By Topic

Experimental results on neural network-based control strategies for flexible-link manipulators

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)
Talebi, H.A. ; Dept. of Electr. Eng., AmirKabir Univ., Tehran, Iran ; Khorasani, K. ; Patel, R.V.

The problem of controlling a nonminimum phase nonlinear system with application to tip position control of a flexible-link manipulator is considered. An output re-definition strategy is developed which is applicable to a class of open-loop stable nonlinear systems whose input-output maps contain nonlinear terms from output and linear terms from input. No a priori knowledge about the nonlinearities of the system is required. The output re-definition scheme is based on first identifying the nonlinearities of the system using neural networks and then modifying the system zero dynamics. A stable/anti-stable factorization is performed on the zero dynamics of the system. The new output is re-defined using the neural identifier and the stable part of the zero dynamics. A controller is then designed based on the new output whose zero dynamics are stable and can be inverted. For the flexible-link manipulator case, the controller is composed of a stabilizing joint PD controller and an output re-definition tracking controller. Experimental and simulation results are presented to show the effectiveness of the proposed control scheme as compared to both linear and nonlinear conventional controllers

Published in:

Neural Networks, 1999. IJCNN '99. International Joint Conference on  (Volume:3 )

Date of Conference: