By Topic

Stable adaptive control for robot trajectory tracking using neural networks

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

3 Author(s)
Sun Fuchun ; Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China ; Sun Zengqi ; Zhang Rongjun

Existing stable adaptive control approaches using neural networks have been developed mostly in continuous time systems for robot trajectory tracking. This paper investigates the discrete time case. A novel scheme for integrating a neural network (NN) approach with an adaptive implementation of the sliding mode control with the sector is developed. The sliding mode control with the sector serves two purposes, one is to provide the global stability of the closed loop system, the other is to improve the tracking performance. The whole system stability and tracking error convergence are proved by Lyapunov techniques which yield a NN weight tuning algorithm

Published in:

Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on  (Volume:4 )

Date of Conference:

22-28 Apr 1996