Prescribed-time multi-coalition Nash equilibrium seeking by event-triggered communication

被引:0
|
作者
Sun, Mengwei [1 ]
Ren, Lu [2 ,3 ]
Liu, Jian [1 ,4 ]
Sun, Changyin [1 ,2 ]
机构
[1] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
[2] Anhui Univ, Sch Artificial Intelligence, Hefei 230601, Anhui, Peoples R China
[3] Anhui Univ, Minist Educ, Engn Res Ctr Autonomous Unmanned Syst Technol, Hefei 230601, Anhui, Peoples R China
[4] Southeast Univ, Minist Educ, Key Lab Measurement & Control Complex Syst Engn, Nanjing 210096, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-coalition noncooperative game; Nash equilibrium seeking; Prescribed-time convergence; Event-triggered scheme; DISTRIBUTED OPTIMIZATION; GAMES;
D O I
10.1016/j.chaos.2024.115679
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This article investigates the event-triggered prescribed-time Nash equilibrium seeking problem among multiple coalitions of agents in noncooperative games. Each coalition acts as a virtual player in the noncooperative game, with decisions made by its member agents. Agents lack complete information about others' decisions and instead estimate them through a communication graph. An event-triggered prescribed-time multi-coalition Nash equilibrium seeking method is developed based on the leader-following consensus protocol, dynamic average consensus protocol, and gradient play. This method ensures the Nash equilibrium of the multi-coalition game is reached within a prescribed time, even when communication between agents only occurs under specific triggering conditions-effectively conserving communication resources. Unlike existing approaches, the proposed algorithm allows precise settling time assignment without prior knowledge of system parameters. This algorithm also prevents Zeno behavior. Lastly, the efficiency of the designed algorithm is demonstrated through simulation experiments.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Distributed event-triggered generalized Nash equilibrium seeking in multi-coalition noncooperative games with coupling constraints
    Li, Yamei
    Zhu, Yanan
    Li, Tao
    Zheng, Bochao
    ASIAN JOURNAL OF CONTROL, 2023, 25 (05) : 3859 - 3869
  • [2] An Efficient Distributed Nash Equilibrium Seeking With Compressed and Event-Triggered Communication
    Chen, Xiaomeng
    Huo, Wei
    Wu, Yuchi
    Dey, Subhrakanti
    Shi, Ling
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2025, 70 (03) : 2035 - 2042
  • [3] Prescribed-time distributed optimization and Nash equilibrium seeking
    Zhang M.-M.
    Ye M.-J.
    Zheng Y.-S.
    Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2022, 39 (08): : 1397 - 1406
  • [4] Predefined-Time Distributed Nash Equilibrium Seeking for Noncooperative Games With Event-Triggered Communication
    Liu, Jiehan
    Yi, Peng
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2023, 70 (09) : 3434 - 3438
  • [5] Distributed adaptive generalized Nash equilibrium seeking algorithm with event-triggered communication
    Cai, Xin
    Nan, Xinyuan
    Gao, Bingpeng
    ASIAN JOURNAL OF CONTROL, 2023, 25 (03) : 2239 - 2248
  • [6] Prescribed-time distributed Nash equilibrium seeking for noncooperation games?
    Zhao, Yu
    Tao, Qianle
    Xian, Chengxin
    Li, Zhongkui
    Duan, Zhisheng
    AUTOMATICA, 2023, 151
  • [7] An Event-Triggered Distributed Generalized Nash Equilibrium Seeking Algorithm
    Xu, Wenying
    Yang, Shaofu
    Grammatico, Sergio
    He, Wangli
    2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2021, : 4301 - 4306
  • [8] Distributed Nash Equilibrium Seeking Under Event-Triggered Mechanism
    Zhang, Kaijie
    Fang, Xiao
    Wang, Dandan
    Lv, Yuezu
    Yu, Xinghuo
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2021, 68 (11) : 3441 - 3445
  • [9] Distributed Nash equilibrium seeking with stochastic event-triggered mechanism
    Huo, Wei
    Tsang, Kam Fai Elvis
    Yan, Yamin
    Johansson, Karl Henrik
    Shi, Ling
    AUTOMATICA, 2024, 162
  • [10] A distributed event-triggered generalized Nash equilibrium seeking algorithm
    Cai, Xin
    Xiao, Feng
    Wei, Bo
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 5252 - 5257