Stabilizing receding horizon control of sampled-data nonlinear systems via their approximate discrete-time models

被引：0

作者：

Elaiw, AM ^{[1
]}

Gyurkovics, E ^{[1
]}

机构：

[1] Budapest Univ Technol & Econ, Sch Math, H-1521 Budapest, Hungary

来源：

CONTROL APPLICATIONS OF OPTIMISATION 2003 | 2003年

关键词：

predictive control; feedback stabilization; sampled-data systems; optimal control; numerical methods;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Results on stabilizing receding horizon control of sampled-data nonlinear systems via their approximate discrete-time models are presented. The proposed receding horizon control is based on the solution of Bolza-type optimal control problems for the parametrized family of approximate discrete-time models. The sampling period is considered to be fixed, and the discretization parameter is allowed to vary. Sufficient conditions are established which guarantee that the controller that renders the origin to be asymptotically stable for the approximate model also stabilizes the exact discrete-time model for sufficiently small discretization parameters. Copyright (C) 2003 IFAC.

引用

页码：39 / 44

页数：6

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