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Worst-case analysis of identification: BIBO robustness for closed loop data
School of Mathematics, University of Leeds.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
1994 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 39, no 10, 2171-2176 p.Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
1994. Vol. 39, no 10, 2171-2176 p.
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-10276DOI: 10.1109/9.328804Local ID: 90eab210-bf84-11db-834c-000ea68e967bOAI: oai:DiVA.org:ltu-10276DiVA: diva2:983218
Note
Godkänd; 1994; 20070218 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-21Bibliographically approved

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