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System Identification

The field of system identification uses statistical methods to build mathematical models of dynamical systems from measured data. System identification also includes the optimal design of experiments for efficiently generating informative data for fitting such models as well as model reduction. A common approach is to start from measurements of the behavior of the system and the external influences (inputs to the system) and try to determine a mathematical relation between them without going into many details of what is actually happening inside the system; this approach is called system identification.

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System Identification: Koopman with Control
2

System Identification: Koopman with Control

Steve Brunton
10 min
Intermediate
Video
Theory

This lecture provides an overview of the use of modern Koopman spectral theory for nonlinear control. In particular, we develop control in a coordinate system defined by eigenfunctions of...

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What are Nonlinear ARX Models?
1

What are Nonlinear ARX Models?

Mathworks
Intermediate
Article / Blog
Theory

This Mathworks page provides an overview of Nonlinear ARX Models.Nonlinear ARX models extend the linear ARX models to the nonlinear case. The structure of these models enables you to model...

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System Identification: Regression Models
1

System Identification: Regression Models

Steve Brunton
5 min
Intermediate
Video
Theory

This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and...

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