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Iteration domain H-infinity-optimal iterative learning controller design

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Abstract
This paper presents an H-infinity-based design technique for the synthesis of higher-order iterative learning controllers (ILCs) for plants subject to iteration-domain input/output disturbances and plant model uncertainty. Formulating the higher-order ILC problem into a high-dimensional multivariable discrete-time system framework, it is shown how the addition of input/output disturbances and plant model uncertainty to the TLC problem can be cast as an H-infinity-norm minimization problem. The distinctive feature of this formulation is to consider the uncertainty as arising in the iteration domain rather than the time domain. An algebraic approach to solving the problem in this framework is presented, resulting in a sub-optimal controller that can achieve both stability and robust performance. The key observation is that H-infinity synthesis can be used for higher-order ILC design to achieve a reliable performance in the presence of iteration-varying external disturbances and model uncertainty. Copyright (C) 2007 John Wiley & Sons, Ltd.
Author(s)
Moore, Kevin L.Ahn, Hyo-SungChen, Yang Quan
Issued Date
2008-06
Type
Article
DOI
10.1002/rnc.1231
URI
https://scholar.gist.ac.kr/handle/local/17349
Publisher
John Wiley & Sons Inc.
Citation
International Journal of Robust and Nonlinear Control, v.18, no.10, pp.1001 - 1017
ISSN
1049-8923
Appears in Collections:
Department of Mechanical and Robotics Engineering > 1. Journal Articles
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