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NARX Identification of Hammerstein Systems Using Least-Squares Support Vector Machines

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Block-oriented Nonlinear System Identification

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 404))

Abstract

This chapter describes a method for the identification of a SISO and MIMO Hammerstein systems based on Least Squares Support Vector Machines (LS-SVMs). The aim of this chapter is to give a practical account of the works [14] and [15], adding to this material new insights published since. The identification method presented in this chapter gives estimates for the parameters governing the linear dynamic block represented as an ARX model, as well as for the unknown static nonlinear function.

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Author information

Authors and Affiliations

  1. ING Life Belgium, Sint Michielswarande 70, B-1040, Etterbeek, Belgium

    Ivan Goethals

  2. Department of Information Technology, division Syscon, Uppsala University, Box 337, SE-751 05, Uppsala, Sweden

    Kristiaan Pelckmans

  3. ESAT-SCD-SISTA, Katholieke Universiteit Leuven, Kasteelpark 10, B-3001, Leuven, Heverlee, Belgium

    Tillmann Falck, Johan A. K. Suykens & Bart De Moor

Authors
  1. Ivan Goethals
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  2. Kristiaan Pelckmans
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  3. Tillmann Falck
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  4. Johan A. K. Suykens
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  5. Bart De Moor
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Editors and Affiliations

  1. Laboratoire GREYC, Ensicaen, Campus Cote de Nacre, Boulevard du Marechal Juin, BP 5186, 14032, Caen Cedex, France

    Fouad Giri

  2. Seamans Center for the Engineering Arts and Sciences, The University of Iowa, 52242 1527, Iowa City, IA, USA

    Er-Wei Bai

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Goethals, I., Pelckmans, K., Falck, T., Suykens, J.A.K., De Moor, B. (2010). NARX Identification of Hammerstein Systems Using Least-Squares Support Vector Machines. In: Giri, F., Bai, EW. (eds) Block-oriented Nonlinear System Identification. Lecture Notes in Control and Information Sciences, vol 404. Springer, London. https://doi.org/10.1007/978-1-84996-513-2_15

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  • DOI: https://doi.org/10.1007/978-1-84996-513-2_15

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-512-5

  • Online ISBN: 978-1-84996-513-2

  • eBook Packages: EngineeringEngineering (R0)

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