Fully Distributed Adaptive Nash Equilibrium Seeking Algorithm for Constrained Noncooperative Games with Prescribed Performance

TL;DR

This paper presents a fully distributed adaptive algorithm for finding Nash equilibria in constrained noncooperative games, ensuring prescribed-time stability and validated through power market simulations.

Contribution

It introduces a novel fully distributed NE seeking algorithm with prescribed-time stability using adaptive penalties and uncoordinated gains, extending prior asymptotic results.

Findings

Achieves prescribed-time stability in NE seeking

Ensures fully distributed implementation

Validated through power market simulation

Abstract

This paper investigates a fully distributed adaptive Nash equilibrium (NE) seeking algorithm for constrained noncooperative games with prescribed-time stability. On the one hand, prescribed-time stability for the proposed NE seeking algorithm is obtained by using an adaptive penalty technique, a time-varying control gain and a cosine-related time conversion function, which extends the prior asymptotic stability result. On the other hand, uncoordinated integral adaptive gains are incorporated in order to achieve the fully distribution of the algorithm. Finally, the theoretical result is validated through a numerical simulation based on a standard power market scenario.