Title data
Grüne, Lars ; Nešić, Dragan:
Stabilization of sampled-data nonlinear systems via their approximate models : an optimization based approach.
In:
Proceedings of the 41st IEEE Conference on Decision and Control. Volume 1. -
Piscataway, NJ
: IEEE
,
2002
. - pp. 1934-1939
ISBN 0-7803-7516-5
DOI: https://doi.org/10.1109/CDC.2002.1184810
Related URLs
Abstract in another language
We present results on numerical regulator design for sampled-data nonlinear plants via their approximate discrete-time plant models. The regulator design is based on an approximate discrete-time plant model and is carried out either via an infinite horizon optimization problem or via a finite horizon with terminal cost optimization problem. In general, it is not true that a stabilizing controller for a discrete-time approximate model also stabilizes the exact sampled-data system, hence extra conditions are needed to ensure the desired behavior for the exact closed-loop system. In this paper we focus on the case when the sampling period T and the accuracy parameter h of the approximate discrete-time plant model are independent of each other and present appropriate conditions under which this approach yields practical and/or semiglobal stability of the exact discrete-time model.
Further data
Item Type: | Article in a book |
---|---|
Refereed: | Yes |
Institutions of the University: | Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne |
Result of work at the UBT: | No |
DDC Subjects: | 500 Science 500 Science > 510 Mathematics |
Date Deposited: | 01 Mar 2021 14:40 |
Last Modified: | 09 Jan 2024 12:52 |
URI: | https://eref.uni-bayreuth.de/id/eprint/63406 |