By Topic

Cogging Compensating Piecewise Iterative Learning Control with application to a motion system

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)
van Berkel, K. ; Eindhoven Univ. of Technol., Eindhoven ; Rotariu, I. ; Steinbuch, M.

Iterative learning control (ILC) is an effective control technique for motion systems that perform repetitively the same trajectory (setpoint). The result of the learning procedure is a feedforward signal that perfectly compensates all deterministic dynamics in the system for the learned setpoint performed at a specific start position. For other setpoints and start positions, the learned feedforward signal will not be perfect, because the learned deterministic dynamics are setpoint- and position-dependent. In this paper cogging compensating piecewise ILC (CCPILC) is proposed that enables to use one learned feedforward signal for different setpoints and start positions without losing performance. The learned feedforward signal will therefore be decomposed into a setpoint- and a position-dependent part, such that both parts can be adapted individually according to the desired change in setpoint and/or start position.

Published in:

American Control Conference, 2007. ACC '07

Date of Conference:

9-13 July 2007