自动化学报2024，Vol.50Issue(6)：1210-1220,11.DOI:10.16383/j.aas.c230584
自适应分布式聚合博弈广义纳什均衡算法
Distributed Adaptive Generalized Nash Equilibrium Algorithm for Aggregative Games
摘要
Abstract
With the development of cyber-physical system technology,the distributed cooperative optimization problem for multi-agent systems has been widely studied.This study focuses on the distributed constrained aggreg-ative game for multi-agent systems,where the local cost function is subject to the global aggregative and global equality constraints.Firstly,a Nash equilibrium seeking algorithm based on estimation gradient descent is designed for the first-order integrator-based multi-agent systems.To this end,an adaptive estimation scheme is designed us-ing the average consensus method of multi-agent systems to realize the distributed estimation of global aggregative function.Based on this,the estimation gradient function is calculated.Secondly,the above algorithm is extended to the state-accessible and state-inaccessible general heterogeneous linear multi-agent systems using the state and out-put feedback control scheme,respectively.Finally,the convergence proof is provided using the LaSalle's invariance principle and several simulation examples are provided for illustrating the effectiveness of our proposed algorithms.关键词
聚合博弈/自适应/比例积分/梯度跟踪/一般线性多智能体系统Key words
Aggregative game/adaptive/proportional-integral/gradient tracking/general linear multi-agent system引用本文复制引用
时侠圣,任璐,孙长银..自适应分布式聚合博弈广义纳什均衡算法[J].自动化学报,2024,50(6):1210-1220,11.基金项目
国家自然科学基金创新研究群体科学基金(61921004),国家自然科学基金重点项目(62236002,62136008),国家自然科学基金(62303009)资助 Supported by Foundation for Innovative Research Groups of National Natural Science Foundation of China(61921004),Key Projects of National Natural Science Foundation of China(62236002,62136008),and National Natural Science Foundation of China(62303009) （61921004）
