Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2005.854658
Title: Iterative learning control for systems with input deadzone
Authors: Xu, J.-X. 
Xu, J. 
Lee, T.H. 
Keywords: Convergence analysis
Input deadzone
Iterative learning control
Nonlinear dynamics
Issue Date: Sep-2005
Source: Xu, J.-X.,Xu, J.,Lee, T.H. (2005-09). Iterative learning control for systems with input deadzone. IEEE Transactions on Automatic Control 50 (9) : 1455-1459. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2005.854658
Abstract: 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. © 2005 IEEE.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/56427
ISSN: 00189286
DOI: 10.1109/TAC.2005.854658
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

33
checked on Dec 13, 2017

WEB OF SCIENCETM
Citations

27
checked on Nov 1, 2017

Page view(s)

29
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.