Estimate Impulse-Response Models Using System Identification App

Before you can perform this task, you must have:

Imported data into the System Identification app. SeeImport Time-Domain Data into the App. For supported data formats, seeData Supported by Correlation Analysis.
Performed any required data preprocessing operations. To improve the accuracy of your model, you should detrend your data. SeeWays to Prepare Data for System Identification.

To estimate in the System Identification app using time-domain correlation analysis:

In the System Identification app, selectEstimate>Correlation modelsto open the Correlation Model dialog box.
In theTime span (s)field, specify a scalar value as the time interval over which the impulse or step response is calculated. For a scalar time spanT, the resulting response is plotted from-T/4toT.

Tip

You can also enter a 2-D vector in the format[min_value max_value].
In theOrder of whitening filterfield, specify the filter order.
The prewhitening filter is determined by modeling the input as an autoregressive process of orderN. The algorithm applies a filter of the formA(q)u(t)=u_F(t). That is, the inputu(t)is subjected to an FIR filterAto produce the filtered signalu_F(t).Prewhiteningthe input by applying a whitening filter before estimation might improve the quality of the estimated impulse responseg.
The order of the prewhitening filter,N, is the order of theAfilter.Nequals the number of lags. The default value ofNis10, which you can also specify as[].
In theModel Namefield, enter the name of the correlation analysis model. The name of the model should be unique in the Model Board.
ClickEstimateto add this model to the Model Board in the System Identification app.
In the Correlation Model dialog box, clickClose.

Export the model to the MATLAB^®workspace for further analysis by dragging it to theTo Workspacerectangle in the System Identification app.
View the transient response plot by selecting theTransient respcheck box in the System Identification app. For more information about working with this plot and selecting to view impulse- versus step-response, seeImpulse and Step Response Plots.

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