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## 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

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