Journal
INTERNATIONAL JOURNAL OF CONTROL
Volume 95, Issue 9, Pages 2379-2397Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207179.2021.1912394
Keywords
Cyber-attack detection; consensus control; fault detection; stochastic cyber-attack; stochastic fault
Categories
Funding
- Qatar National Research Fund (a member of Qatar Foundation) [10-0105-17017]
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Department of National Defence (DND) under the Discovery Grant and DND Supplemental Programs
Ask authors/readers for more resources
This paper investigates the stochastic fault and cyber-attack detection and consensus control problems for multi-agent systems, proposing an effective method that incorporates Markovian approach and Bayesian inference to detect and control stochastic faults and cyber-attacks in the system. Simulation and case study results confirm the effectiveness and capabilities of the proposed methodologies for a team of multi-agent Autonomous Underwater Vehicles (UAVs).
In this paper, the stochastic fault and cyber-attack detection and consensus control problems are investigated for multi-agent systems. By using a Markovian approach, Linear Matrix Inequalities (LMI) are derived that incorporate relative information among the agents to detect stochastic faults and cyber-attacks and then resiliently control the system to reach a consensus. A mixed coding and Message Authentication approach is presented to detect data injection cyber-attacks on the communication links. By using the Bayesian inference, useful information regarding the cyber-attack, such as the probability of its occurrence, is derived. Simulation and two case study results corresponding to a team of multi-agent Autonomous Underwater Vehicles (UAVs) confirm and verify the effectiveness and capabilities of our proposed methodologies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available