Title data
Stieler, Marleen ; Baumann, Michael Heinrich ; Grüne, Lars:
Noncooperative Model Predictive Control for Affine-Quadratic Games.
In: Proceedings in Applied Mathematics and Mechanics.
Vol. 18
(2018)
Issue 1
.
- e201800036.
ISSN 1617-7061
DOI: https://doi.org/10.1002/pamm.201800036
This is the latest version of this item.
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Project information
Project title: |
Project's official title Project's id DFG Project "Performance Analysis for Distributed and Multiobjective Model Predictive Control" Gr 1596/13-1 |
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Project financing: |
Bundesministerium für Bildung und Forschung Deutsche Forschungsgemeinschaft Hanns-Seidel-Stiftung Michael H. Baumann is supported by Hanns-Seidel-Stiftung e.V. (HSS), funded by Bundesministerium für Bildung und Forschung (BMBF). |
Abstract in another language
Nash strategies are a natural solution concept in noncooperative game theory because of their `stable' nature: If the other players stick to the Nash strategy it is never beneficial for one player to unilaterally change his or her strategy. In this sense, Nash strategies are the only reliable strategies.
The idea to perform and analyze Model Predictive Control (MPC) based on Nash strategies instead of optimal control sequences is appealing because it allows for a systematic handling of noncooperative games, which are played in a receding horizon manner. In this paper we extend existence and uniqueness results on Nash equilibria for affine-quadratic games. For this class of games we moreover state sufficient conditions that guarantee trajectory convergence of the MPC closed loop.
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Available Versions of this Item
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Noncooperative Model Predictive Control for Affine-Quadratic Games. (deposited 19 May 2018 21:00)
- Noncooperative Model Predictive Control for Affine-Quadratic Games. (deposited 19 Dec 2018 07:59) [Currently Displayed]