Data-Driven Practical Cooperative Output Regulation Under Actuator Faults and DoS Attacks.

Area of Science:

• Control Systems Engineering
• Cyber-Physical Systems
• Distributed Systems

Background:

• Multiagent systems are vulnerable to denial-of-service (DoS) attacks and actuator faults, compromising their cooperative output regulation.
• Existing solutions often require knowledge of system parameters, limiting their applicability in real-world scenarios.

Purpose of the Study:

• To develop a resilient practical cooperative output regulation strategy for multiagent systems under DoS attacks and actuator faults.
• To introduce a novel data-driven control approach that does not require prior knowledge of system parameters.

Main Methods:

• Design of resilient distributed observers to handle DoS attacks.
• Implementation of a resilient communication mechanism and time-varying sampling periods to counter intelligent attacks.
• Development of a fault-tolerant and resilient controller using Lyapunov approach and output regulation theory.
• Utilization of a data-driven algorithm for controller parameter learning.

Main Results:

• The proposed method enables resilient practical cooperative output regulation in multiagent systems.
• The data-driven approach effectively handles unknown system parameters.
• The system demonstrates robustness against DoS attacks and actuator faults.

Conclusions:

• The novel data-driven control strategy ensures resilient cooperative output regulation for multiagent systems facing complex adversarial conditions.
• The approach overcomes limitations of existing methods by not requiring system parameter knowledge, offering a practical solution.