Model Reduction Using Proper Orthogonal Decomposition and Predictive Control of Distributed Reactor System

Model Reduction via Proper Orthogonal Decomposition

Model Reduction by Proper Orthogonal Decomposition (POD)

Mathematical models for human tissue and blood flow both represent time dependent nonlinear partial differential equations in three space dimensions. Their numerical solution based on appropriate space/time discretizations requires computational times that even when using state-of-the-art algorithmic solvers are far from being acceptable for real time OR scenarios. A way to overcome this diffic...

Model Reduction for fluids, Using Balanced Proper Orthogonal Decomposition

Many of the tools of dynamical systems and control theory have gone largely unused for fluids, because the governing equations are so dynamically complex, both high-dimensional and nonlinear. Model reduction involves finding low-dimensional models that approximate the full high-dimensional dynamics. This paper compares three different methods of model reduction: proper orthogonal decomposition ...

Model Reduction of Population Balance Systems by Proper Orthogonal Decomposition

Zusammenfassung Der Beitrag beschreibt den Einsatz der Proper Orthogonal Decomposition (POD) für die Modellreduktion von Partikelprozessen in fluider Strömung. Diese Prozessklasse ist von großer Bedeutung für die chemische und pharmazeutische Industrie. Physikalische Modelle solcher Prozesse sind häufig sehr komplex und für Regelungsaufgaben wenig geeignet. POD bietet hier eine attraktive Mögli...

Proper Orthogonal Decomposition Model Order Reduction of nonlinear IC models

Future simulation for nanoelectronics requires that circuit equations can be coupled to electromagnetics, to semiconductor equations, and to heat transfer. The consequence is that one has to deal with large systems. Model Order Reduction (MOR) is a means to speed up simulation of large systems. Existing MOR techniques mostly apply to linear problems and even then they have to be generalized to ...