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Nonlinear System Identification: An Overview of Common Approaches

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Encyclopedia of Systems and Control
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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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Correspondence to Qinghua Zhang .

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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