Distributed Fuzzy Resilient Tracking for Nonlinear MASs Under DoS Attacks

In this paper, the distributed fuzzy resilient tracking problem for a class of second-order nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks is addressed. Compared with the existing distributed fuzzy tracking results, a more general class of second-order MASs with DoS attac...

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Bibliographic Details
Published in:International journal of control, automation, and systems automation, and systems, 2023-10, Vol.21 (10), p.3176-3186
Main Authors: Gao, Shu-Huan, Chen, Mengmeng, Deng, Chao
Format: Article
Language:English
Subjects:
Control
Control methods
Denial of service attacks
Engineering
Fuzzy control
Mechatronics
Multiagent systems
Nonlinear systems
Regular Papers
Robotics
Tracking problem
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Summary:In this paper, the distributed fuzzy resilient tracking problem for a class of second-order nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks is addressed. Compared with the existing distributed fuzzy tracking results, a more general class of second-order MASs with DoS attacks under combined output observable situation are considered in this paper. Under DoS attacks, the second-order derivative of the traditional distributed observer does not exist, while this signal is necessary to solve the distributed fuzzy tracking problem for second-order MASs when using the backstepping method. To solve the problem, a hierarchical control method that consists of a cooperative resilient observer and a distributed controller is proposed. Specifically, a new distributed resilient observer state with a second-order derivative and also the function of defending network attacks is designed based on a combined output observable condition. By using the backstepping technique, decentralized fuzzy adaptive resilient controllers are designed to achieve distributed tracking under DoS attacks. It is shown that the distributed fuzzy resilient tracking problem can be solved under our designed method. Finally, second-order nonlinear MASs are provided to verify the effectiveness of our method.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-022-0881-2