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Compare Output with Measured Data

Plot simulated or predicted output and measured data for comparison, compute best fit values


compare Compare model output and measured output
goodnessOfFit Goodness of fit between test and reference data
findstates Estimate initial states of model
idpar Create parameter for initial states and input level estimation
compareOptions Option set for compare
findstatesOptions Option set for findstates

Examples and How To

Plot Models in the System Identification App

To create one or more plots of your models, select the corresponding check box in the Model Views area of the System Identification app.

Compare Simulated Output with Measured Data

This example shows how to validate an estimated model by comparing the simulated model output with measured data.


Supported Model Plots

Available plot types and corresponding supported models.

Impulse and Step Response Plots

Plotting transient response plots for models, including impulse response and step response, for all linear parametric models and correlation analysis models.

Frequency Response Plots

Plotting Bode and Nyquist plots for models.

Noise Spectrum Plots

Plotting the frequency-response of the estimated noise model for a linear system.

Pole and Zero Plots

Plotting pole-zero plots for linear parametric models and using pole-zero plots to gain insight into model-order reduction.

Toolbox Preferences Editor

Set plot preferences that persist from session to session.

Simulating and Predicting Model Output

Understanding the difference between simulated and predicted output.

Simulating Identified Model Output in Simulink

Blocks for importing and simulating models from the MATLAB® environment into a Simulink® model.

Computing Model Uncertainty

Computing model parameter uncertainty of linear models.

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