System identification with Julia: 2 Linear ARX models

We estimate a linear ARX model, also known as a discrete-time transfer function.
System identification with Julia is an introductory video series about system identification, the art and science of estimating dynamical models using input-output data and the Julia programming language.
Notebook file: juliahub.com/ui/Notebooks/fre...
00:00 Intro to linear models
00:53 Discrete and continuous time
04:00 The ARX model
06:45 Least-squares estimation
08:17 In practice
10:00 Constructing the regressor matrix
12:35 Computing the estimate
13:47 Using the built-in arx function
17:18 Consistency of the ARX least-squares estimate
20:23 Total least-squares estimation
22:31 Increasing the model order
23:12 Uncertainty quantification
25:33 Summary
Throughout the series, we will use the tools JuliaSim and ControlSystemIdenitification, detailed below. The functions getARXregressor and arx used in the video belong to ControlSystemIdenitification.jl
JuliaSim is an online platform providing enterprise solutions for modeling, simulation and control in Julia, building on ControlSystems.jl, see juliahub.com/products/juliasim/ with control-specific documentation available help.juliahub.com/juliasimcon...
For classical system identification in Julia, see baggepinnen.github.io/Control...
Please leave a comment if there is a particular system-identification related topic you would like to learn about!
Got questions or feedback? We'd love to hear from you! Fill out the contact form below, and our team will get back to you as soon as possible.
share.hsforms.com/1ax_TNnP2S5...

[@TheHerries]

Awesome presentation.

[@matthew32453245]

Great videos thanks! Im learning a lot from them

[@Zhijian-ng6gv]

Nice tutorial, however I cannot run the tutorial file in Juliahub ;(

[@Zhijian-ng6gv]

Also have no access into the simulation data