Distributed Resilient Event-Triggered Nash Equilibrium Seeking for Noncooperative Games with Dead-Zone Inputs: A Low-Frequency Neuro-Adaptive Approach

For the non-cooperative game in network systems, in which players are controlled by unknown dead-zone inputs and subjected to false data injection (FDI) attacks, a distributed Nash equilibrium (NE) seeking algorithm is proposed. The control strategy utilizes an adaptive compensation algorithm with low frequency feature, which is applied in NE seeking algorithms. Moreover, the dynamic system adopts an event-triggered mechanism to decrease the communication costs of players. Additionally, the asymptotic convergence of the players' strategies toward the NE is proved with Lyapunov function. At last, simulations are conducted to exhibit the proficiency of the proposed methods.