You can obtain identification data by:
Measuring input and output signals from a physical system.
Your data must capture the important system dynamics, such as dominant time constants. After measuring the signals, organize the data into variables, as described in Representing Data in MATLAB Workspace. Then, import it in the System Identification app or represent it as a data object for estimating models at the command line.
Generating an input signal with desired characteristics, such as a random Gaussian or binary signal or a sinusoid, using idinput. Then, generate an output signal using this input to simulate a model with known coefficients. For more information, see Generate Data Using Simulation.
Using input/output data thus generated helps you study the impact of input signal characteristics and noise on estimation.
Logging signals from Simulink® models.
This technique is useful when you want to replace complex components in your model with identified models to speed up simulations or simplify control design tasks. For more information on how to log signals, see Export Signal Data Using Signal Logging in the Simulink documentation.