Predefined-Time Distributed Nash Equilibrium Seeking for Noncooperative Games With Event-Triggered Communication
Jiehan Liu, Peng Yi
Abstract
In this brief, we investigate a predefined-time distributed Nash equilibrium seeking problem for a class of noncooperative games under an event-triggered scenario. To achieve fast convergence while reducing the communication and computation costs, a novel distributed Nash equilibrium seeking approach is proposed by applying the gradient play, a consensus-based estimator, and a time base generator (TBG). Different from existing works on Nash equilibrium computation under a bounded convergence time, the design of distributed algorithm in this brief is based on a newly developed TBG. The new TBG is more efficient and convenient than the traditional TBG. By virtue of an adaptive event-triggered rule, the distributed estimators are designed to estimate other players’ actions over strongly connected directed graphs. Moreover, the predefined-time convergence analysis of the players’ actions to the Nash equilibrium is given based on the Lyapunov stability method. Finally, simulation studies are provided to demonstrate the effectiveness of the constructed TBG and the advantages of the derived strategy.