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Title data
Stieler, Marleen ; Baumann, Michael Heinrich ; Grüne, Lars:
Noncooperative Model Predictive Control for Affine-Quadratic Games.
Bayreuth
,
2018
. - 2 S.
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Project information
| Project title: |
Project's official title Project's id Analyse der Regelgüte für verteilte und multikriterielle Modellprädiktive Regelung — Die Rolle von Paretofronten, multikriterieller Dissipativität und mehrfachen Gleichgewichten 244602989 |
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| Project financing: |
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
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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