By Topic

Neural sliding mode controller of uncertain robot manipulators using H method

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Weidong Chen ; Dept. of Inf. Eng., Yanshan Univ., Qinhuangdao, China ; Dezhi Tang ; Hongrui Wang ; Li Chen

An adaptive neural robust controller based on H method is presented for trajectory of uncertain robot manipulators. An RBF neural network is used to compensate the plant parameter uncertainties, in addition, sliding-mode control action is included to eliminate the effect of approximation error via neural network approximation and the H tracking performance ensures the robust stability that under a prescribed attenuation level for external disturbance. The simulation shows that the control law can guarantee fast convergence of trajectory tracking error as well as robustness for parameter uncertainties and external disturbances.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:6 )

Date of Conference:

15-19 June 2004