By Topic

Inverse Dynamic model identification of 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

1 Author(s)
Anh, H.P.H. ; Electr. & Electron. Dept., Ho Chi Minh City Univ. of Technol., Ho Chi Minh City, Vietnam

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 arm. The contact force variations and highly nonlinear coupling features of both links of the 2-axes PAM system are modeled thoroughly through an inverse neural MIMO NARX model-based identification process using experiment input-output training data. For the first time, the dynamic inverse neural MIMO NARX model of the 2-axes PAM robot arm has been investigated. The results show that the neural inverse dynamic MIMO NARX model trained by back propagation learning algorithm yields outstanding performance and perfect accuracy.

Published in:

Advanced Intelligent Mechatronics, 2009. AIM 2009. IEEE/ASME International Conference on

Date of Conference:

14-17 July 2009