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A brief introduction to the toolbox is given in the paper <ref name="castagnotto17">A. Castagnotto; M. Cruz Varona; L. Jeschek; B. Lohman, "<span class="plainlinks">[http://dx.doi.org/10.1515/auto-2016-0137 sss & sssMOR: Analysis and Reduction of Large-Scale Dynamic Systems in MATLAB ]</span>", at-Automatisierungstechnik, 2017</ref>, as well as in following poster: | A brief introduction to the toolbox is given in the paper <ref name="castagnotto17">A. Castagnotto; M. Cruz Varona; L. Jeschek; B. Lohman, "<span class="plainlinks">[http://dx.doi.org/10.1515/auto-2016-0137 sss & sssMOR: Analysis and Reduction of Large-Scale Dynamic Systems in MATLAB ]</span>", at-Automatisierungstechnik, 2017</ref>, as well as in following poster: | ||
[[File:poster_Castagnotto_Komso.pdf]] | [[File:poster_Castagnotto_Komso.pdf|180px]] | ||
== References == | == References == | ||
Revision as of 09:06, 15 October 2020
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...
- ...classical reduction methods such as modal truncation, Rational Krylov Method, Balanced Truncation
- ...state-of-the-art reduction methods such as isrk, Iterative Rational Krylov Method, icop, cure, spark, cirka,...
- ...a Graphical User Interface (GUI)
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:
References
- ↑ 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
- Official website: http://www.rt.mw.tum.de/?sssMOR
- MATLAB File Exchange: http://de.mathworks.com/matlabcentral/fileexchange/59169-sssmor-toolbox
- Public Git Repository: https://github.com/MORLab/sssMOR
Contact
Alessandro Castagnotto, Maria Cruz Varona, morlab@rt.mw.tum.de