Computing the distance between a nonlinear model and its linear approximation:: an L2 approach

被引：11

作者：

Kihas, D ^{[1
]}

Marquez, HJ ^{[1
]}

机构：

[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2V4, Canada

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2004年 / 28卷 / 12期

关键词：

nonlinear model; linearization; Hamilton-Jacobi inequality; input-output stability; input-to-state stability;

D O I：

10.1016/j.compchemeng.2004.08.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper we consider the following problem: viewing both a nonlinear system model and its linearization as mappings from input-to-state, we define the error between the state of the original nonlinear system and that of the linearization and find the region of the state space where this error is norm-bounded, in the integral-square (or L-2-norm) sense. Using the Hamilton-Jacobi inequality we define the distance between these two systems as the upper bound of this error. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：2659 / 2666

页数：8

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