Shiftet values of omega in bode plot as result from generating idfrd() and tfest()

Question

Rai Way 2024-7-17

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2138242-shiftet-values-of-omega-in-bode-plot-as-result-from-generating-idfrd-and-tfest

评论： Rai Way 2024-7-18

采纳的回答： Paul

data.CSV

在 MATLAB Online 中打开

Hello,

i have a problem at the calculation / estimation of a transfer function when using frequency-domain data.

My task is to get the continious transfer function for further simulation from measured magnitude and phase response by an impedance analyser.

The quality of the estimated curve is ok, but the problem is that the curve is shifted in omega and i cannot observe the problem.

The frequency limits of the measured data are 20 Hz to 5000 Hz with the units (freq. [Hz], magn [-], phase [°]).

Figure 1 and Figrue 2 shows the magnitude and phase of the measured data.

In Figure 3 shows the bode plot with idfrd() / frd() and the estimated TF.

Here the values are shiftet.

What ist the problem in this case?

format short g

clear

matt = readmatrix('data.CSV');

fre = matt(1:300,1);

frerad = fre.*(pi/180);

abso = matt(1:300,2);

absdb = 20*log10(abso);

phdeg = matt(1:300,3);

phrad = phdeg.*(pi/180);

% options = bodeoptions;

% options.FreqUnits = 'Hz';

figure(1)

semilogx(fre,absdb)

legend()

ylabel('magn. [dB]')

xlabel('freq. [Hz]')

grid()

figure(2)

semilogx(fre,phdeg)

ylabel('magn. [dB]')

xlabel('freq. [Hz]')

legend()

grid()

complexVector = abso.* exp(1j*phrad);

vect_mess = idfrd(complexVector,frerad,0);

% vect_mess = frd(complexVector,frerad);

tf_estimated = tfest(vect_mess,3)

tf_estimated = 2.637 s^2 + 77.66 s + 337.4 ------------------------------- s^3 + 175.3 s^2 + 1839 s + 3528 Continuous-time identified transfer function. Parameterization: Number of poles: 3 Number of zeros: 2 Number of free coefficients: 6 Use "tfdata", "getpvec", "getcov" for parameters and their uncertainties. Status: Estimated using TFEST on frequency response data "vect_mess". Fit to estimation data: 99.13% FPE: 8.091e-08, MSE: 7.774e-08

figure(3)

bode(vect_mess,tf_estimated )

legend()

grid()