Model reduction of linear hybrid systems
Model reduction of linear hybrid systems
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DOI：
10.1109/cdc42340.2020.9303918
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
I. V. Gosea;M. Petreczky;J. Leth;R. Wisniewski;A. Antoulas
中科院分区：
文献类型：
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作者：
I. V. Gosea;M. Petreczky;J. Leth;R. Wisniewski;A. Antoulas
本文提出了一种用于线性混合系统的模型还原算法，即具有外部诱导离散事件的混合系统，具有线性连续子系统和线性重置图。模型还原算法基于平衡截断。此外，本文还证明了针对原始模型的投入输出行为与降低阶模型之间的差异结合的分析误差。这种误差的结合是根据用于模型还原的Gramians的奇异值来提出的。
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.