scholarly journals Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs

2019 ◽  
Vol 41 (4) ◽  
pp. A2270-A2295
Author(s):  
Roland Pulch ◽  
Akil Narayan
Keyword(s):  
Dynamical Systems ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Balanced Truncation ◽  
Model Order ◽  
Linear Dynamical Systems

Using model order reduction to accelerate optimization of multi-stage linear dynamical systems

2014 ◽  
pp. 453-458
Author(s):  
Yao Yue ◽  
Suzhou Li ◽  
Lihong Feng ◽  
Andreas Seidel-Morgenstern ◽  
Peter Benner
Keyword(s):  
Dynamical Systems ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Model Order ◽  
Linear Dynamical Systems ◽  
Multi Stage

Second Order Model Reduction Based on Diagonal Blocks of Gramians

2011 ◽  
Vol 317-319 ◽  
pp. 2359-2366
Author(s):  
Cong Teng
Keyword(s):  
Model Order Reduction ◽  
Large Scale ◽  
Order Reduction ◽  
Second Order ◽  
Balanced Truncation ◽  
Order Model ◽  
Model Order ◽  
Linear Dynamical Systems ◽  
Large Scale Systems ◽  
New Algorithms

In this paper, some new algorithms based on diagonal blocks of reachability and observability Gramians are presented for structure preserving model order reduction on second order linear dynamical systems. They are more suitable for large scale systems compared to existing Gramian based algorithms, namely second order balanced truncation methods. In experiments, they have similar performance as the existing techniques.

scholarly journals Second-Order Model Reduction Based on Gramians

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Cong Teng
Keyword(s):  
Model Order Reduction ◽  
Large Scale ◽  
Order Reduction ◽  
Second Order ◽  
Balanced Truncation ◽  
Order Model ◽  
Model Order ◽  
Linear Dynamical Systems ◽  
Large Scale Systems ◽  
Order Linear

Some new and simple Gramian-based model order reduction algorithms are presented on second-order linear dynamical systems, namely, SVD methods. Compared to existing Gramian-based algorithms, that is, balanced truncation methods, they are competitive and more favorable for large-scale systems. Numerical examples show the validity of the algorithms. Error bounds on error systems are discussed. Some observations are given on structures of Gramians of second order linear systems.

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