A framework for stabilization of nonlinear sampled-data systems based on their approximate discrete-time models

被引：356
|
作者：
Nesic, D [1 ]
Teel, AR
机构：
[1] Univ Melbourne, Dept Elect & Elect Engn, Parkville, Vic 3052, Australia
[2] Univ Calif Santa Barbara, Dept Elect & Comp Engn, Santa Barbara, CA 93106 USA
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2004年 / 49卷 / 07期
基金：
美国国家科学基金会; 澳大利亚研究理事会;
关键词：
discrete-time; Lyapunov method; nonlinear; sampled-data; stabilization;
D O I：
10.1109/TAC.2004.831175
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A unified framework for design of stabilizing controllers for sampled-data differential inclusions via their approximate discrete-time models is presented. Both fixed and fast sampling are considered. In each case, sufficient conditions are presented which guarantee that the controller that stabilizes a family of approximate discrete-time plant models also stabilizes the exact discrete-time plant model for sufficiently small integration and/or sampling periods. Previous results in the literature are extended to cover: 1) continuous-time plants modeled as differential inclusions; 2) general approximate discrete-time plant models; 3) dynamical discontinuous controllers modeled as difference inclusions; and 4) stability with respect to closed arbitrary (hot necessarily compact) sets.
引用
收藏
页码：1103 / 1122
页数：20
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