Prescribed-time distributed Nash equilibrium seeking for noncooperation games?

被引:20
作者
Zhao, Yu [1 ]
Tao, Qianle [1 ]
Xian, Chengxin [1 ]
Li, Zhongkui [2 ]
Duan, Zhisheng [3 ]
机构
[1] Northwestern Polytech Univ, Sch Automation, Xian 710129, Peoples R China
[2] Peking Univ, Coll Engn, Dept Mech & Aerosp Engn, Beijing 100871, Peoples R China
[3] Peking Univ, Dept Mech & Engn Sci, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
Nash equilibrium seeking; Prescribed-time algorithm; Sampled control; Without velocity measurement; CONVERGENCE;
D O I
10.1016/j.automatica.2023.110933
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates the prescribed-time distributed Nash equilibrium seeking (DNES) problem for multi-agent noncooperation games. Based on the distributed motion-planning method and the gradient search, a class of prescribed-time DNES algorithms are developed for first and second-order multi-agent systems, respectively. They may ensure each player' s action converges to the Nash equilibrium (NE) point at a prescribed settling time in advance. Further, for the case when the velocity information of each agent is not available, an observer-based prescribed-time DNES algorithm is extended. Compared with existing works, the convergence time of proposed prescribed-time DNES algorithms in this paper can be assigned in advance by users according to task requirements. Besides, the designed DNES algorithms are sampled without continuous measurements, which means players can update their actions at each sampling moment to avoid the increasing cost brought by continuous information interaction among players. Finally, the effectiveness of algorithms proposed in this paper is verified by some numerical simulations.(c) 2023 Elsevier Ltd. All rights reserved.
引用
收藏
页数:10
相关论文
共 38 条
[1]  
Baar Tamer., 1995, Dynamic Noncooperative Game Theory, V2nd
[2]  
Bryson A. E., 1975, Applied optimal control: optimization, estimation and control
[3]   Distributed discrete-time coordinated tracking with a time-varying reference state and limited communication [J].
Cao, Yongcan ;
Ren, Wei ;
Li, Yan .
AUTOMATICA, 2009, 45 (05) :1299-1305
[4]   A fixed-time convergent algorithm for distributed convex optimization in multi-agent systems [J].
Chen, Gang ;
Li, Zhiyong .
AUTOMATICA, 2018, 95 :539-543
[5]   Distributed Generalized Nash Equilibrium Seeking Algorithm Design for Aggregative Games Over Weight-Balanced Digraphs [J].
Deng, Zhenhua ;
Nian, Xiaohong .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30 (03) :695-706
[6]   A leader-following rendezvous problem of double integrator multi-agent systems [J].
Dong, Yi ;
Huang, Jie .
AUTOMATICA, 2013, 49 (05) :1386-1391
[7]   PENALTY METHODS FOR THE SOLUTION OF GENERALIZED NASH EQUILIBRIUM PROBLEMS [J].
Facchinei, Francisco ;
Kanzow, Christian .
SIAM JOURNAL ON OPTIMIZATION, 2010, 20 (05) :2228-2253
[8]  
Freeman RA, 2006, IEEE DECIS CONTR P, P339
[9]   Nash Equilibrium Seeking in Noncooperative Games [J].
Frihauf, Paul ;
Krstic, Miroslav ;
Basar, Tamer .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (05) :1192-1207
[10]   A Passivity-Based Approach to Nash Equilibrium Seeking Over Networks [J].
Gadjov, Dian ;
Pavel, Lacra .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (03) :1077-1092