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Experimentelle Modellbildung Zur Digitalen Simulation

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Simulationstechnik

Part of the book series: Informatik-Fachberichte ((INFORMATIK,volume 109))

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Zusammenfassung

Die Modellbildung ist eine notwendige Voraussetzung für Simulationsaufgaben. Ist eine theoretische Modellbildung nicht möglich, so muß das Modell durch eine experimentelle Analyse geschätzt werden. In dieser Arbeit werden verschiedene Verfahren zur experimentellen Modellbildung vorgestellt, welche sich besonders für die Verwendung in digitalen on-line Simulationen eignen.

Summary

The model design is a neccessary prerequisite for simulation tasks. If it is impossible to find a model by theoretical studies, it must be estimated by an experimental analysis. In this paper different methods for the experimental analysis are presented. They can specially be used in connection with digital on-line simulations.

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Literatur

  1. Unbehauen, H., Regelungstechnik I, Vieweg-Verlag, Braunschweig, 1982

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  2. Unbehauen, H., Regelungstechnik III, Vieweg-Verlag, Braunschw., 1985

    MATH  Google Scholar 

  3. Rajbman, N.S., Identification of industrial processes, North-Holland Publ.Comp., Amsterdam, 1980

    MATH  Google Scholar 

  4. Unbehauen, H., et al., Parameterschätzverfahren zur Systemidentifikation, Oldenbourg-Verlag, München, 1974

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  5. Isermann, R., Prozeßidentifikation, Springer, Berlin 1974

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  6. Eykhoff, P. (Ed.), Trends and Progress in System Identification, Pergamon Press, Oxford, 1981

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  7. Diekmann, K., Unbehauen, H., Test for determining the order of canonical models, IFAC-Symp. “Theory and Appl.of Digital Control”, Neu Dehli, 1982

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  8. Diekmann, K., Unbehauen, H., Application of MIMO-Identification to a blast furnace, IFAC-Symp. “Identification and System Parameter Estimation”, Washington 1982

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  9. Astroem, K., Mayne, D.Q., A new algorithm for recursive estimation of controlled ARMA processes, ibid

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  10. Diekmann, K., Appl. of parameter estimation methods to time variant systems, IFAC-Symp. “Digital Computer Applications”, Wien, 1985.

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© 1985 Springer-Verlag Berlin Heidelberg

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Diekmann, K. (1985). Experimentelle Modellbildung Zur Digitalen Simulation. In: Möller, D.P.F. (eds) Simulationstechnik. Informatik-Fachberichte, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-70640-0_8

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  • DOI: https://doi.org/10.1007/978-3-642-70640-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-15700-7

  • Online ISBN: 978-3-642-70640-0

  • eBook Packages: Springer Book Archive

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