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Distributed and networked model predictive control

Title data

Grüne, Lars ; Allgöwer, Frank ; Findeisen, Rolf ; Fischer, Jörg ; Groß, Dominic ; Hanebeck, Uwe D. ; Kern, Benjamin ; Müller, Matthias A. ; Pannek, Jürgen ; Reble, Marcus ; Stursberg, Olaf ; Varutti, Paolo ; Worthmann, Karl:
Distributed and networked model predictive control.
In: Lunze, Jan (Hrsg.): Control theory of digitally networked dynamic systems. Chapter 4. - Cham ; Heidelberg ; New York ; Dordrecht ; London : Springer , 2014 . - pp. 111-167
ISBN 978-3-319-01130-1
DOI: https://doi.org/10.1007/978-3-319-01131-8_4

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Official URL: Volltext

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Project information

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

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

In this chapter, we consider the problem of controlling networked and distributed systems by means of model predictive control (MPC). The basic idea behind MPC is to repeatedly solve an optimal control problem based on a model of the system to be controlled. Every time a new measurement is available, the optimization problem is solved and the corresponding input sequence is applied until a new measurement arrives. As explained in the sequel, the advantages of MPC over other control strategies for networked systems are due to the fact that a model of the system is available at the controller side, which can be used to compensate for random bounded delays. At the same time, for each iteration of the optimization problem an optimal input sequence is calculated. In case of packet dropouts, one can reuse this information to maintain closed-loop stability and performance.

Further data

Item Type: Article in a book
Refereed: No
Keywords: control problems; systems theory; model predictive control; digital networks; centralized structures; decentralized structures
Subject classification: Mathematics Subject Classification Code: 93B51 (93B40 93A14)
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
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 15 Apr 2015 12:12
Last Modified: 15 Apr 2015 12:12
URI: https://eref.uni-bayreuth.de/id/eprint/10113