By Topic

Adaptive H Tracking Control Design via Neural Networks of a Constrained Robot System

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)
Petronilho, A. ; Electrical Engineering Department - University of São Paulo at São Carlos, C.P.359, São Carlos, SP, 13560-970, Brazil E-mail: apetroni@sel.eesc.usp.br ; Siqueira, A.A.G. ; Terra, M.H.

In this paper, a nonlinear adaptive neural network tracking control with a guaranteed Hperformance is proposed for a constrained robot manipulator with plant uncertainties. The neural network is used to learn the unknown dynamics by an adaptive algorithm. Moreover, a force sensor is built to measure the forces and torques between the experimental robot UArm II end-effector and the environment. Finally, results obtained from the implementation of the proposed controller in the manipulator UArm II, under a constrained movement, are presented.

Published in:

Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on

Date of Conference:

15-15 Dec. 2005