Stochastic fault and cyber-attack detection and consensus control in multi-agent systems

ABSTRACT

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.

Keywords:

• Cyber-attack detection
• consensus control
• fault detection
• stochastic cyber-attack
• stochastic fault

Acknowledgments

K. Khorasani would like to acknowledge the support received from the NPRP grant number 10-0105-17017 from the Qatar National Research Fund (a member of Qatar Foundation), Natural Sciences and Engineering Research Council of Canada (NSERC), and the Department of National Defence (DND) under the Discovery Grant and DND Supplemental Programs.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

K. Khorasani would like to acknowledge the support received from the NPRP grant number 10-0105-17017 from the Qatar National Research Fund (a member of Qatar Foundation), Natural Sciences and Engineering Research Council of Canada (NSERC), and the Department of National Defence (DND) under the Discovery Grant and DND Supplemental Programs.