Title data
Stieler, Marleen ; Baumann, Michael Heinrich ; Grüne, Lars:
Noncooperative Model Predictive Control for AffineQuadratic Games.
Bayreuth
,
2018
.  2 p.
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Project information
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Project financing: 
Bundesministerium für Bildung und Forschung Deutsche Forschungsgemeinschaft HannsSeidelStiftung Michael H. Baumann is supported by HannsSeidelStiftung 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 affinequadratic games. For this class of games we moreover state sufficient conditions that guarantee trajectory convergence of the MPC closed loop.
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 Noncooperative Model Predictive Control for AffineQuadratic Games. (deposited 19 May 2018 21:00) [Currently Displayed]