Geodesic
Routh-type $L_2$ model reduction revisited
Kybernetika, Tome 54 (2018) no. 3, pp. 557-575 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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A computationally simple method for generating reduced-order models that minimise the $L_2$ norm of the approximation error while preserving a number of second-order information indices as well as the steady-state value of the step response, is presented. The method exploits the energy-conservation property peculiar to the Routh reduction method and the interpolation property of the $L_2$-optimal approximation. Two examples taken from the relevant literature show that the suggested techniques may lead to approximations that are not worse than those afforded by popular more cumbersome techniques.
A computationally simple method for generating reduced-order models that minimise the $L_2$ norm of the approximation error while preserving a number of second-order information indices as well as the steady-state value of the step response, is presented. The method exploits the energy-conservation property peculiar to the Routh reduction method and the interpolation property of the $L_2$-optimal approximation. Two examples taken from the relevant literature show that the suggested techniques may lead to approximations that are not worse than those afforded by popular more cumbersome techniques.
DOI : 10.14736/kyb-2018-3-0557
Classification : 93A15, 93B11, 93C05
Keywords: model reduction; $L_2$ norm; Routh approximation; steady–state response 
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     title = {Routh-type $L_2$ model reduction revisited},
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     pages = {557--575},
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Krajewski, Wiesław; Viaro, Umberto. Routh-type $L_2$ model reduction revisited. Kybernetika, Tome 54 (2018) no. 3, pp. 557-575. doi: 10.14736/kyb-2018-3-0557

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