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Reduced Order Modeling

Reduce computational complexity of 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 surrogate reduced order model can simplify analysis and control design.


Reduced Order Modeling Basics

Data-Driven Methods

Linearization-Based Methods