The goal of Model Order Reduction (MOR) [1] is to catch a model of order lower than that of the real model. The reduced order model should be characterized by a low computational effort but able to estimate the input-output map of the original system in an important region of the input space. Actually, since only a subset of the input space are of interest, this matching should occur in this subset of the input space. This contribution emphasizes some consequences of the adoption of a reduced order model when structural control applications are pursued.
Model order reduction issues for structural control applications
CASCIATI, SARA;
2012-01-01
Abstract
The goal of Model Order Reduction (MOR) [1] is to catch a model of order lower than that of the real model. The reduced order model should be characterized by a low computational effort but able to estimate the input-output map of the original system in an important region of the input space. Actually, since only a subset of the input space are of interest, this matching should occur in this subset of the input space. This contribution emphasizes some consequences of the adoption of a reduced order model when structural control applications are pursued.File in questo prodotto:
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