Estimate Frequency Response with Linearization-Based Input Using Linear Analysis Tool

This example shows how to perform frequency response estimation for a model using the Linear Analysis Tool. The input signal used for estimation is based on the linearization of the model.

Step 1. Linearize Simulink model.

  • Open Simulink® model.

    sys = 'scdDCMotor';
  • Open the Linear Analysis Tool for the model.

    In the Simulink Editor, select Analysis > Control Design > Linear Analysis.

  • In the Plot Result list, choose New Bode.

  • Linearize the model.

    Click . A new linearized model, linsys1, appears in the Linear Analysis Workspace.

    The software used the model initial conditions as the operating point to generate linsys1.

Step 2. Create sinestream input signal.

  • Click the Frequency Response Estimation tab.

    In this tab, you estimate the frequency response of the model.

  • Open the Create sinestream input dialog box.

    Select Sinestream from the Input Signal list to open the Create sinestream input dialog box.

  • Initialize the input signal frequencies and parameters based on linsys1.

    Click Initialize frequencies and parameters.

    The Frequency content viewer is populated with frequency points. The software chooses the frequencies and input signal parameters automatically based on the dynamics of linsys1.

  • In the Frequency content viewer of the Create sinestream input dialog box, select all the frequency points.

  • Specify the amplitude of the input signal.

    Enter 1 in the Amplitude box.

  • Create the input sinestream signal.

    Click OK. The input signal in_sine1 appears in the Linear Analysis Workspace.

Step 3. Select the plot to display the estimation result.

In the Plot Result list, choose Bode Plot 1 to add the next computed linear system to Bode Plot 1.

Step 4. Estimate frequency response.

Click . The estimated system, estsys1, appears in the Linear Analysis Workspace.

Step 5. Examine estimation results.

Bode Plot 1 now shows the Bode responses for the estimated model and the linearized model.

The frequency response for the estimated model matches that of the linearized model.

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