NDLI: Model synthesis weighting effects on model tuning in system identification

Content Provider	IEEE Xplore Digital Library
Author	Nimityongskul, S. Lacy, S. Babuska, V.
Copyright Year	2008
Description	Author affiliation: Wisconsin-Madison Univ., Madison, WI (Nimityongskul, S.)
Abstract	System identification is the process of deriving dynamic equations from observed system behavior, the inverse of the common problem of deriving solutions to a given set of dynamics. The system identification process generally consists of two steps, a model synthesis step followed by a model tuning step. For complex systems, standard system identification tools often fail to provide satisfactory results without extensive manipulation by an experienced engineer. Input, output, and frequency weightings are often used to adjust the properties of the identified model in model tuning. In this effort, we examine the impact of model synthesis weightings on model tuning results. Model synthesis weightings are shown to improve the initial models used for model tuning. However, it is shown that an improved initial model for model tuning does not necessarily lead to faster model tuning or more accurate identified models.
Starting Page	638
Ending Page	643
File Size	224771
Page Count	6
File Format	PDF
ISBN	9781424420780
ISSN	07431619
DOI	10.1109/ACC.2008.4586564
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	System identification Frequency Tuning Control system synthesis State-space methods Cost function Computational modeling Equations Singular value decomposition Observability
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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