A subspace approach to balanced truncation for model reduction of nonlinear control systems

被引:337
作者
Lall, S [1 ]
Marsden, JE
Glavaski, S
机构
[1] Stanford Univ, Dept Astronaut & Aeronaut, Stanford, CA 94305 USA
[2] CALTECH, Pasadena, CA 91125 USA
[3] Honeywell Inc, Ctr Technol, Minneapolis, MN 55418 USA
关键词
balanced truncation; model reduction; Karhunen-Loeve expansion; total least-squares; Hankel norm;
D O I
10.1002/rnc.657
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we introduce a new method of model reduction for nonlinear control systems. Our approach is to construct an approximately balanced realization. The method requires only standard matrix computations, and we show that when it is applied to linear systems it results in the usual balanced truncation. For nonlinear systems, the method makes use of data from either simulation or experiment to identify the dynamics relevant to the input-output map of the system. An important feature of this approach is that the resulting reduced-order model is nonlinear, and has inputs and outputs suitable for control. We perform an example reduction for a nonlinear mechanical system. Copyright (C) 2002 John Wiley Sons, Ltd.
引用
收藏
页码:519 / 535
页数:17
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