Generate a Bode plot.

sys = rss(5);
h = bodeplot(sys);

Change the units to Hz and suppress the phase plot. To do so, edit properties of the plot handle, h.

setoptions(h,'FreqUnits','Hz','PhaseVisible','off');

The plot automatically updates when you call setoptions.

Create a Bode plot of a dynamic system.

sys = tf(1,[1 1]); 
h = bodeplot(sys);

Fix the phase at 1 rad/s to 750 degrees. To do so, get the plot properties. Then alter the properties PhaseMatchingFreq and PhaseMatchingValue to match a phase to a specified frequency.

p = getoptions(h); 
p.PhaseMatching = 'on'; 
p.PhaseMatchingFreq = 1; 
p.PhaseMatchingValue = 750;

Update the plot.

setoptions(h,p);

The first bode plot has a phase of -45 degrees at a frequency of 1 rad/s. Setting the phase matching options so that at 1 rad/s the phase is near 750 degrees yields the second Bode plot. Note that, however, the phase can only be -45 + N*360, where N is an integer, and so the plot is set to the nearest allowable phase, namely 675 degrees (or 2*360 - 45 = 675).

Compare the frequency responses of identified state-space models of order 2 and 6 along with their 2 $$\sigma$$ confidence regions.

load iddata1
sys1 = n4sid(z1, 2); 
sys2 = n4sid(z1, 6);

Both models produce about 70% fit to data. However, sys2 shows higher uncertainty in its frequency response, especially close to Nyquist frequency as shown by the plot:

w = linspace(8,10*pi,256);
h = bodeplot(sys1,sys2,w);
setoptions(h,'PhaseMatching','on','ConfidenceRegionNumberSD',2);

Right-click the plot and select Characteristics > Confidence Region to turn on the confidence region characteristic. Alternatively, type showConfidence(h) to plot the confidence region.

Compare the frequency response of a parametric model, identified from input/output data, to a nonparametric model identified using the same data. Identify parametric and non-parametric models based on data.

load iddata2 z2;
w = linspace(0,10*pi,128);
sys_np = spa(z2,[],w);
sys_p = tfest(z2,2);

spa and tfest require System Identification Toolbox™ software. sys_np is a nonparametric identified model. sys_p is a parametric identified model.

Create a Bode plot that includes both systems.

opt = bodeoptions;  
opt.PhaseMatching = 'on';
bodeplot(sys_np,sys_p,w,opt);