Data-Driven Control: ERA/OKID Example in Matlab

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In this lecture, we explore the observer Kalman filter identification (OKID) and eigensystem realization algorithm (ERA) in Matlab on an example.

This video was produced at the University of Washington

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Thank you for the video on using era and okid

BalajiSankar

So much satisfaction to reach this point

luiggitello

Dear Steve, in the ERA function you used Ur to calculate Br. Also, you used Vr to calculate Cr. These should be replaced

hrt

Thank you for the great video. Question for you, Dr. Steve? Would you please explain how you get the impulse generated for a MIMO system seems like you are doing a DOE of Nu by Nu and combine them instead of doing that in one time?

leoliu

I am still waiting for someone to email me my dataset with a randomly forced u.

tayyipensarozkaya

a fascinating result is that your code despite all these replacing and the power of sigma which should be 0.5 but it is -0.5, works properly and when I change it to the correct version it does not!
I also check with your book, the same thing you mentioned in the video is also in the book.
So, can we conclude that what you explained in the book and in the video are incorrect and what you wrote as the code is correct?

hrt

What if I only have the output data? How can I identify the system without the input data?

mateogonzalezhurtado

Is the matlab code available to the public? where can I get it?

benjomino

Could you please update the code on the course website ?

markghali

How does one decide the order of the resulting system ? through SVD ?

markghali

Download MATLAB testsys have u - 2x200 and Y - 2x200. So it has 200 states? Am I right?

indramal

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