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An Optimal Two-stage Identification Algorithm for Hammerstein–Wiener Nonlinear Systems

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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

Consider a scalar stable discrete time nonlinear dynamic system represented by

$$ y(k) = \sum_{i=1}^{p} a_i \{ \sum_{l=1}^q d_l g_l[y(k-i)]\} + \sum_{j=1}^{n} b_j \{ \sum_{t=1}^{m} c_t f_t[u(k-j)] \} + \eta(k) $$
(1)

where y(k), u(k) and η(k) are the system output, input and disturbance at time k respectively. The g l (·)’s and f t (·)’s are non-linear functions

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References

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Author information

Authors and Affiliations

  1. Dept. of Elec. and Comp. Engineering, University of Iowa,  

    Er-Wei Bai

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  1. Er-Wei Bai
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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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Bai, EW. (2010). An Optimal Two-stage Identification Algorithm for Hammerstein–Wiener Nonlinear Systems. 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_3

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  • DOI: https://doi.org/10.1007/978-1-84996-513-2_3

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-512-5

  • Online ISBN: 978-1-84996-513-2

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