Affine formation maneuver control for multi-agent systems against false data injection attacks based on adaptive...

Area of Science:

• Control Systems Engineering
• Cybersecurity for Multi-Agent Systems
• Networked Systems

Background:

• Multi-agent systems are vulnerable to False Data Injection (FDI) attacks, compromising formation maneuvering.
• Existing control strategies may not adequately address adaptive attack compensation and communication efficiency.

Purpose of the Study:

• To develop an adaptive dual-terminal event-triggered control framework for secure affine formation maneuvering.
• To mitigate FDI attacks while maintaining system stability and reducing network load.

Main Methods:

• Integration of stress matrix-based affine localization and adaptive attack compensation.
• Implementation of a dual-channel event-triggered mechanism with time-dependent thresholds.
• Lyapunov stability analysis to ensure bounded tracking errors and prevent Zeno behavior.

Main Results:

• Successful reconstruction of attack-free states by follower agents.
• Demonstrated effective mitigation of FDI attacks.
• Preservation of formation integrity and robust system performance.
• Significant reduction in communication load through dynamic triggering.

Conclusions:

• The proposed framework provides a secure and efficient solution for formation maneuvering in multi-agent systems under FDI attacks.
• The adaptive and event-triggered approach balances security, performance, and communication efficiency.