ARX Time-Series Model

ARX models are a powerful tool for modeling and analyzing the behavior of dynamic systems. They are widely used in a variety of fields, including control engineering, signal processing, and electrical engineering. ARX models are often used in control engineering, where they are used to design controllers for systems such as robots or manufacturing processes. ARX models are based on the concept of linear time-invariant (LTI) systems, which are systems that can be described by linear differential equations. In an ARX model, the input and output of a system are related by a linear equation.

An ARX model is a combination of an autoregressive model (AR) and an exogenous input model (X). It is used to represent the dynamics of a system and is commonly used in control engineering to model and analyze dynamic systems. An autoregressive model is a type of statistical model that represents a time series as a linear combination of its past values and a stochastic process.

[jonathanuis]

John, a thousand thanks! I love what you are doing. Sharing knowledge in such wonderful manner

[amel]

Thank you for this video. I wanted to ask you a question: in the case where we have data containing a control input u, a disturbance d, and an output y, how can we perform the identification with Gekko?

[bernagoga]

Your videos are amazing! Thank you for sharing.

[ahmadkhoirunnajib]

million thanks for the video ! i want to ask a question : how to implement this ARX model in MPC for TCLab ?

[jinxiangsun]

Hello John, can you talk about the Output-only ARX model of MDOF system? Thank you very much.

[Jair_inacio_Neto_Teixeira]

Your content is amazing! Just one question, is it possible to use such model to implement a control like lqr ?

[nikolaskatsantonis]

I edited this comment :) Thx for your support, I really appreciate it :)