Lecture 11. Identification of Linear Dynamical Systems - part 3
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 2022: lecture11_Sysidpart3.pdf
Download lecture11_Sysidpart3.pdf
Lecture Video (from 2021): Lecture11_FULL.mp4
Download Lecture11_FULL.mp4
also available on Youtube
A couple of typos from 2021 have been corrected in the Lecture Slides 2022
Code:
arxorder.m Download arxorder.m
residuals.m Download 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