Dynamic data-driven model reduction: adapting reduced models from incomplete data
This work presents a data-driven online adaptive model reduction approach for systems that undergo dynamic changes. Classical model reduction constructs a reduced model of a large-scale system in an offline phase and then keeps the reduced model unchanged during the evaluations in an online phase; h...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing
2016
|
| Online Access: | http://hdl.handle.net/1721.1/103331 https://orcid.org/0000-0002-5045-046X https://orcid.org/0000-0003-2156-9338 |