Model reduction of linear hybrid systems

2020/03/17 by Ion Victor Gosea, Mihaly Petreczky, Gosea, Ion Victor +7
Mathematics · #Dynamical Systems (math.DS) #FOS: Mathematics #math.DS

paper · pdf · doi:10.48550/arxiv.2003.07954

arxiv created 2020/03/17 · arxiv updated 2020/03/19

Abstract

The paper proposes a model reduction algorithm for linear hybrid systems, i.e., hybrid systems with externally induced discrete events, with linear continuous subsystems, and linear reset maps. The model reduction algorithm is based on balanced truncation. Moreover, the paper also proves an analytical error bound for the difference between the input-output behaviors of the original and the reduced order model. This error bound is formulated in terms of singular values of the Gramians used for model reduction.

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• Quality of Approximate Balanced Truncation
• Model Reduction for Systems with Inhomogeneous Initial Conditions
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