Resilient Containment Control in Adversarial Environment

被引:14
|
作者
Yan, Jiaqi [1 ]
Wen, Changyun [1 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
来源
关键词
Protocols; Control systems; Security; Network topology; Distributed algorithms; Standards; Signal processing algorithms; Containment control; cybersecurity; resilient algorithms; robust graphs; REACHING APPROXIMATE AGREEMENT; MULTIAGENT SYSTEMS; CONSENSUS; DYNAMICS;
D O I
10.1109/TCNS.2020.3017922
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 article considers the problem of containment control in an adversarial environment, where some of the agents might be misbehaving (or faulty). Despite the influence of network misbehaviors, the normal followers aim to move into the convex hull spanned by the normal leaders. Toward this goal, resilient containment control is investigated in this work. We propose secure protocols for both first-order and second-order systems, where each normal follower ignores the most extreme values in its neighborhood and modifies its state based on the remaining ones. Assuming that the number of malicious agents is locally upper bounded, sufficient conditions on the network topology are derived to guarantee the achievement of resilient containment. Numerical examples are also provided in the end to verify our theoretical results.
引用
收藏
页码:1951 / 1959
页数:9
相关论文
共 50 条
  • [21] Containment control of multi-agent systems in a noisy communication environment
    Wang, Yunpeng
    Cheng, Long
    Hou, Zeng-Guang
    Tan, Min
    Wang, Ming
    AUTOMATICA, 2014, 50 (07) : 1922 - 1928
  • [22] Resilient Collaborative Intelligence for Adversarial IoT Environments
    Weerakoon, Dulanga
    Jayarajah, Kasthuri
    Tandriansyah, Randy
    Misra, Archan
    2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019), 2019,
  • [23] Making Images Resilient to Adversarial Example Attacks
    Tian, Shixin
    Cai, Ying
    Bao, Forrest
    Oruganti, Ramakrishna
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2022, PT III, 2022, 13531 : 188 - 199
  • [24] Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors
    Lapid, Raz
    Dubin, Almog
    Sipper, Moshe
    MATHEMATICS, 2024, 12 (22)
  • [25] Adversarial Models and Resilient Schemes for Network Coding
    Nutman, Leah
    Langberg, Michael
    2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6, 2008, : 171 - 175
  • [26] Resilient Output Containment Control of Heterogeneous Multiagent Systems Against Composite Attacks: A Digital Twin Approach
    Cui, Yukang
    Cao, Lingbo
    Gong, Xin
    Basin, Michael V.
    Shen, Jun
    Huang, Tingwen
    IEEE TRANSACTIONS ON CYBERNETICS, 2024, 54 (05) : 3313 - 3326
  • [27] Resilient Event-Triggered Containment Control of Multiagent Systems Under Asynchronous DoS Attacks and Disturbances
    Mousavian, Mohammad
    Atrianfar, Hajar
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2025, 12 (01): : 85 - 95
  • [28] Adaptive resilient containment control for nonlower triangular multiagent systems with time-varying delay and sensor faults
    Li, Zan
    Cao, Liang
    Pan, Yingnan
    Zhang, Pengchao
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2022, 359 (17): : 9759 - 9781
  • [29] Output Resilient Containment Control of Heterogeneous Systems With Active Leaders Using Reinforcement Learning Under Attack Inputs
    Li, Qing
    Xia, Lina
    Song, Ruizhuo
    IEEE ACCESS, 2019, 7 : 162219 - 162228
  • [30] Mixed self/event-triggered ternary control for resilient consensus against mobile adversarial agents
    Matsume, Hiroki
    Wang, Yuan
    Ishii, Hideaki
    Defago, Xavier
    NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2024, 52