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Mutual Impact of Computing Power and Control Theory pp 195–211Cite as

Identification of Data-Compatible Models for Control Applications

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Abstract

This paper considers, in the context of Errors-in-Variables identification schemes, the Frisch scheme where a whole family of data-compatible models can be selected. A simple criterion to select a model which minimizes the one-step-ahead prevision error is then developed for applications where this performance is more important than the accuracy in the description of the process behind the data. The results of several simulations are then proposed to evaluate the criterion behaviour.

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References

  1. Kalman, R.E., (1982). Identification from Real Data, Current developments in the interface: Economics, Econometrics, Mathematic, edited by M. Hazewinkel and H.G. Rinnooy Kan, D. Reidel, Dordrecht, 161–196.

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  2. Beghelli S., R.P. Guidorzi and U. Soverini (1990). The Frisch Scheme in Dynamic System Identification, Automatica, Special Issue on Identification and System Parameter Estimation, 26, 171–176.

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  3. Guidorzi, R.P. (1991). Certain Models from Uncertain Data: the Dynamic case. Systems & Control Letters, 17, 415–424.

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  4. Beghelli S., P. Castaldi, R. P. Guidorzi and U. Soverini (1992). A Comparison Between Different Estimation Schemes on a Simulated System. Res. Rept. DS1–1–92, Dip. di Elettronica, Informatica e Sistemistica dell’Università di Bologna.

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Author information

Authors and Affiliations

  1. Department of Electronics Systems and Computer Science, University of Bologna, Bologna, Italy

    R. P. Guidorzi

  2. Department of Automatic Control, Polytechnic Institute of Bucharest, Bucharest, Roumania

    A. Stoian

Authors
  1. R. P. Guidorzi
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  2. A. Stoian
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Editor information

Editors and Affiliations

  1. Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic

    M. Kárný

  2. School of Engineering and Information Sciences, University of Reading, Reading, UK

    K. Warwick

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© 1993 Springer Science+Business Media New York

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Guidorzi, R.P., Stoian, A. (1993). Identification of Data-Compatible Models for Control Applications. In: Kárný, M., Warwick, K. (eds) Mutual Impact of Computing Power and Control Theory. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2968-2_14

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  • DOI: https://doi.org/10.1007/978-1-4615-2968-2_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6291-3

  • Online ISBN: 978-1-4615-2968-2

  • eBook Packages: Springer Book Archive

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