Federated Control: A Trustable Control Framework for Large-Scale Cyber-Physical Systems

被引:2
|
作者
Zhu, Jing [1 ,2 ]
Yuan, Yong [5 ]
Wang, Fei-Yue [3 ,4 ]
Wang, Ge [2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China
[2] Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
[3] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100023, Peoples R China
[4] Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
[5] Renmin Univ China, Sch Math, Beijing 100872, Peoples R China
关键词
Blockchains; Control systems; Encryption; Data privacy; Data models; Process control; Topology; Cosmos; cyber-physical system (CPS); distributed control; federated ecology; multiblockchain structure; BLOCKCHAIN; SECURITY;
D O I
10.1109/TII.2024.3363092
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To break the dilemma of data island, a distributed framework for trustable control is proposed toward information security and data privacy in large-scale cyber-physical systems. The federated control system consists of distinct blockchains, as such information security and data privacy are technologically guaranteed. Moreover, data are divided into private and nonprivate data. Only nonprivate data can be exchanged for a better global system performance, where the interblockchain communication is ensured by cross-blockchain technologies. Federated control framework establishes a trustable environment where each subsystem is willing to share data for optimal performance. The architecture, structure, and implementation process of federated control are discussed, together with the potential applications to smart buildings.
引用
收藏
页码:7986 / 7994
页数:9
相关论文
共 50 条
  • [41] Hypergames and Cyber-Physical Security for Control Systems
    Bakker, Craig
    Bhattacharya, Arnab
    Chatterjee, Samrat
    Vrabie, Draguna L.
    ACM TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS, 2020, 4 (04)
  • [42] Congestion Control in Molecular Cyber-Physical Systems
    Felicetti, Luca
    Femminella, Mauro
    Reali, Gianluca
    IEEE ACCESS, 2017, 5 : 10000 - 10011
  • [43] Optimization and Control of Cyber-Physical Vehicle Systems
    Bradley, Justin M.
    Atkins, Ella M.
    SENSORS, 2015, 15 (09) : 23020 - 23049
  • [44] Optimal Defense and Control for Cyber-Physical Systems
    Niu, Haifeng
    Jagannathan, S.
    2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI), 2015, : 634 - 639
  • [45] Covert Attacks in Cyber-Physical Control Systems
    de Sa, Alan Oliveira
    Rust da Costa Carmo, Luiz F.
    Machado, Raphael C. S.
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (04) : 1641 - 1651
  • [46] Resilience of cyber-physical manufacturing control systems
    Moghaddam, Mohsen
    Deshmukh, Abhijit
    MANUFACTURING LETTERS, 2019, 20 : 40 - 44
  • [47] Learning Tracking Control for Cyber-Physical Systems
    Wu, Chengwei
    Pan, Wei
    Sun, Guanghui
    Liu, Jianxing
    Wu, Ligang
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (11) : 9151 - 9163
  • [48] Special Issue on Control of Cyber-Physical Systems
    Johansson, Karl H.
    Pappas, George J.
    Tabuada, Paulo
    Tomlin, Claire J.
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (12) : 3120 - 3121
  • [49] The analysis of traffic control cyber-physical systems
    Shi Jianjun
    Wu Xu
    Guan Jizhen
    Chen Yangzhou
    INTELLIGENT AND INTEGRATED SUSTAINABLE MULTIMODAL TRANSPORTATION SYSTEMS PROCEEDINGS FROM THE 13TH COTA INTERNATIONAL CONFERENCE OF TRANSPORTATION PROFESSIONALS (CICTP2013), 2013, 96 : 2487 - 2496
  • [50] Cyber-Physical Systems: Computation, Communication, and Control
    Zhang, Liguo
    Fallah, Yaser P.
    Jihene, Rezgui
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2013,