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On model reduction by least squares moment matching

2021/09/24 by Alberto Padoan, Padoan, Alberto · 1 citation
Computer Science · Engineering · Mathematics · #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering #math.OC

paper · pdf · doi:10.48550/arxiv.2109.11869

Submitted to the 60th Conference on Decision and Control (CDC)

arxiv created 2021/09/24 · arxiv updated 2021/09/27

Abstract

The paper addresses the model reduction problem by least squares moment matching for continuous-time, linear, time-invariant systems. The basic idea behind least squares moment matching is to approximate a transfer function by ensuring that the interpolation conditions imposed by moment matching are satisfied in a least squares sense. This idea is revisited using invariance equations and steady-state responses to provide a new time-domain characterization of least squares moment matching. The characterization, in turn, is then used to obtain a parameterized family of models achieving least squares moment matching. The theory is illustrated by a worked-out numerical example.

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