Cart (Loading....) | Create Account
Close category search window
 

Dynamic model identification of the 2-Axes PAM robot arm using neural MIMO NARX model

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)
Ho Pham Huy Anh ; Grad. Sch. of Mech. & Automotive Eng., Ulsan Univ., Ulsan ; Kyoung Kwan Ahn ; Yoon Jong Il

In this paper, a novel inverse dynamic MIMO NARX model is used for modeling and identifying simultaneously both of joints of the prototype 2-axes PAM robot armpsilas inverse dynamic model. The contact force variations and highly nonlinear coupling features of both links of the 2-axes PAM robot arm are modeled thoroughly through an inverse neural MIMO NARX model-based identification process using experiment input-output training data. For the first time, the nonlinear inverse dynamic MIMO NARX model scheme of the prototype 2-axes PAM robot arm has been investigated. The results show that proposed dynamic intelligent model trained by back propagation learning algorithm yields outstanding performance and perfect accuracy.

Published in:

Communications and Electronics, 2008. ICCE 2008. Second International Conference on

Date of Conference:

4-6 June 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.