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Reduced Order Modeling

Reduce computational complexity of Simulink® models by creating accurate surrogates

Reduced order modeling is a technique for reducing the computational complexity or storage requirements of a model while preserving the expected fidelity within a satisfactory error. Working with a reduced order model can simplify analysis and control design.

You can create reduced order models (ROMs) of subsystems modeled in Simulink, including full-order, high-fidelity third-party simulation models. You can use these models for system-level desktop simulation, hardware-in-the-loop (HIL) testing, control design, and virtual sensor modeling.

To create a ROM of a Simulink model or subsystem in the model using a UI workflow, install the Reduced Order Modeling Support Package. For more information, see Reduced Order Modeling Support Package on File Exchange.

Topics

Reduced Order Modeling Basics

  • Reduced Order Modeling (System Identification Toolbox)
    Reduce computational complexity of models by creating accurate surrogates.

Data-Driven Methods

Linearization-Based Methods

Physics-Based Methods

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