Learning Goals:

You should understand what are important for a successful identification experiment. You should be able to use the system identification toolbox for identifying arx, oe, armax and bj models. You should know how to use the BIC(MDL) criterion for model order selection. You should know how to use residual analysis to guide you in model (in)validation. You should know that numerical issues might arise unless special care is taken, when identifying a system at a too high sample rate.

Material Ch 12.7-8 and Ch 17 in Ljung+Glad+Hansson. (or Ch 11.4-5 + Ch. 13 in old book)

Ch 14 (Nonlinear Models, Ch 12 in old book) is not part of the course, but is a recommended extra read for the interested student.

Lecture Slides: lecture11_Sysidpart3.pdf

lecture11_Sysidpart3_small.pdf

Lecture Video (from 2021): Lecture11_FULL.mp4

also available on Youtube

https://youtu.be/4pTA045Epuc

A couple of typos from 2021 have been corrected in the later slides.

PADLET

When watching the video, you can post questions/comments on this padlet

Code:

arxorder.m

arxtest.m

toofast.m

residuals.m

System Identification Toolbox:

Use "help ident" to investigate functionality in the system identification toolbox.
Start the GUI by the command "systemIdentification"
Study "doc X" where X is
- arxstruc, selstruc, struc
- arx, oe, armax, bj
- present, polydata, getpvec, bodeplot
- idpoly, iddata, idinput, idmodel/sim
- compare, resid