2017
DOI: 10.1016/j.automatica.2017.07.064
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Distributed Nash equilibrium seeking for aggregative games with coupled constraints

Abstract: In this paper, we study a distributed continuous-time design for aggregative games with coupled constraints in order to seek the generalized Nash equilibrium by a group of agents via simple local information exchange. To solve the problem, we propose a distributed algorithm based on projected dynamics and non-smooth tracking dynamics, even for the case when the interaction topology of the multi-agent network is time-varying. Moreover, we prove the convergence of the non-smooth algorithm for the distributed gam… Show more

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Cited by 223 publications
(197 citation statements)
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“…The exogenous disturbance results that most of existing distributed algorithms cannot ensure the multiagent system converge to the GNE of the game. Moreover, the communication among players is depicted by weight‐balanced digraphs, which extend undirected graphs considered by most of existing results about aggregative games . Besides, unlike the differential games that are known as dynamic games (see the work of Başar and Olsder for details), the aggregative games considered here are static games, where the cost functions of all players are independent of the derivatives of decisions and the transient trajectories given by algorithms, though exogenous disturbances are involved for players.…”
Section: Preliminaries and Formulationmentioning
confidence: 99%
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“…The exogenous disturbance results that most of existing distributed algorithms cannot ensure the multiagent system converge to the GNE of the game. Moreover, the communication among players is depicted by weight‐balanced digraphs, which extend undirected graphs considered by most of existing results about aggregative games . Besides, unlike the differential games that are known as dynamic games (see the work of Başar and Olsder for details), the aggregative games considered here are static games, where the cost functions of all players are independent of the derivatives of decisions and the transient trajectories given by algorithms, though exogenous disturbances are involved for players.…”
Section: Preliminaries and Formulationmentioning
confidence: 99%
“…Remark 1. Different from most of aggregative games, 11,[15][16][17][18][19][20] our formulation involves exogenous disturbances for players. The exogenous disturbance results that most of existing distributed algorithms cannot ensure the multiagent system (7) converge to the GNE of the game.…”
Section: Assumption 3 F(x) Is -Strongly Monotone and -Lipschitz Contmentioning
confidence: 99%
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