Second-order algorithm for optimal model order reduction

1990 ◽  
Vol 13 (5) ◽  
pp. 887-892 ◽  
Author(s):  
A. E. Bryson ◽  
A. Carrier
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
Second Order ◽  
Optimal Model ◽  
Model Order ◽  
Order Algorithm

scholarly journals Extracting second-order structures from single-input state-space models: Application to model order reduction

2011 ◽  
Vol 21 (3) ◽  
pp. 509-519 ◽  
Author(s):  
Jérôme Guillet ◽  
Benjamin Mourllion ◽  
Abderazik Birouche ◽  
Michel Basset
Keyword(s):  
State Space ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Second Order ◽  
Input State ◽  
Model Order ◽  
New Approach ◽  
Order Form ◽  
Form Model ◽  
Single Input

Extracting second-order structures from single-input state-space models: Application to model order reductionThis paper focuses on the model order reduction problem of second-order form models. The aim is to provide a reduction procedure which guarantees the preservation of the physical structural conditions of second-order form models. To solve this problem, a new approach has been developed to transform a second-order form model from a state-space realization which ensures the preservation of the structural conditions. This new approach is designed for controllable single-input state-space realizations with real matrices and has been applied to reduce a single-input second-order form model by balanced truncation and modal truncation.

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.

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