How can I estimate transfer function from frequency data?

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Hello, I have magnitude and phase data of a system in frequency domain:
I want to derive its transfer fuction with the following code:
load('Magnitude.mat');
load('Phase.mat');
load('freq.mat');
data = frd(Magnitude.*exp(1j*Phase*pi/180),freq); % Frequency-response data model
np = 6; % # of poles
nz = 6; % # of zeros
iodelay = NaN;
sys = tfest(data,np,nz,iodelay);
bodeplot(sys,{2*pi*1e0,2*pi*1e6})
sys.Report.Fit
h1 = gcr;
setoptions(h1,'FreqUnits','Hz')
setoptions(h1,'MagUnits','abs')
Here is the result:
The estimated TF does not fit well with the phase angle but fit percent report is 98% and MSE is very high (3.6e6). I tried it for any number of zeros and poles but I got even worse results.
Could you please help me to solve it?
Thanks

回答(1 个)

Star Strider
Star Strider 2022-5-13
编辑:Star Strider 2022-5-13
The best way to see how well the estimated system fits the data is to use the compare function.
Change (increase) ‘np’ using only the number of poles (initially use the default value for the number of zeros and if necessary, fine-tune later with ‘nz’) until you get an appropriate fit.
EDIT — (13 May 2022 at 14:50)
Increase the system order. I was able to get an acceptable fit to both the magnitude and phase with:
ord = 22;
sys = ssest(data,ord);
Also:
figure
compare(data,sys)
% sys.Report.Fit
h1 = gcr;
setoptions(h1,'FreqUnits','Hz')
setoptions(h1,'MagUnits','abs')
.
  2 个评论
Easa AliAbbasi
Easa AliAbbasi 2022-5-14
Thank you. I increased the order to 12 which is the best order calculated by MATLAB for my system
and here is the report:
FitPercent: 99.0501
LossFcn: 1.2070e+06
MSE: 1.2070e+06
FPE: 1.9693e+06
AIC: 1.7322e+03
AICc: 1.7482e+03
nAIC: 14.4837
BIC: 1.7947e+03
The values of MSE and FPE are concerning me. Do you have any comments on it?

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