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Krylov subspace techniques for reduced-order modeling of nonlinear dynamical systems
Applied Math| Speaker: | Zhaoujun Bai, UC Davis |
| Location: | 693 Kerr |
| Start time: | Fri, Nov 22 2002, 4:10PM |
Description
Means of applying Krylov subspace techniques for adaptively
extracting accurate reduced-order models of large-scale nonlinear
dynamical systems is a relatively open problem. There has been
much current interest in developing such techniques. We focus on
a bi-linearization method, which extends Krylov subspace techniques
for linear systems. In this approach, a nonlinear system is first
approximated by a bilinear system through Carleman bilinearization.
Then a reduced-order bilinear system is constructed in such a way
that it matches certain number of multimoments corresponding to
the first few kernels of the Volterra-Wiener representation of
the bilinear system. It is shown that the two-sided Krylov subspace
technique matches significant more number of multimoments than
the corresponding one-side technique.