By Topic

Uncertain Bound Estimation for Robustness to the Robot Manipulators Using Feedforward Neural Network

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

2 Author(s)
Singh, H.P. ; Dept. of Math., Indian Inst. of Technol., Roorkee, India ; Sukavanam, N.

In this paper, an intelligent adaptive robust compensator is developed to eliminate the effects of system uncertainties for tracking control of robot manipulators. For controller design, the prior information of the bound of uncertainties is not required but we estimate this bound by using feed forward neural network. Lyapunov approach will be used to show that the filtered tracking error and neural network weight error are uniformly ultimately bounded. Finally, simulation studies are carried out for a two-link robot manipulator to show the effectiveness of the control scheme.

Published in:

Computational Intelligence and Communication Networks (CICN), 2010 International Conference on

Date of Conference:

26-28 Nov. 2010