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Refined Instrumental Variable Methods for Hammerstein Box-Jenkins Models

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System Identification, Environmental Modelling, and Control System Design

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Abstract

This chapter presents an estimation method for Hammerstein models under colored added noise conditions. The proposed method is detailed for both continuous-time and discrete-time models and is based on the refined instrumental variable method. In order to use a regression form, the Hammerstein model is reformulated as an augmented multi-input-single-output linear time invariant model. The performance of the proposed methods are exposed through relevant Monte Carlo simulation examples.

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Notes

  1. 1.

    f:ℝn↦ℝ is a real meromorphic function if f=g/h with g,h analytic and h≠0.

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Authors and Affiliations

  1. CNRS, Nancy-Université, Vandoeuvre-lès-Nancy Cedex, France

    Vincent Laurain, Marion Gilson & Hugues Garnier

Authors
  1. Vincent Laurain
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  2. Marion Gilson
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  3. Hugues Garnier
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Corresponding author

Correspondence to Vincent Laurain .

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Editors and Affiliations

  1. Computer Engineering, RMIT University, Swanston Street 10, Melbourne, 3000, Victoria, Australia

    Liuping Wang

  2. Centre de Recherche en, Automatique de Nancy, Université Nancy I, Vandoeuvre-les-Nancy CX, France

    Hugues Garnier

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Laurain, V., Gilson, M., Garnier, H. (2012). Refined Instrumental Variable Methods for Hammerstein Box-Jenkins Models. In: Wang, L., Garnier, H. (eds) System Identification, Environmental Modelling, and Control System Design. Springer, London. https://doi.org/10.1007/978-0-85729-974-1_2

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  • DOI: https://doi.org/10.1007/978-0-85729-974-1_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-973-4

  • Online ISBN: 978-0-85729-974-1

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