Estimate Frequency Response Models with Noise Using
System Identification Toolbox
Open the Simulink model, and specify which portion of the model to linearize:
load_system('magball');
io(1) = linio('magball/Desired Height',1);
io(2) = linio('magball/Magnetic Ball Plant',1,'output');
Compute the steady-state operating point, and linearize the model:
op = findop('magball',operspec('magball'),...
findopOptions('DisplayReport','off'));
sys = linearize('magball',io,op);
Create a chirp signal, and use it to estimate the frequency response:
in = frest.Chirp('FreqRange',[1 1000],...
'Ts',0.001,...
'NumSamples',1e4);
[~,simout] = frestimate('magball',io,op,in);
Use System Identification Toolbox software to estimate a fifth-order, state-space model.
Compare the results of analytical linearization and the state-space model:
input = generateTimeseries(in);
output = simout{1}.Data;
data = iddata(output,input.Data(:),in.Ts);
sys_id = n4sid(detrend(data),5,'cov','none');
bodemag(sys,ss(sys_id('measured')),'r')
legend('Linear model obtained using LINEARIZE',...
'State-space model using System Identification Toolbox',...
'Location','SouthWest')
Estimate Frequency Response Models with Noise Using System Identification Toolbox