Using System Identification Toolbox More Effectively

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Eymen Kosar
Eymen Kosar 2022년 7월 22일
댓글: Eymen Kosar 2022년 8월 11일
Hello,
Let's say I have a system that its output is noisy enough to ident in system identification toolbox.
In this case is it okey to log data after using low pass filter? Because when we use low pass there will be a little phase shift and it can effect the transfer function of the system. This situation concerns me.
Are there any ways to use this noisy or filtered data in system identification toolbox get best estimated transfer function?
Any help will be appreciated.
Thanks.

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Star Strider
Star Strider 2022년 7월 22일
Because when we use low pass there will be a little phase shift and it can effect the transfer function of the system.’
You are correct to recognise that possibility, however it is straightforward to avoid using the filtfilt function to do the actual filtering of the signal with any filter you design. The lowpass function does this automatically. For best results with it (and its friends) use the ImpulseResponse','iir' name-value paiir.
For broadband (not band-limited) noise use the sgolayfilt funciton. I usually use a 3-degree polynomial and adjust the ‘framelen’ value to get the result I want.
.
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Eymen Kosar
Eymen Kosar 2022년 7월 25일
Processed and gained information you gave here is really valuable for me.
Well. Again, thanks in advance.
Eymen
Star Strider
Star Strider 2022년 7월 25일
As always, my pleasure!

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Rajiv Singh
Rajiv Singh 2022년 8월 9일
If you have input and output signals separately, you will need to filter both identically, so that in the resulting transfer function, the filter dynamics "cancel out". The net effect of prefiltering the data is to impose a frequency-weighting of the fitting errors. The frequencies where the filter frequency response has lower magnitude are given less importance (smaller weighhting).

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