Appendix D: Identification of linear models

Appendix D: Identification of linear models

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Our aim is to introduce the reader into the practical aspects of identification process and to describe how to perform identification using the capabilities of MATLAB® and Simulink®. First, we shall briefly present identification of black-box models based on the most often used in practice model structures and methods for their parameters estimation. Next, we describe shortly the gray-box identification approach based on the linear state-space model.

Chapter Contents:

  • D.1 Identification of linear black-box model
  • D.1.1 Experiment design and input/output data acquisition
  • D.1.2 Model structure selection and parameters estimation
  • D.1.3 Model validation
  • D.1.3.1 Test consistency of model input–output behavior
  • D.1.3.2 Test of output signals
  • D.1.3.3 Test of parameters confidence interval
  • D.1.3.4 Pole zero test
  • D.1.3.5 Test of residuals
  • D.2 Identification of linear gray-box model
  • D.3 Notes and references

Inspec keywords: state-space methods; parameter estimation

Other keywords: linear model; model structures; black-box models; parameter estimation; linear state-space model; identification process; Simulink; Matlab; gray-box identification approach

Subjects: Simulation, modelling and identification

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