%0 Book Section %1 citeulike:13751038 %A Benner, Peter %A Faßbender, Heike %B Encyclopedia of Systems and Control %C London %D 2014 %E Baillieul, John %E Samad, Tariq %I Springer %K lumped-parameter-modelling 00a71-theory-of-mathematical-modeling 93a30-systems-theory-mathematical-modeling 93b11-system-structure-simplification %R 10.1007/978-1-4471-5102-9\_142-1 %T Model Order Reduction: Techniques and Tools %U http://dx.doi.org/10.1007/978-1-4471-5102-9\_142-1 %X Model order reduction (MOR) is here understood as a computational technique to reduce the order of a dynamical system described by a set of ordinary or differential-algebraic equations (ODEs or DAEs) to facilitate or enable its simulation, the design of a controller, or optimization and design of the physical sys- tem modeled. It focuses on representing the map from inputs into the system to its outputs, while its dynamics are treated as a blackbox so that the large-scale set of describing ODEs/DAEs can be replaced by a much smaller set of ODEs/DAEs without sacrificing the accuracy of the input-to-output behavior.

@incollection{citeulike:13751038, abstract = {{Model order reduction (MOR) is here understood as a computational technique to reduce the order of a dynamical system described by a set of ordinary or differential-algebraic equations (ODEs or DAEs) to facilitate or enable its simulation, the design of a controller, or optimization and design of the physical sys- tem modeled. It focuses on representing the map from inputs into the system to its outputs, while its dynamics are treated as a blackbox so that the large-scale set of describing ODEs/DAEs can be replaced by a much smaller set of ODEs/DAEs without sacrificing the accuracy of the input-to-output behavior.}}, added-at = {2017-06-29T07:13:07.000+0200}, address = {London}, author = {Benner, Peter and Fa{\ss}bender, Heike}, biburl = {https://www.bibsonomy.org/bibtex/2358e731143af0df1e6269c16fe05ff0d/gdmcbain}, booktitle = {Encyclopedia of Systems and Control}, citeulike-article-id = {13751038}, citeulike-attachment-1 = {benner_14_model.pdf; /pdf/user/gdmcbain/article/13751038/1032949/benner_14_model.pdf; c6ed1ce9ca7f492903f493bb7c1249e105a47b4b}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-1-4471-5102-9\_142-1}, citeulike-linkout-1 = {http://link.springer.com/referenceworkentry/10.1007/978-1-4471-5102-9\_142-1}, doi = {10.1007/978-1-4471-5102-9\_142-1}, editor = {Baillieul, John and Samad, Tariq}, file = {benner_14_model.pdf}, interhash = {fd9869dcb24d2fe3ea9f35a651286c99}, intrahash = {358e731143af0df1e6269c16fe05ff0d}, keywords = {lumped-parameter-modelling 00a71-theory-of-mathematical-modeling 93a30-systems-theory-mathematical-modeling 93b11-system-structure-simplification}, posted-at = {2015-09-04 06:01:15}, priority = {2}, publisher = {Springer}, timestamp = {2020-03-01T23:47:29.000+0100}, title = {{Model Order Reduction: Techniques and Tools}}, url = {http://dx.doi.org/10.1007/978-1-4471-5102-9\_142-1}, year = 2014 }