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A tangential method for the balanced truncation in model reduction

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Abstract

In this paper, we present a new approach for large-scale Lyapunov matrix equations, where we present two algorithms named: Adaptive Block Tangential Lanczos-type and Arnoldi-type algorithms (ABTL and ABTA). This approach is based on the projection of the initial problem onto tangential Krylov subspaces to produce a low-rank approximate solution of large Lyapunov equations. These approximations are used in model reduction of large-scale dynamical systems with multiple inputs and multiple outputs (MIMO). We give some algebraic properties and present some numerical experiences to show the effectiveness of the proposed algorithms.

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Authors and Affiliations

  1. Laboratoire de Mathématiques Pures et Appliquées, Université du Littoral, Côte d’Opale, Calais, France

    Y. Kaouane

  2. Laboratoire de Mathématiques Appliquées et Informatique, Université Cadi Ayyad, Marrakech, Morocco

    Y. Kaouane

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  1. Y. Kaouane
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Correspondence to Y. Kaouane.

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Kaouane, Y. A tangential method for the balanced truncation in model reduction. Numer Algor 83, 629–652 (2020). https://doi.org/10.1007/s11075-019-00696-9

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  • DOI: https://doi.org/10.1007/s11075-019-00696-9

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