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Optimization-Based Stabilization of Sampled-Data Nonlinear Systems via Their Approximate Discrete-Time Models

Title data

Grüne, Lars ; Nešić, Dragan:
Optimization-Based Stabilization of Sampled-Data Nonlinear Systems via Their Approximate Discrete-Time Models.
In: SIAM Journal on Control and Optimization. Vol. 42 (2003) Issue 1 . - pp. 98-122.
ISSN 1095-7138
DOI: https://doi.org/10.1137/S036301290240258X

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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 both cases we discuss situations when the sampling period T and the integration period h used in obtaining the approximate discrete-time plant model are the same or they are independent of each other. We show that using this approach practical and/or semiglobal stability of the exact discrete-time model is achieved under appropriate conditions.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Controller design; Asymptotic controllability; Stabilization; Numerical methods; Optimal control; Approximate model; Discretization; Sampling
Institutions of the University: 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
Faculties
Result of work at the UBT: No
DDC Subjects: 500 Science
500 Science > 510 Mathematics
Date Deposited: 02 Mar 2021 08:00
Last Modified: 09 Jan 2024 12:57
URI: https://eref.uni-bayreuth.de/id/eprint/63464