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Model Approximation using magnitude and phase criteria: Implications for Model Reduction and System Identification

Sandberg, Henrik; Lanzon, Alexander; Anderson, Brian

Description

In this paper, we use convex optimization for model reduction and identification of transfer functions. Two different approximation criteria are studied. When the first criterion is used, magnitude functions are matched, and when the second criterion is used, phase functions are matched. The weighted error bounds have direct interpretation in a Bode diagram, and are suitable to engineers working with frequency-domain data. We also show that transfer functions that have similar magnitude or...[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Journal article
URI: http://hdl.handle.net/1885/25534
Source: International Journal of Robust and Nonlinear Control
DOI: 10.1002/rnc.1124

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