Error-bounds for balanced model-reduction of linear time-varying systems

被引:60
作者
Lall, S [1 ]
Beck, C
机构
[1] Stanford Univ, Dept Aeronaut & Astronaut, Stanford, CA 94305 USA
[2] Univ Illinois, Dept Gen Engn, Urbana, IL 61801 USA
关键词
balanced truncation; model reduction; time-varying systems;
D O I
10.1109/TAC.2003.812779
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Error-bounds are developed for balanced truncation of linear time-varying systems, leading to an extension of the "twice the sum of the tail" formulas, well known in the time-invariant case. The approach relies on an operator-theoretic framework for analysis of linear time-varying systems. This provides a multivariable notion of frequency for such systems, which are thus characterized by rational functions of many complex variables, allowing the problem to be formulated in the linear-fractional framework. Using a time-varying version of standard necessary conditions for reduced-order modeling, based on convex operator inequalities, we show that these error-bounds for balanced truncation are related to the closest possible reduced-order modeling error in a sense which parallels the time-invariant case.
引用
收藏
页码:946 / 956
页数:11
相关论文
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