Please use this identifier to cite or link to this item: https://doi.org/10.1109/ACC.2009.5160036
Title: Iterative learning control with high-order internal model for linear time-varying systems
Authors: Liu, C.
Xu, J. 
Wu, J.
Issue Date: 2009
Source: Liu, C., Xu, J., Wu, J. (2009). Iterative learning control with high-order internal model for linear time-varying systems. Proceedings of the American Control Conference : 1634-1639. ScholarBank@NUS Repository. https://doi.org/10.1109/ACC.2009.5160036
Abstract: In this work we focus on iterative learning control (ILC) for iteratively varying reference trajectories which are described by a high-order internal model. The high-order internal model (HOIM) is formulated as a polynomial between two consecutive iterations. The classical ILC with iteratively invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders to a unity coefficient, in other words, the 0th order internal model. By inserting the polynomial (HOIM) into the past control input of the ILC law, and designing appropriate learning control gains, the learning convergence in the iteration axis can be guaranteed for continuous-time linear time varying (LTV) systems. The initial condition, P-type and D-type ILC, and possible extension to nonlinear cases are also explored. © 2009 AACC.
Source Title: Proceedings of the American Control Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/70721
ISBN: 9781424445240
ISSN: 07431619
DOI: 10.1109/ACC.2009.5160036
Appears in Collections:Staff Publications

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

SCOPUSTM   
Citations

6
checked on Dec 14, 2017

WEB OF SCIENCETM
Citations

4
checked on Nov 20, 2017

Page view(s)

27
checked on Dec 17, 2017

Google ScholarTM

Check

Altmetric


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