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Revision as of 11:06, 15 October 2020 by Himpe (talk | contribs) (fix embedded poster)


Logo sssMOR long.png

sssMOR, the sparse state space and Model Order Reduction toolbox, is an open-source MATLAB toolbox for the analysis and reduction of large-scale linear models, developed at the Chair of Automatic Control at TU Munich. It can be seen as a natural extension of MATLAB's Control System Toolbox allowing to extend the analysis and control design to systems represented by large-scale models.


Features

sssMOR includes the sss toolbox which can be used to...

  • ...define state-space models in MATLAB while preserving the sparsity of the system matrices. This allows a definition of models up to a state-space dimension of 108.
  • ...exploit sparsity in the analysis of large-scale models with functions such as bode, impulse, step, lsim, norm, ...
  • ...manipulate state-space models through additions, subtractions, multiplications, connections, truncations, ...

In addition, sssMOR includes...

sssMOR is compatible to MESS for the low-rank approximative solution of Lyapunov equations, e.g. within the functions norm and tbr.

The toolbox comes with a full MATLAB documentation as well as demos and tutorials. By signing up to our mailing list you can stay up-to-date with new releases.

A brief introduction to the toolbox is given in the paper [1], as well as in following poster:

Poster Castagnotto Komso.pdf

References

  1. A. Castagnotto; M. Cruz Varona; L. Jeschek; B. Lohman, "sss & sssMOR: Analysis and Reduction of Large-Scale Dynamic Systems in MATLAB ", at-Automatisierungstechnik, 2017

Links

Contact

Alessandro Castagnotto, Maria Cruz Varona, morlab@rt.mw.tum.de