Dynamic event-based finite-horizon H_∞ secure consensus control of a class of nonlinear multi-agent systems

Area of Science:

• Control Systems Engineering
• Networked Systems
• Cybersecurity

Background:

• Multi-agent systems (MASs) face challenges in achieving consensus under adversarial conditions.
• Existing control strategies may not adequately address the complexity of multiple, simultaneous attacks.

Purpose of the Study:

• To investigate H∞ consensus control for nonlinear MASs under multiple attack scenarios.
• To develop a robust output feedback control strategy resilient to diverse cyber threats.
• To introduce a dynamic event-triggered scheme for efficient data sharing.

Main Methods:

• A novel model characterizing denial-of-service (DoS), scaling, and replay attacks.
• Implementation of a dynamic event-triggered scheme for communication efficiency.
• Design of an output feedback strategy based on convex optimization algorithms.

Main Results:

• Conditions for the solvability of the H∞ consensus control problem are established.
• Feedback gains are derived using convex optimization techniques.
• The proposed strategy effectively achieves H∞ consensus performance under multiple attacks.

Conclusions:

• The developed approach provides a robust solution for H∞ consensus control in nonlinear MASs facing sophisticated attacks.
• The dynamic event-triggered scheme enhances communication efficiency while maintaining control performance.
• Simulation examples validate the effectiveness of the proposed theoretical results.