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Combining Krylov subspace methods and identification-based methods for model order reduction. (English) Zbl 1128.93314

Summary: Many different techniques to reduce the dimensions of a model have been proposed in the near past. Krylov subspace methods are relatively cheap, but generate non-optimal models. In this paper a combination of Krylov subspace methods and orthonormal vector fitting (OVF) is proposed. In that way a compact model for a large model can be generated. In the first step, a Krylov subspace method reduces the large model to a model of medium size, then a compact model is derived with OVF as a second step.

MSC:

93B11 System structure simplification
93C15 Control/observation systems governed by ordinary differential equations
93C05 Linear systems in control theory
34H05 Control problems involving ordinary differential equations
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