Learn to estimate linear ARX models and discrete-time transfer functions in this 27-minute instructional video from the System Identification with Julia series. Master fundamental concepts including discrete and continuous time systems, least-squares estimation techniques, and practical implementation using Julia programming tools. Follow along with hands-on demonstrations of constructing regressor matrices, computing estimates, and utilizing built-in ARX functions from ControlSystemIdentification.jl. Explore advanced topics like consistency of ARX least-squares estimates, total least-squares estimation, model order selection, and uncertainty quantification. Access the complete notebook file through JuliaHub and leverage enterprise-level tools like JuliaSim for modeling, simulation and control applications. Perfect for those interested in system identification, control theory, and scientific computing with Julia.
Linear ARX Models in System Identification with Julia - Part 2
Overview
Syllabus
Intro to linear models
Discrete and continuous time
The ARX model
Least-squares estimation
In practice
Constructing the regressor matrix
Computing the estimate
Using the built-in arx function
Consistency of the ARX least-squares estimate
Total least-squares estimation
Increasing the model order
Uncertainty quantification
Summary
Taught by
JuliaHub
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