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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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Author information

Authors and Affiliations

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

    Qinghua Zhang

Authors
  1. Qinghua Zhang
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Editor information

Editors and Affiliations

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

    John Baillieul

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

    Tariq Samad

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© 2015 Springer-Verlag London

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Zhang, Q. (2015). Nonlinear System Identification: An Overview of Common Approaches. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5058-9_104

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