TY - GEN
T1 - Distributed adaptive Nash equilibrium seeking over multi-agent networks with communication uncertainties
AU - Fang, Xiao
AU - Wen, Guanghui
AU - Zhou, Jialing
AU - Zheng, Wei Xing
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper aims to address the distributed Nash equilibrium seeking problem for noncooperative games over multi-agent networks in the presence of communication uncertainties. Compared with the existing results on distributed Nash equilibrium seeking, the underlying communication network of the agents considered in this paper is subjected to unknown communication uncertainties. Specifically, the coupling weights on communication channels are perturbed by bounded uncertain signals. To achieve the goal of Nash equilibrium seeking, two distributed adaptive Nash equilibrium seeking algorithms based on the cooperative tracking protocol and estimate feedback respectively are proposed by designing adaptive coupling weights to overcome the effect of the communication uncertainties on Nash equilibrium seeking. The convergence of the proposed algorithms is theoretically analyzed and the effectiveness of the algorithms is illustrated by simulation results.
AB - This paper aims to address the distributed Nash equilibrium seeking problem for noncooperative games over multi-agent networks in the presence of communication uncertainties. Compared with the existing results on distributed Nash equilibrium seeking, the underlying communication network of the agents considered in this paper is subjected to unknown communication uncertainties. Specifically, the coupling weights on communication channels are perturbed by bounded uncertain signals. To achieve the goal of Nash equilibrium seeking, two distributed adaptive Nash equilibrium seeking algorithms based on the cooperative tracking protocol and estimate feedback respectively are proposed by designing adaptive coupling weights to overcome the effect of the communication uncertainties on Nash equilibrium seeking. The convergence of the proposed algorithms is theoretically analyzed and the effectiveness of the algorithms is illustrated by simulation results.
UR - http://www.scopus.com/inward/record.url?scp=85126035377&partnerID=8YFLogxK
U2 - 10.1109/CDC45484.2021.9683032
DO - 10.1109/CDC45484.2021.9683032
M3 - Conference contribution
AN - SCOPUS:85126035377
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3387
EP - 3392
BT - 60th IEEE Conference on Decision and Control, CDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 60th IEEE Conference on Decision and Control, CDC 2021
Y2 - 13 December 2021 through 17 December 2021
ER -