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This example illustrates the effects of time-varying sources on estimation. The example also shows how to set time-varying sources to be constant during estimation to improve estimation results.
Open the Simulink^{®} model.
sys = 'scdspeed_ctrlloop';
open_system(sys);
Linearize the model.
Set the Engine Model block to normal mode for accurate linearization.
set_param('scdspeed_ctrlloop/Engine Model','SimulationMode','Normal')
Open the Linear Analysis Tool for the model.
In the Simulink Editor, select Analysis > Control Design > Linear Analysis.
Select the visualization for the linearized model.
In the Plot Result list, select New Bode.
Click .
The linearized model, linsys1, appears in the Linear Analysis Workspace.
Create an input sinestream signal for the estimation.
Open the Create sinestream input dialog box.
In the Frequency Response Estimation tab, select Sinestream in the Input Signal list.
Open the Add frequencies dialog box.
Click .
Specify the input sinestream frequency range and number of frequency points.
Enter 100 in the To box.
Enter 10 in the box for the number of frequency points.
Click OK.
The added points are visible in the Frequency content viewer of the Create sinestream input dialog box.
In the Frequency content viewer of the Create sinestream input dialog box, select all the frequency points.
Specify input sinestream parameters.
For this example, change the Number of periods and Settling periods to ensure that the model reaches steady-state for each frequency point in the input sinestream.
Enter 30 in the Number of periods box.
Enter 25 in the Settling periods box.
Create the input sinestream.
Click OK. The new input signal, in_sine1, appears in the Linear Analysis Workspace.
Select the visualization for the estimated model.
In the Plot Result list of the Linear Analysis Tool, select Bode Plot 1.
Set the Diagnostic Viewer to open when estimation is performed.
Select the Launch Diagnostic Viewer check box.
Estimate the frequency response for the model.
Click . The frequency response estimation result, estsys1, appears in the Linear Analysis Workspace.
Compare the estimated model and the linearized model.
Click the Diagnostic Viewer - estsys1 tab in the plot pane of the Linear Analysis Tool.
Click and drag linsys1 onto the Diagnostic Viewer to add linsys1 to the Diagnostic Viewer plots.
Click the Figures tab of the Linear Analysis Tool.
Configure the Diagnostic Viewer to show only the frequency point where the estimation and linearization results do not match.
In the Frequency Selector section, enter 9 in the From box and 11 in the To box to set the frequency range that is analyzed in the Diagnostic Viewer.
The Filtered Steady State Time Response plot depicts a signal that is not sinusoidal.
View the unfiltered time response.
Right-click the Filtered Steady State Time Response plot and clear the Show filtered steady state output only option.
The step input and external disturbances drive the model away from the operating point that the linearized model uses. This prevents the response from reaching steady-state. To correct this problem, find and disable the time-varying source blocks that interfere with the estimation. Then estimate the frequency response of the model again.
Find and disable the time-varying sources within the model.
Open the Options for frequency response estimation dialog box.
On the Frequency Response Estimation tab, in the Generate Results section, click Options.
In the Time Varying Sources tab, click Find and add time varying source blocks automatically.
This action populates the time varying sources list with the block paths of the time varying sources in the model. These sources will be held constant during estimation.
Estimate the frequency response for the model.
Click . The frequency response estimation result for the model, estsys2, appears in the Linear Analysis Workspace.
Compare the newly estimated model and the linearized model.
Click on the Diagnostic Viewer - estsys2 tab in the plot area of the Linear Analysis Tool.
Click and drag linsys1 onto the Diagnostic Viewer to add linsys1 to the Diagnostic Viewer plots.
The frequency response obtained by holding the time-varying sources constant matches the exact linearization results.
Compare the linear model obtained using exact linearization techniques with the estimated frequency response:
% Open the model mdl = 'scdspeed_ctrlloop'; open_system(mdl) io = getlinio(mdl); % Set the model reference to normal mode for accurate linearization set_param('scdspeed_ctrlloop/Engine Model','SimulationMode','Normal') % Linearize the model sys = linearize(mdl,io); % Estimate the frequency response between 10 and 100 rad/s in = frest.Sinestream('Frequency',logspace(1,2,10),'NumPeriods',30,'SettlingPeriods',25); [sysest,simout] = frestimate(mdl,io,in); % Compare the results frest.simView(simout,in,sysest,sys)
The linearization results do not match the estimated frequency response for the first two frequencies. To view the unfiltered time response, right-click the time response plot, and uncheck Show filtered steady state output only.
The step input and external disturbances drive the model away from the operating point, preventing the response from reaching steady-state. To correct this problem, find and disable these time-varying source blocks that interfere with the estimation.
Identify the time-varying source blocks using frest.findSources:
srcblks = frest.findSources(mdl,io);
Create a frestimate options set to disable the blocks.
opts = frestimateOptions; opts.BlocksToHoldConstant = srcblks;
Repeat the frequency response estimation using the optional input argument opts.
[sysest2,simout2] = frestimate(mdl,io,in,opts); frest.simView(simout2,in,sysest2,sys);
Now the resulting frequency response matches the exact linearization results. To view the unfiltered time response, right-click the time response plot, and uncheck Show filtered steady state output only.