Reinforcement learning based optimal synchronization control for multi-agent systems with input constraints using vanishing viscosity method

被引：0
|
作者：
Zhang, Dianfeng [1 ]
Yao, Ying [1 ]
Wu, Zhaojing [1 ]
机构：
[1] School of Mathematics and Information Sciences, Yantai University, Yantai,264005, China
来源：
Information Sciences | 2023年 / 637卷
关键词：
Compendex;
D O I：
118949
中图分类号：
学科分类号：
摘要：
Disturbance rejection
引用
收藏
相关论文
共 9 条
  • [1] Performance-Based Human-in-the-Loop Optimal Bipartite Consensus Control for Multi-Agent Systems via Reinforcement Learning
    Huang, Zongsheng
    Li, Tieshan
    Long, Yue
    Yang, Hanqing
    2024 14th International Conference on Information Science and Technology, ICIST 2024, 2024, : 497 - 502
  • [2] Redundant Robot Control Using Multi Agent Reinforcement Learning
    Perrusquia, Adolfo
    Yu, Wen
    Li, Xiaoou
    IEEE International Conference on Automation Science and Engineering, 2020, 2020-August : 1650 - 1655
  • [3] Collaborative learning in e-learning based on multi-agent systems
    Software College, Zhejiang University of Technology, Hangzhou, 310014, China
    不详
    Southeast University, China; IEEE Beijing Section; National Natural Science Foundation of China; CIMS Committee, National Hi-Tech R and D Program of China; K.C.Wong Education Foundation, Hong Kong, 1600, 1398-1402 (2006):
  • [4] Collaborative Optimization of Multi-microgrid System Based on Multi-agent Game and Reinforcement Learning
    Liu, Junfeng
    Wang, Xiaosheng
    Lu, Junbo
    Zeng, Jun
    Dianwang Jishu/Power System Technology, 2022, 46 (07): : 2722 - 2732
  • [5] Iterative Learning Control for Multi-Agent Systems with Finite-Leveled Sigma-Delta Quantizer and Input Saturation
    Zhang, Ting
    Li, Junmin
    Chinese Control Conference, CCC, 2021, 2021-July : 5637 - 5644
  • [6] Improving Multi agent Systems Based on Reinforcement Learning and Case Base Reasoning
    Department of Computer Engineering and Information Technology, Islamic Azad University, Qazvin Branch, Qazvin, Iran
    不详
    不详
    Int. J. Comput. Sci. Issues, 1 1-3 (130-138): : 130 - 138
  • [7] Access Point Clustering in Cell-Free Massive MIMO Using Conventional and Federated Multi-Agent Reinforcement Learning
    Banerjee, Bitan
    Elliott, Robert C.
    Krzymień, Witold A.
    Medra, Mostafa
    IEEE Transactions on Machine Learning in Communications and Networking, 2023, 1 : 107 - 123
  • [8] Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Interactive Traffic Scenarios
    Liu, Qi
    Li, Zirui
    Li, Xueyuan
    Wu, Jingda
    Yuan, Shihua
    IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2022, 2022-October : 4074 - 4081
  • [9] Demand Side Management and Peer-to-Peer Energy Trading for Industrial Users Using Two-Level Multi-Agent Reinforcement Learning
    Wang, Jiatong
    Mishra, Dillip Kumar
    Li, Li
    Zhang, Jiangfeng
    IEEE Transactions on Energy Markets, Policy and Regulation, 2023, 1 (01): : 23 - 36
1