Abstract
This paper investigates a Nash equilibrium seeking problem of aggregative games with linear coupling constraints, where the cost function of each player is coupled through an aggregative function. All players seek the Nash equilibrium by exchanging decision information with neighbors over strongly connected and weight-unbalanced digraphs. A novel distributed continuous-time algorithm is designed by using the Lagrangian multiplier method and the dynamic average consensus method. Then, we show exponential convergence of the designed algorithm by utilizing stability theory of nonlinear systems. Finally, a numerical simulation is provided to verify the effectiveness of our algorithm.
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