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Data analysis from measurements (PRBS injected to a system -> how to plot the bode of the system response)

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I have data (measurements from a synchronous machine), a PRBS has been injected to the excitation system (AVR setpoint) and the output measurements have been collected (Active Power for example). So I have the perturbed setpoint (Set point of the regulator with the PRBS added to this SP, which is my input u), and I have the ouput y (Active Power P).
Now I need to trace the bode of P/SP (y/u). I'm mostly interseted in the low frequencies from 0.05 Hz to 20Hz (max 100Hz).
I would like to know, how I can proceed in Matlab, do I need a particular Toolbox ?
Any advice would be highly appreciated.
Thanks a lot

Akzeptierte Antwort

Mathieu NOE
Mathieu NOE am 20 Mai 2022
see my suggestion below (data in attachement)
data = load('beam_experiment.mat');
x = transpose(data.x); %input
y = transpose(data.y); %output
fs = data.fs; % sampling frequency
NFFT = 2048;
NOVERLAP = round(0.75*NFFT); % 75 % overlap
%% solution 1 with tfestimate (requires Signal Processing Tbx)
% [Txy,F] = tfestimate(x,y,hanning(NFFT),NOVERLAP,NFFT,fs);
%% alternative with supplied sub function
[Txy,Cxy,F] = mytfe_and_coh(x,y,NFFT,fs,hanning(NFFT),NOVERLAP); % t = transfer function (complex), Cxy = coherence, F = freq vector
% bode plots
function [Txy,Cxy,f] = mytfe_and_coh(x,y,nfft,Fs,window,noverlap)
% Transfer Function and Coherence Estimate
% compute PSD and CSD
window = window(:);
n = length(x); % Number of data points
nwind = length(window); % length of window
if n < nwind % zero-pad x , y if length is less than the window length
x = x(:); % Make sure x is a column vector
y = y(:); % Make sure y is a column vector
k = fix((n-noverlap)/(nwind-noverlap)); % Number of windows
% (k = fix(n/nwind) for noverlap=0)
index = 1:nwind;
Pxx = zeros(nfft,1);
Pyy = zeros(nfft,1);
Pxy = zeros(nfft,1);
for i=1:k
xw = window.*x(index);
yw = window.*y(index);
index = index + (nwind - noverlap);
Xx = fft(xw,nfft);
Yy = fft(yw,nfft);
Xx2 = abs(Xx).^2;
Yy2 = abs(Yy).^2;
Xy2 = Yy.*conj(Xx);
Pxx = Pxx + Xx2;
Pyy = Pyy + Yy2;
Pxy = Pxy + Xy2;
% Select first half
if ~any(any(imag([x y])~=0)) % if x and y are not complex
if rem(nfft,2) % nfft odd
select = [1:(nfft+1)/2];
select = [1:nfft/2+1]; % include DC AND Nyquist
Pxx = Pxx(select);
Pyy = Pyy(select);
Pxy = Pxy(select);
select = 1:nfft;
Txy = Pxy ./ Pxx; % transfer function estimate
Cxy = (abs(Pxy).^2)./(Pxx.*Pyy); % coherence function estimate
f = (select - 1)'*Fs/nfft;
  3 Kommentare
Mathieu NOE
Mathieu NOE am 23 Mai 2022
hello again
if you need a good quality FRF down to 0.1 Hz resolution , you need NFFT = 10 x Fs at least.
I don't know your Fs but the amont of samples must be larger than NFFT itself... so can be pretty large.
also plot your result with x axis in log scale to compare with the theoretical Bode plot.
all the best
Yannick CAIRE
Yannick CAIRE am 24 Mai 2022
Yes fs is 200Hz (0.005s period) and I have a large amount of points (24000).
It's gettting better with a NFFT around 6000 for example, but I think I can still improve it.

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Weitere Antworten (1)

Rajiv Singh
Rajiv Singh am 31 Mai 2022
This could be seen as an exercise in system identification. Use functions like TFEST,SSEST, ARX to fit a model to the (u,y) data. Then call BODE or FREQRESP on the model to get the frequency response.
Requires System Identification Toolbox.
  1 Kommentar
Yannick CAIRE
Yannick CAIRE am 16 Okt. 2022
Thanks, do you have an example using these functions ? Then I could start from somewhere, I have the input and ouput data captured at 5ms sampling interval, using a PRBS. Input is the PRBS + the setpoint of the system.

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