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[期刊论文]

Resilient Formation Control Based on Watermarks for Networked Quadrotors under Deception Attacks

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author:

Zhan, W. (Zhan, W..) [1] | Miao, Z. (Miao, Z..) [2] | Zeng, J. (Zeng, J..) [3] | Unfold

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Scopus

Abstract:

This article addresses the problem of formation control of networked UAVs under deception attacks. A lightweight resilient formation control framework based on watermarks is proposed to achieve the desired formation configuration without extra monitoring attack status. Since deception attacks are covert, the shared information is watermarked before transmission to establish the protocol among networked UAVs. To facilitate the resilient formation controller design, a decoder is first developed to decipher the inverse transformation of deception attacks, where the watermark is the criterion for approximating the inverse transformation. The Gauss error function is introduced to eliminate some unrealistic input commands under deception attacks, obtaining the predefined input performance. Then, a resilient formation controller is developed to guarantee the global boundedness of all signals within the inner-loop and outerloop system, while the formation error converges to a small neighborhood of zero by solving the linear matrix inequality. Two challenging deception attack examples in simulations and experiments are conducted to verify the effectiveness and performance of the proposed resilient formation control framework. © 1967-2012 IEEE.

Keyword:

Deception attacks linear matrix inquality networked UAVs resilient control watermark

Community:

  • [ 1 ] [Zhan W.]Hunan University, College of Electrical and Information Engineering, Changsha, 410082, China
  • [ 2 ] [Miao Z.]Hunan University, College of Electrical and Information Engineering, Changsha, 410082, China
  • [ 3 ] [Zeng J.]Hunan University, College of Electrical and Information Engineering, Changsha, 410082, China
  • [ 4 ] [Chen Y.]Fuzhou University, School of Mechanical Engineering and Automation, Fuzhou, 350108, China
  • [ 5 ] [Chen Y.]National Engineering Research Center of Robot Visual Perception and Control Technology, Changsha, 410082, China
  • [ 6 ] [Chen Y.]Zhejiang University, Institute of Cyber-Systems and Control, Hangzhou, 310027, China
  • [ 7 ] [Wu Z.-G.]Zhejiang University, Institute of Cyber-Systems and Control, Hangzhou, 310027, China
  • [ 8 ] [He W.]University of Science and Technology Beijing, Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education, School of Intelligence Science and Technology, Institute of Artificial Intelligence, Beijing, 100083, China
  • [ 9 ] [Wang Y.]Hunan University, College of Electrical and Information Engineering, Changsha, 410082, China
  • [ 10 ] [Wang Y.]National Engineering Research Center of Robot Visual Perception and Control Technology, Changsha, 410082, China

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Source :

IEEE Transactions on Vehicular Technology

ISSN: 0018-9545

Year: 2025

6 . 1 0 0

JCR@2023

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

30 Days PV: 1

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