Distributed Adaptive Resilient Formation Control of Uncertain Nonholonomic Mobile Robots Under Deception Attacks

被引:37
作者
Wang, Wei [1 ]
Han, Zhen [1 ]
Liu, Kexin [1 ]
Lu, Jinhu [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Robots; Mobile robots; Robot kinematics; Robot sensing systems; Nuclear magnetic resonance; Trajectory; Integrated circuits; Adaptive resilient control; formation; nonholonomic mobile robots; deception attacks; uncertainties; MULTIAGENT SYSTEMS; CONSENSUS CONTROL; TRACKING CONTROL; SENSOR;
D O I
10.1109/TCSI.2021.3096937
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper investigates the formation control problem for a group of nonholonomic mobile robots (NMRs) with unknown parameters and deception attacks. The information transmitted among different robots is represented by a directed graph and only a subset of the robots can obtain the full information of the desired trajectory directly. For those robots which cannot access to the reference trajectory directly, distributed estimators are designed to estimate the unknown trajectory information by using only locally available information. Besides, the sensor-to-controller transmitting channels and the communication among connected robots are suffering from deception attacks. Adaptive laws and compensation terms are designed to handle the issue of attack-induced uncertainties. Then, a novel distributed resilient formation control scheme is designed, based on which a sufficient condition is developed to guarantee that the formation errors converge to a compact set and all the closed-loop signals are bounded. Experimental results are given to validate the theoretical studies.
引用
收藏
页码:3822 / 3835
页数:14
相关论文
共 30 条
  • [1] Improved adaptive resilient control against sensor and actuator attacks
    An, Liwei
    Yang, Guang-Hong
    [J]. INFORMATION SCIENCES, 2018, 423 : 145 - 156
  • [2] [Anonymous], 1995, NONLINEAR ADAPTIVE C
  • [3] Cui H., 2019, IEEE T CIRC SYST VID, V66, P1, DOI [DOI 10.1080/10298436.2018.1485917, 10.1080/09500340.2019.1648896, DOI 10.1109/TCSVT.2018.2793359]
  • [4] Sampled-Based Consensus for Nonlinear Multiagent Systems With Deception Attacks: The Decoupled Method
    Cui, Ying
    Liu, Yurong
    Zhang, Wenbing
    Alsaadi, Fuad E.
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (01): : 561 - 573
  • [5] A vision-based formation control framework
    Das, AK
    Fierro, R
    Kumar, V
    Ostrowski, JP
    Spletzer, J
    Taylor, CJ
    [J]. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2002, 18 (05): : 813 - 825
  • [6] Input-to-State Stabilizing Control Under Denial-of-Service
    De Persis, Claudio
    Tesi, Pietro
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (11) : 2930 - 2944
  • [7] A survey on security control and attack detection for industrial cyber-physical systems
    Ding, Derui
    Han, Qing-Long
    Xiang, Yang
    Ge, Xiaohua
    Zhang, Xian-Ming
    [J]. NEUROCOMPUTING, 2018, 275 : 1674 - 1683
  • [8] On scheduling of deception attacks for discrete-time networked systems equipped with attack detectors
    Ding, Derui
    Wei, Guoliang
    Zhang, Sunjie
    Liu, Yurong
    Alsaadi, Fuad E.
    [J]. NEUROCOMPUTING, 2017, 219 : 99 - 106
  • [9] Discrete-Communication-Based Bipartite Tracking of Networked Robotic Systems via Hierarchical Hybrid Control
    Ding, Teng-Fei
    Ge, Ming-Feng
    Liu, Zhi-Wei
    Wang, Yan-Wu
    Karimi, Hamid Reza
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2020, 67 (04) : 1402 - 1412
  • [10] Nonlinear formation control of unicycle-type mobile robots
    Do, K. D.
    Pan, J.
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2007, 55 (03) : 191 - 204