Distributed Adaptive Nash Equilibrium Seeking for Multiagent Games Under Time-Varying Networks

This paper examines the Nash equilibrium seeking (NES) problem in non-cooperative games involving multiagent systems operating within time-varying networks. The system being studied encompasses unmeasured states and unknown nonlinear functions. To address this, an adaptive NES algorithm is developed using gradient play and a distributed backstepping approach. Additionally, a fuzzy logic system is employed to compensate external disturbance, and an adaptive distributed observer is proposed to share non-neighbor states and facilitate information sharing within the context of a time-varying network. The convergence of the proposed approach is rigorously proven by leveraging the principles of Lyapunov stability theory. The effectiveness of the proposed method is confirmed through a comprehensive analysis of simulation results and physical experiments.