Adaptively Distributed Nash Equilibrium Seeking for Nonlinear Heterogeneous Networked Systems
Zhi Guo Feng, Xiwang Dong, Guoqiang Hu, Jinhu Lü · 2024
This paper studies an adaptively distributed Nash Equilibrium (NE) seeking problem in noncooperative games for nonlinear heterogeneous multi-agent systems (MASs) subject to uncertain system dynamics and communications. In contrast to existing related works that consider players with low-order dynamics, the goal is to make the outputs of nonlinear MASs converge towards the NE in a distributed and adaptive manner. By leveraging the consensus-based designs and pseudo-gradient strategies, novel adaptively distributed NE seeking algorithms that are independent of known information on the topology’s algebraic connectivity and the pseudo-gradient’s Lipschitz and monotone constants, are developed to seek the NE of games with a global asymptotic convergence. It is proved that the developed algorithms are capable of steering the outputs of agents towards the NE asymptotically. The examples and simulation results are presented to verify the proposed designs’ effectiveness.