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Nonlinear model identification for Artemia population motion

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Abstract

In this paper, two different nonlinear models for Artemia swarming are derived. In order to generate the data suitable for identification, a robot driving the Artemia population has been built. The obtained data have been then used to identify the parameters of a model based on Newton’s equations and a black-box NARX model implemented by neural networks. The performances obtained validate the physical hypotheses underlying the gray-box model.

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Authors and Affiliations

  1. Electrical Engineering Department, University of Basrah, Basrah, Iraq

    Mofeed Turky Rashid, Abduladhem Abdulkareem Ali & Ramzy Salim Ali

  2. Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Universit´a degli Studi di Catania, Catania, Italy

    Mattia Frasca & Luigi Fortuna

  3. DiSIA, Facoltà di Ingegneria, Università degli Studi di Messina, Messina, Italy

    Maria Gabriella Xibilia

Authors
  1. Mofeed Turky Rashid
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  2. Mattia Frasca
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  3. Abduladhem Abdulkareem Ali
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  4. Ramzy Salim Ali
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  5. Luigi Fortuna
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  6. Maria Gabriella Xibilia
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Corresponding author

Correspondence to Mattia Frasca.

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Rashid, M.T., Frasca, M., Ali, A.A. et al. Nonlinear model identification for Artemia population motion. Nonlinear Dyn 69, 2237–2243 (2012). https://doi.org/10.1007/s11071-012-0422-2

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  • DOI: https://doi.org/10.1007/s11071-012-0422-2

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