||Compare model output and measured output|
||Goodness of fit between test and reference data|
||Estimate initial states of model|
||Create parameter for initial states and input level estimation|
To create one or more plots of your models, select the corresponding check box in the Model Views area of the System Identification app.
This example shows how to validate an estimated model by comparing the simulated model output with measured data.
Available plot types and corresponding supported models.
Plotting transient response plots for models, including impulse response and step response, for all linear parametric models and correlation analysis models.
Plotting Bode and Nyquist plots for models.
Plotting the frequency-response of the estimated noise model for a linear system.
Plotting pole-zero plots for linear parametric models and using pole-zero plots to gain insight into model-order reduction.
Set plot preferences that persist from session to session.
Understanding the difference between simulated and predicted output.
Blocks for importing and simulating models from the MATLAB® environment into a Simulink® model.
Computing model parameter uncertainty of linear models.