sss & sssMOR: Analysis and reduction of large-scale dynamic systems in MATLAB

被引：33

作者：

Castagnotto, Alessandro ^{[1
]}

Varona, Maria Cruz ^{[1
]}

Jeschek, Lisa ^{[1
]}

Lohmann, Boris ^{[1
]}

机构：

[1] Tech Univ Munich, Dept Mech Engn, Chair Automat Control, Boltzmannstr 15, D-85748 Garching, Germany

来源：

AT-AUTOMATISIERUNGSTECHNIK | 2017年 / 65卷 / 02期

关键词：

Large-scale systems; control systems; model reduction; MATLAB; control system toolbox; NUMERICAL-SOLUTION; ORDER REDUCTION; MODEL-REDUCTION; LYAPUNOV;

D O I：

10.1515/auto-2016-0137

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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(10 (4)), which is 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.

引用

页码：134 / 150

页数：17

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