Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/491
Title: Algorithms for worst case identification in H-infinity and the nu-gap metric
Authors: Date, P
Vinnicombe, G
Keywords: Robust identification;Identification for control;ν-gap metric
Issue Date: 2004
Publisher: Elsevier Science
Citation: Automatica, 40: 995-1002, Mar 2004
Abstract: This paper considers two robustly convergent algorithms for the identification of a linear system from (possibly) noisy frequency response data. Both algorithms are based on the same principle; obtaining a good worst case fit to the data under a smoothness constraint on the obtained model. However they differ in their notions of distance and smoothness. The first algorithm yields an FIR model of a stable system and is optimal, in a certain sense for a finite model order. The second algorithm may be used for modelling unstable plants and yields a real rational approximation in the -gap. Given a model and a controller stabilising the true plant, a procedure for winding number correction is also suggested.
URI: http://bura.brunel.ac.uk/handle/2438/491
DOI: http://dx.doi.org/10.1016/j.automatica.2004.01.019
Appears in Collections:Mathematical Science
Computer Science
Dept of Mathematics Research Papers

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