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Efficient Order Reduction of Parametric and Nonlinear Models by Superposition of Locally Reduced Models
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lohmann, Boris Eid, Rudy |
| Copyright Year | 2009 |
| Abstract | In model reduction of nonlinear dynamical systems and of par ametric systems, a known technique is to first represent the model as an interpolating supe rposition of some (linear or nonparametric) local models and to then apply a common order red ucing projection to the overall model. This common projection must comprise relevant subsp ace information of all local models, and leads therefore to a relatively high reduced order. In this note, we present a remedy to this problem by separating the projection matrix into diffe rent subspaces applied individually to all the local models, leading to a significantly lower orde r, thereby making the reduction more efficient. In addition, by suitable state transformati ons, the state vector of the reduced interpolating model is given a clear physical interpretati on. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.rt.mw.tum.de/fileadmin/w00bhf/www/publikationen/2009_Lohmann_Hirschberg.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
