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.
Topic
System Identification
This topic includes the following resources and journeys:
Type
Experience
Scope
Nonlinear Model Identification
Mathwork overview page describing nonlinear model identification. Use nonlinear model identification when a linear model does not completely capture your system dynamics. You can identify...
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This is the Mathworks documentation page for the idLinear mapping object.
See MoreWhat are Nonlinear ARX Models?
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...
See MoreLinear Model Identification Basics
This is a curated list of Mathworks products, examples, and topics that cover identifying linear models, selecting suitable model structures, constructing and modifying model object...
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This Mathworks page provides an overview of polynomial models.
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