By Topic

Iterative learning control for systems with input deadzone

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)
Jian-Xin Xu ; Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore ; Jing Xu ; Tong Heng Lee

Most iterative learning control (ILC) schemes proposed hitherto were designed and analyzed without taking the input deadzone into account. Input deadzone is a kind of nonsmooth and nonaffine-in-input factor widely existing in actuators or mechatronics devices. It gives rise to extra difficulty due to the presence of singularity in the input channels. In this note, we disclose that ILC methodology remains effective for systems with input deadzone that could be nonlinear, unknown and state-dependent. Through rigorous proof, it is shown that despite the presence of the input deadzone, the simplest ILC scheme retains its ability of achieving the satisfactory performance.

Published in:

Automatic Control, IEEE Transactions on  (Volume:50 ,  Issue: 9 )