Balanced Model Reduction via the Proper Orthogonal Decomposition
نویسنده
چکیده
A new method for performing a balanced reduction of a high-order linear system is presented. The technique combines the proper orthogonal decomposition and concepts from balanced realization theory. The method of snapshots is used to obtain low-rank, reduced-rangeapproximationsto the system controllabilityand observability grammiansin either the timeor frequency domain.The approximationsare thenused to obtaina balancedreducedorder model. The method is particularly effective when a small number of outputs is of interest. It is demonstrated for a linearized high-order system that models unsteady motion of a two-dimensional airfoil. Computation of the exact grammians would be impractical for such a large system. For this problem, very accurate reducedorder models are obtained that capture the required dynamics with just three states. The new models exhibit far superiorperformance than those derived using a conventionalproper orthogonaldecomposition.Although further development is necessary, the concept also extends to nonlinear systems.
منابع مشابه
Aiaa 2001-2611 Balanced Model Reduction via the Proper Orthogonal Decomposition
A new method for performing a balanced reduction of a high-order linear system is presented. The technique combines the proper orthogonal decomposition and concepts from balanced realization theory. The method of snapshots is used to obtain low-rank, reduced-range approximations to the system controllability and observability grammians in either the time or frequency domain. The approximations ...
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