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Machine Intelligence Research
Published in: International Journal of Automation and Computing 3/2015

01-06-2015 | Regular Paper

Robust fault-tolerant iterative learning control for discrete systems via linear repetitive processes theory

Authors: Jian Ding, Blazej Cichy, Krzysztof Galkowski, Eric Rogers, Hui-Zhong Yang

Published in: Machine Intelligence Research | Issue 3/2015

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Abstract

This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multiple-output discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.
previous article Generalized norm optimal iterative learning control with intermediate point and sub-interval tracking
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Metadata
Title
Robust fault-tolerant iterative learning control for discrete systems via linear repetitive processes theory
Authors
Jian Ding
Blazej Cichy
Krzysztof Galkowski
Eric Rogers
Hui-Zhong Yang
Publication date
01-06-2015
Publisher
Institute of Automation, Chinese Academy of Sciences
Published in
Machine Intelligence Research / Issue 3/2015
Print ISSN: 2731-538X
Electronic ISSN: 2731-5398
DOI
https://doi.org/10.1007/s11633-015-0883-0

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