Distributed Nash equilibrium seeking for noncooperative games in nonlinear multi-agent systems: An event-triggered neuro-adaptive approach

This paper proposes a distributed Nash equilibrium seeking strategy for noncooperative games over strongly connected topologies, where the players suffer from unmodeled nonlinearities and external disturbances. By using the neural network (NN) universal approximation theorem, a neuro-adaptive seeking controller is proposed. Besides, the event-triggered mechanism is introduced to reduce communication costs of the players. Furthermore, by developing a Lyapunov function, it is shown that the states of the players asymptotically converge to the Nash equilibrium. Finally, a simulation is conducted to show the effectiveness of the proposed methods.