By Topic

Neural Network Control of a New Biped Robot Model with Back Propagation Algorithm

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)
Tabar, A.F. ; Malek Ashtar Univ. of Technol., Tehran ; Khoogar, A.R. ; Vali, A.R.

This paper provides a comparative study, through simulation, of the effectiveness of the local (decoupled) PD control and the neural network control when applied to a new biped robot model. The biped model has 5_link and 6 degrees of freedom and actuated by Plated Pneumatic Artificial Muscle, which have a very high power to weight ratio and an inherent adaptable compliance. This NN controller allow accurate and dynamic following of prescribed trajectories, not simply control using "via" points specified by a teach pendant. It can significantly improve the accuracy requirements by retraining the basic PD/PID loop, but adding an inner adaptive loop that allows the controller to learn unknown parameters such as friction coefficient, thereby improving tracking accuracy. Simulation results show that NN controller tracking performance is much better than PD controller tracking performance.

Published in:

Robot and Human interactive Communication, 2007. RO-MAN 2007. The 16th IEEE International Symposium on

Date of Conference:

26-29 Aug. 2007