Reduced Order Modeling: Applications and Techniques for Creating ROMs
From the series: Reduced Order Modeling
Reduced order modeling (ROM) is a technique for simplifying a high-fidelity mathematical model by reducing its computational complexity while preserving the dominant behavior of the complex model.
One common application of reduced order modeling enables simulation of third-party FEA/FEM/CFD models in Simulink® including hardware-in-the-loop testing. Other ROM applications include virtual sensor modeling, control design, and digital twins. This overview also highlights different techniques for creating reduced order models with MATLAB® and Simulink such as data-driven modeling (including static and dynamic models), model-based ROMs, linearization-based methods, and physics-based reduction.
Published: 4 Dec 2023
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
Asia Pacific
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)