sss & sssMOR: Analysis and Reduction of Large-Scale Dynamic Systems in MATLAB

We present two MATLAB toolboxes, provided as open-source code, that expand the capabilities of the Control System Toolbox to large-scale models. sss allows the definition and analysis of sparse state-space (sss) objects with functions (such as bode, step, norm,...) revisited to exploit the sparsity of the system matrices. sssMOR entails model reduction algorithms that capture the relevant dynamics of high order systems in models of significantly lower dimensions. The sssMOR_App provides a graphical user interface for easy interaction with the tools. With sss and sssMOR, it is possible to analyze dynamical systems with state-space dimensions higher than O(104), whichis typically the limit for built-in ss objects. In this contribution, we give a first introduction to the toolboxes and the main functionality. Numerical examples show the advantages of using the tools.     «

We present two MATLAB toolboxes, provided as open-source code, that expand the capabilities of the Control System Toolbox to large-scale models. sss allows the definition and analysis of sparse state-space (sss) objects with functions (such as bode, step, norm,...) revisited to exploit the sparsity of the system matrices. sssMOR entails model reduction algorithms that capture the relevant dynamics of high order systems in models of significantly lower dimensions. The sssMOR_App provides...     »