The role of sampling for stability and performance in unconstrained nonlinear model predictive control

URN to cite this document: urn:nbn:de:bvb:703-epub-2009-7

Title data

Worthmann, Karl ; Reble, Marcus ; Grüne, Lars ; Allgöwer, Frank:
The role of sampling for stability and performance in unconstrained nonlinear model predictive control.
Department of Mathematics, University of Bayreuth
Bayreuth, , 2014 . - 23 S.

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Name:	Worthmann_Reble_Gruene_Allgoewer_role_sampling_stab_perform_unconstr_nonlin_mpc_2014.pdf
Version:	Accepted Version
Available under License	German copyright law. This contribution is freely accessible with the consent of the copyright holder on the basis of an (DFG-funded) alliance or national license. The document may be used free of charge for personal use. In addition, the reproduction, editing, distribution and any kind of exploitation require the written consent of the respective rights holder.

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Project information

Project title:

Project's official title	Project's id
DFG Priority Programme 1305 "Control theory for digitally networked dynamical systems", Project "Development of decentralized asynchronous predictive control methods for digitally networked systems"	GR1569/12-2

Project financing:

Deutsche Forschungsgemeinschaft

Abstract

We investigate the impact of sampling on stability and performance estimates in nonlinear model predictive control without stabilizing terminal constraints. Interpreting the sampling period as a discretization parameter, the relation between continuous and discrete time estimates depending on this parameter is analyzed. The technique presented in this paper allows to determine the sampling rate required in order to approximate the continuous time suboptimality bound arbitrarily well and, thus, gives insight into the trade-off between sampling time and guaranteed performance.

Further data

Item Type:	Preprint, postprint
Additional notes (visible to public):	erschienen in: SIAM Journal on Control and Optimization. Bd. 52 (2014) Heft 1 . - S. 581-605. DOI: https://doi.org/10.1137/12086652X A preliminary version was published at the homepage of the first author in February 2012.
Keywords:	nonlinear model predictive control; performance guarantee; suboptimality estimate; sampling rate; multistep feedback laws; discretization; receding horizon control; relaxed Lyapunov inequality
Subject classification:	Mathematics Subject Classification Code: 93C10 93C20 93C57 93B05 93D15 93D20 93D05
DDC Subjects:	500 Science > 510 Mathematics
Institutions of the University:	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 Profile Fields > Advanced Fields > Nonlinear Dynamics 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) Profile Fields Profile Fields > Advanced Fields
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-2009-7
Date Deposited:	17 Apr 2015 07:34
Last Modified:	01 Jun 2021 09:42
URI:	https://epub.uni-bayreuth.de/id/eprint/2009

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