Anonymous
×
Create a new article
Write your page title here:
We currently have 105 articles on MOR Wiki. Type your article name above or click on one of the titles below and start writing!



MOR Wiki

Difference between revisions of "Emgr"

Line 7: Line 7:
   
 
[http://gramian.de emgr] - '''Em'''pirical '''Gr'''amian Framework.
 
[http://gramian.de emgr] - '''Em'''pirical '''Gr'''amian Framework.
Empirical gramians can be computed for linear and nonlinear control systems for purposes of model order reduction or system identification.
+
Empirical gramians can be computed for linear and nonlinear control systems for purposes of model order reduction, uncertainty quantification or system identification.
 
Model reduction using empirical gramians can be applied to the state space, to the parameter space or to both through combined reduction.
 
Model reduction using empirical gramians can be applied to the state space, to the parameter space or to both through combined reduction.
 
The '''emgr''' framework is a compact open source toolbox for gramian-based model reduction and compatible with [http://www.gnu.org/software/octave/ OCTAVE] and [http://www.mathworks.de/products/matlab/ MATLAB].
 
The '''emgr''' framework is a compact open source toolbox for gramian-based model reduction and compatible with [http://www.gnu.org/software/octave/ OCTAVE] and [http://www.mathworks.de/products/matlab/ MATLAB].

Revision as of 11:54, 6 June 2013


Synopsis

emgr - Empirical Gramian Framework. Empirical gramians can be computed for linear and nonlinear control systems for purposes of model order reduction, uncertainty quantification or system identification. Model reduction using empirical gramians can be applied to the state space, to the parameter space or to both through combined reduction. The emgr framework is a compact open source toolbox for gramian-based model reduction and compatible with OCTAVE and MATLAB.

Features

Application matrix for the empirical gramian framework

emgr encompasses six types of gramians:

  • Empirical Controllability Gramian
  • Empirical Observability Gramian
  • Empirical Cross Gramian
  • Empirical Sensitivity Gramian
  • Empirical Identifiability Gramian
  • Empirical Joint Gramian

applicable to:

  • Linear + Nonlinear Systems
  • First + Second Order Systems
  • Parametric Systems

and with sample implementations for:

  • Balanced Truncation + Direct Trunction
  • Parameter Identification + Sensitivity Analysis
  • Parameter Reduction
  • Combined State and Parameter Reduction
  • (Bayesian) Inverse Problem Reduction

References

Links

Contact

Christian Himpe