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Encyclopedia of Systems and Control pp 1–10Cite as

Nonlinear System Identification: An Overview of Common Approaches

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Abstract

Nonlinear mathematical models are essential tools in various engineering and scientific domains, where more and more data are recorded by electronic devices. How to build nonlinear mathematical models essentially based on experimental data is the topic of this entry. Due to the large extent of the topic, this entry provides only a rough overview of some well-known results, from gray-box to black-box system identification.

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Author information

Authors and Affiliations

  1. Inria, Campus de Beaulieu, 35042 Rennes Cedex, France

    Qinghua Zhang

Authors
  1. Qinghua Zhang
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Corresponding author

Correspondence to Qinghua Zhang .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Division of Automatic Control, Department of Electrical Engineering, Linköping University, Linköping, Sweden

    Lennart Ljung

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Zhang, Q. (2019). Nonlinear System Identification: An Overview of Common Approaches. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_104-2

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_104-2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Nonlinear System Identification: An Overview of Common Approaches
    Published:
    26 September 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_104-2

  2. Original

    Nonlinear System Identification: An Overview of Common Approaches
    Published:
    29 March 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_104-1

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