scholarly journals Transient simulation of very large scale models using Krylov subspace-based model order reduction

2014 ◽  
Author(s):  
O. Macchion ◽  
A. Suleng ◽  
M. Mork ◽  
J. Sindler
Keyword(s):  
Model Order Reduction ◽  
Large Scale ◽  
Krylov Subspace ◽  
Order Reduction ◽  
Transient Simulation ◽  
Model Order ◽  
Scale Models

scholarly journals Basic principles and aims of model order reduction in compliant mechanisms

2011 ◽  
Vol 2 (2) ◽  
pp. 197-204 ◽  
Author(s):  
M. Rösner ◽  
R. Lammering
Keyword(s):  
Model Order Reduction ◽  
Large Scale ◽  
Krylov Subspace ◽  
Compliant Mechanisms ◽  
Linear Time ◽  
Order Reduction ◽  
Research Direction ◽  
Future Research ◽  
Model Order ◽  
Advantages And Disadvantages

Abstract. Model order reduction appears to be beneficial for the synthesis and simulation of compliant mechanisms due to computational costs. Model order reduction is an established method in many technical fields for the approximation of large-scale linear time-invariant dynamical systems described by ordinary differential equations. Based on system theory, underlying representations of the dynamical system are introduced from which the general reduced order model is derived by projection. During the last years, numerous new procedures were published and investigated appropriate to simulation, optimization and control. Singular value decomposition, condensation-based and Krylov subspace methods representing three order reduction methods are reviewed and their advantages and disadvantages are outlined in this paper. The convenience of applying model order reduction in compliant mechanisms is quoted. Moreover, the requested attributes for order reduction as a future research direction meeting the characteristics of compliant mechanisms are commented.

A Hybrid Approach for Model Order Reduction and Controller Design of Large-Scale Power Systems

2021 ◽  
pp. 211-226
Author(s):  
Rishabh Singhal ◽  
Yashonidhi Srivastava ◽  
Shini Agarwal ◽  
Abhimanyu Kumar ◽  
Souvik Ganguli
Keyword(s):  
Power Systems ◽  
Model Order Reduction ◽  
Large Scale ◽  
Controller Design ◽  
Hybrid Approach ◽  
Order Reduction ◽  
Model Order
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