Linear System Identification

  • Gennady G. Kulikov
  • Haydn A. Thompson
Part of the Advances in Industrial Control book series (AIC)


In general there are two ways of arriving at models of physical processes:
  • Physical principles modelling. Physical knowledge of the process, in the form of first principles, is employed to arrive at a model that will generally consist of a multitude of differential / partial differential / algebraic relations between physical quantities. The construction of a model is based on presumed knowledge about the physics that governs the process. The first principles relations concern, e.g., the laws of conservation of energy and mass and Newton’s law of movement.

  • Experimental modelling, or system identification. Measurements of several variables of the process are taken and a model is constructed by identifying a model that matches the measured data as well as possible.


Cost Function Binary Signal Auto Regressive Maximum Likelihood Estimator Crest Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Gennady G. Kulikov
    • 1
  • Haydn A. Thompson
    • 2
  1. 1.Department of Automated Control SystemsUfa State Aviation Technical UniversityRussia
  2. 2.Department of Automatic Control and Systems EngineeringThe University of SheffieldSheffieldUK

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