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Ensuring Certain Physical Properties in Black Box Models by Applying Fuzzy Techniques
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1997 (English)In: Proceedings of the 11th IFAC Symposium on System Identification, 1997, Vol. 1, 721-727 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider the situation where a nonlinear physical system is identified from input-output data. In case no specific physical structural knowledge about the system is available, parameterized grey box models cannot be used. Identification in black-box-type of model structures is then the only alternative, and general approaches like neural nets, neuro-fuzzy models, etc., have to be applied.However, certain non-structural knowledge about the system is sometimes available. It could be known, e.g., that the step response is monotonic, or that the steady-state gain curve is monotonic. The question is then how to utilize and maintain such knowledge in a black box framework.In this paper we show how to incorporate this type of prios information in an otherwise black box environment, by applying a specific fuzzy model structure, with strict parametric constraints. The usefulness of the apporach is illustrated by experiments on real-world data.

Place, publisher, year, edition, pages
1997. Vol. 1, 721-727 p.
Keyword [en]
Fuzzy modeling and identification, Nonlinear systems, Monotonicity
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-93805ISBN: 0080425925 (print)OAI: oai:DiVA.org:liu-93805DiVA: diva2:626699
Conference
11th IFAC Symposium on System Identification, Fukuoka, Japan, July, 1997
Available from: 2013-06-10 Created: 2013-06-10 Last updated: 2013-06-10

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Ljung, Lennart

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