 / 377

页数：15

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