Distributed Nash Equilibrium Seeking for Double‐Integrator Multiagent Systems via Event‐Triggered Communication

This paper develops a distributed Nash equilibrium‐seeking algorithm tailored for double‐integrator multiagent systems. It specifically addresses the critical problems of information loss caused by limited communication in an incomplete information environment. By integrating the leader‐following consensus framework with the decentralized gradient‐based dynamic event‐triggered scheme, information sampling, estimation, and transmission are restricted to occur only at designated triggered moments. The strategy establishes sufficient conditions for achieving exponential convergence to the Nash equilibrium, while also highlighting the impact of parameter design on system convergence. Additionally, it contributes a fresh perspective on tackling distributed Nash equilibrium challenges in multiagent systems. A simulation case under two sets of different parameters is presented to verify the validity of the proposed scheme.