Frequency limited model order reduction technique

Abstract

Derivation of a mathematical system is a critical parameter for analysis, design and simulationof a dynamic system. While deriving from physical systems large higher order complexmodels are obtained. These models are represented by partial differential equations, odinarydifferential equations. For simplification and ease in solution of these models, reduced ordermodels are required that approximates with the original system as closely as possible. Considerableamount of research has been done on different features of model order reduction.Existing techniques have the drawbacks of lacking properties like stability, passivity, largeapproximation with error and lack of apriori error bounds etc. This thesis includes frequencylimited Gramians based model order reduction techniques for standard continous and discretetime systems . The proposed techniques produce easily computable error bounds andcomparable approximation error. Numerical problems are also illustrated to exhibit the compatibilityand effictievness of the proposed techniques to the existing ones. Some of practicalapplications of MOR are. _ Fabrication industries _ Missiles analysis and launching _ Industrial real time applications