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Semi-Empirical Modeling of Non-Linear Dynamic Systems through Identification of Operating Regimes and Local Models

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Neural Network Engineering in Dynamic Control Systems

Part of the book series: Advances in Industrial Control ((AIC))

Abstract

An off-line algorithm for semi-empirical modeling of nonlinear dynamic systems is presented. The model representation is based on the interpolation of a number of simple local models, where the validity of each local model is restricted to an operating regime, but where the local models yield a complete global model when interpolated. The input to the algorithm is a sequence of empirical data and a set of candidate local model structures. The algorithm searches for an optimal decomposition into operating regimes, and local model structures. The method is illustrated using simulated and real data. The transparency of the resulting model and the flexibility with respect to incorporation of prior knowledge is discussed.

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Authors and Affiliations

  1. Department of Engineering Cybernetics, Norwegian Institute of Technology, 7034, Trondheim, Norway

    Tor A. Johansen & Bjarne A. Foss

Authors
  1. Tor A. Johansen
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  2. Bjarne A. Foss
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Editor information

Editors and Affiliations

  1. Daimler-Benz AG, Alt Moabit 96 a, D-10559, Berlin, Germany

    Kenneth J. Hunt

  2. Department of Electrical and Electronic Engineering, Queen’s University of Belfast, Belfast, BT9 5AH, UK

    George R. Irwin

  3. Department of Cybernetics, School of Engineering and Information Sciences, University of Reading, P.O. Box 225, Whiteknights, Reading, RG6 2AY, UK

    Kevin Warwick

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© 1995 Springer-Verlag London Limited

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Johansen, T.A., Foss, B.A. (1995). Semi-Empirical Modeling of Non-Linear Dynamic Systems through Identification of Operating Regimes and Local Models. In: Hunt, K.J., Irwin, G.R., Warwick, K. (eds) Neural Network Engineering in Dynamic Control Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-3066-6_6

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  • DOI: https://doi.org/10.1007/978-1-4471-3066-6_6

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-3068-0

  • Online ISBN: 978-1-4471-3066-6

  • eBook Packages: Springer Book Archive

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