Adaptive Fuzzy Secure Consensus Control of Nonlinear Multi-Agent Systems Under Deception Attacks

This paper investigates the secure consensus control problem for nonlinear multi-agent systems (MASs) under de-ception attacks. The main characteristic of the proposed secure consensus control method is its ability to mitigate undesirable system behaviors caused by deception attacks at the communication links among different agents. In particular, the relationship between the compromised signals and the output signals of MASs is analyzed. Furthermore, a novel Nussbaum function and an adaptive fuzzy law are respectively proposed to tackle the unknown control direction and to estimate the unknown terms caused by deception attacks. Simulation results are presented to demonstrate the validity of the proposed adaptive consensus secure control method.

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Publication Details

Published
2024-08-10
DOI
https://doi.org/10.1109/ifuzzy63051.2024.10662875
Citations
1
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
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Adaptive Fuzzy Secure Consensus Control of Nonlinear Multi-Agent Systems Under Deception Attacks

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Distributed Control Multi-Agent Systems
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article

Adaptive Fuzzy Secure Consensus Control of Nonlinear Multi-Agent Systems Under Deception Attacks

Tong Wang, Yannan Bi, Jianbin Qiu, Pansheng Ding, Fei Wang
article en
1 citations

Abstract

This paper investigates the secure consensus control problem for nonlinear multi-agent systems (MASs) under de-ception attacks. The main characteristic of the proposed secure consensus control method is its ability to mitigate undesirable system behaviors caused by deception attacks at the communication links among different agents. In particular, the relationship between the compromised signals and the output signals of MASs is analyzed. Furthermore, a novel Nussbaum function and an adaptive fuzzy law are respectively proposed to tackle the unknown control direction and to estimate the unknown terms caused by deception attacks. Simulation results are presented to demonstrate the validity of the proposed adaptive consensus secure control method.

Harbin Institute of Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 39%
Distributed Control Multi-Agent Systems
0.35
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