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Krylov subspace techniques for reduced-order modeling of nonlinear dynamical systems
Applied MathSpeaker: | Zhaoujun Bai, UC Davis |
Location: | 693 Kerr |
Start time: | Fri, Nov 22 2002, 4:10PM |
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.