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Worst-case analysis of identification - BIBO robustness for closed loop data

Partington, J.R. and Makila, P.M. (1994) Worst-case analysis of identification - BIBO robustness for closed loop data. IEEE Transactions on Automatic Control, 39 (10). pp. 2171-2176. ISSN 0018-9286


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This paper deals with the worst-case analysis of identification of linear shift-invariant (possibly) infinite-dimensional systems. A necessary and sufficient input richness condition for the existence of robustly convergent identification algorithms in l1 is given. A closed-loop identification setting is studied to cover both stable and unstable (but BIBO stabilizable) systems. Identification (or modeling) error is then measured by distance functions which lead to the weakest convergence notions for systems such that closed-loop stability, in the sense of BIBO stability, is a robust property. Worst-case modeling error bounds in several distance functions are included

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 1994 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds)
Depositing User: Sherpa Assistant
Date Deposited: 30 Sep 2005
Last Modified: 10 Jun 2014 08:35
Published Version: http://dx.doi.org/10.1109/9.328804
Status: Published
Refereed: Yes
Identification Number: 10.1109/9.328804
URI: http://eprints.whiterose.ac.uk/id/eprint/697

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