Plotting with experimental data

2017 2 3
2 个回答
回答已采纳
更新时间：2017 2 6
10 次查看（30 天）

0 个投票

Hi, I have 3 columns, time(in s), output(in V), input(in V) respectively, where by using iddata, is it correct for me to determine the ['Frequency',time] in seconds ? or should i do it in frequency (Hz)
tf = iddata(data(:,2),data(:,3),'Frequency',time)
sys = tfest(tf,2)
By using the system identification app, after importing the output and input values and estimation using state space model it turns that that the order is 2. Is it right for to to key in [tfest(tf,2)] in this case ? Or doing it wrongly?
Any help is appreciated !

请先登录，再回答此问题。

 采纳的回答

Star Strider
Star Strider 2017-2-3

2 个投票

I would use this syntax (from the documentation):
  • data = iddata(y,u,Ts) creates an iddata object containing a time-domain output signal y and input signal u, respectively. Ts specifies the sample time of the experimental data.
Specifically with respect to your data, I would do something like this:
time = data(:,1);
Ts = mean(diff(time));
time_data = iddata(data(:,2),data(:,3),Ts);
freq_data = fft(time_data);
freq_units = freq_data.units;
Fr = freq_data.frequency;
sys = tfest(freq_data,2)
NOTE — I do not have your data so this is UNTESTED CODE. I cannot be certain it will work without modification.

4 个评论
显示 2更早的评论 隐藏 2更早的评论

Niam
Niam 2017-2-5
Hi Star Strider !
My apologies for the late reply, i tried out your code and it plotted out a graph (assuming that it's correct), it gave the comment
if true
Status:
Estimated using TFEST on frequency domain data "freq_data".
Fit to estimation data: 100% (simulation focus)
FPE: 1.778e-10, MSE: 1.773e-10
end
May i ask why the estimation data actually does ? (since it waver between the %)
Your help is greatly appreciated ! Thank for you your patient , hope to hear from you
Star Strider
Star Strider 2017-2-5
Waking up here ...
My pleasure!
The tfest told you that it was able to fit your data, and that it did so quite accurately. I cannot find anything in the R2016b documentation that explains the output you got, so there could be version differences. The mean squared error (MSE) is on the order of machine precision, so the fit to your data are excellent!
Niam
Niam 2017-2-6
Thanks again for the clear explanation ! It have benefited me in many ways for understanding ! (:

请先登录，再进行评论。

更多回答（1 个）

Walter Roberson
Walter Roberson 2017-2-3

0 个投票

The 'Frequency' parameter should have frequencies. If you have sample times then pass them as the third parameter with no 'Frequency' option; https://www.mathworks.com/help/ident/ref/iddata.html

1 个评论
显示 -1更早的评论 隐藏 -1更早的评论

Niam
Niam 2017-2-3
I understand for this part now , do you have any idea for the System identification app ?

请先登录，再进行评论。

类别

在 帮助中心 和 File Exchange 中查找有关 Transfer Function Models 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by