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Nonlinear Structure Identification with Linear Least Squares and ANOVA
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2005 (English)In: Proceedings of the 16th IFAC World Congress, 2005, 8-8 p.Conference paper (Refereed)
Abstract [en]

The objective of this paper is to find the structure of a nonlinear system from measurement data, as a prior step to model estimation. Applying ANOVA directly on a dataset is compared to applying ANOVA on residuals from a linear model. The distributions of the involved test variables are computed and used to show that ANOVA is effective in finding which regressors give linear effects and what regressors produce nonlinear effects. The ability to find nonlinear substructures depending on only subsets of regressors is an ANOVA feature which is shown not to be affected by subtracting a linear model.

Place, publisher, year, edition, pages
2005. 8-8 p.
Keyword [en]
System identification, Nonlinear systems, Structural properties, Analysis of variance, Linear estimation
National Category
Engineering and Technology Control Engineering
URN: urn:nbn:se:liu:diva-31772DOI: 10.3182/20050703-6-CZ-1902.00009Local ID: 17596ISBN: 978-3-902661-75-3OAI: diva2:252595
16th IFAC World Congress, Prague, Czech Republic, July, 2005
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-04-16

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Lind, Ingela
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Automatic ControlThe Institute of Technology
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