Approximation of large-scale dynamical systems for Bench-mark Collection


Santosh Kumar Suman,Awadhesh Kumar,



Benchmarks Example,Order reduction,Error estimation,Krylov,Balanced Truncation,Modal method,


In this contribution,We present a benchmark collection Inclusive of some needful real-world examples, which can be used to assessment and compare numerical methods for model reduction. In this paper the reduction method is explored for getting structure preserving reduced order model of a large-scale dynamical system, we have considered model order reduction of higher orderLTIsystems) with SISO and MIMO [XXXII] that aims at finding Error estimation using Approximation of both system. This enables a new evaluation of the error system Provided that the Observability Gramian of the original system has once been considered, an H∞and H2 error bound can be computed with negligible numerical attempt for any reduced model attributable to The reduced order model (ROM) of a large-scale dynamical system is necessary to effortlessness the analysis of the system using approximation Algorithms. The response evaluation is considered in terms ofresponse constraints and graphical assessments.the application of Approximation methodsis offered for arisingROMof the large-scaleLTI systems which includes benchmark problems. It is reported that the reduced order model using compare numerical methods is almost alike in performance to that of with original systems.all simulation resultshave been obtained via MATLAB based software (sssMOR toolbox).


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