By Topic

A hybrid intelligent active force controller for articulated robot arms using dynamic structure 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
$33 $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)
Loo Chu Kiong ; Fac. of Eng. & Technol., Multimedia Univ., Melaka, Malaysia ; M. Rajeswari

Active Force Control (AFC) is known to offer a feasible solution to control efficiently a robot operating at highspeed operation. This method is proven to be stable and robust against internal and external disturbance and has been successfully in various experimental works. In this regards, the main issue of AFC method is the estimation of the inertia matrix of the robot arm. In previous work neural network is proposed to estimate the inertia matrix. In this approach, the off-line training of neural network requires. systematic and effective data preparation scheme. In addition, how to design the neural network is another important issue. This paper proposes yet another methodology to address the two issues stated above. In this approach, the All estimation of inertia matrix is made based on priori knowledge of robot dynamic model. On the other hand, the optimal design of neural network is autonomously determined through the off-line learning phase using Growing Multi-Experts Network (GAN).

Published in:

TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering  (Volume:3 )

Date of Conference:

28-31 Oct. 2002