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Distributed Consensus Tracking of Networked Agent Systems Under Denial-of-Service Attacks.

Authors :
Wan, Ying
Wen, Guanghui
Yu, Xinghuo
Huang, Tingwen
Source :
IEEE Transactions on Systems, Man & Cybernetics. Systems; Oct2021, Vol. 51 Issue 10, p6183-6196, 14p
Publication Year :
2021

Abstract

Distributed consensus tracking problem of networked agent systems with directed topologies under denial-of-service (DoS) attacks is investigated. The considered networked agent network consists of a physical layer with fixed physical links and a cyber layer with cyber control units. Both the communication network connecting these two layers and the cyber communication network within the cyber layer may subject to malicious DoS attacks. These two types of attacks have different impacts on the networked system; the former one affects the timely update of control inputs, and the latter influences the connection weights of the cyber communication graph. First, for DoS signals occurring in the communication network which transmits the state and control input information between the two layers, the distributed control protocol based on the event-triggered scheme and locally deployed estimators are designed. Efficient algorithms for selecting event-triggered control parameters and Zeno-free triggered parameters are given to ensure the mean-square consensus. The relationships between the system’s parameters and the features of DoS attacks are successfully revealed. Second, corresponding theoretical analysis is derived for consensus tracking of the networked systems when DoS attacks are launched within the cyber layer. Conditions concerning the length of repairing time and indexes of DoS attacks are given by utilizing hybrid control theory. At last, the effectiveness of the obtained results is demonstrated by performing simulations on multirobot systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21682216
Volume :
51
Issue :
10
Database :
Complementary Index
Journal :
IEEE Transactions on Systems, Man & Cybernetics. Systems
Publication Type :
Academic Journal
Accession number :
153713433
Full Text :
https://doi.org/10.1109/TSMC.2019.2960301