Resilient Distributed Nash Equilibrium Control for Nonlinear MASs Under DoS Attacks.

Area of Science:

• Control Systems Engineering
• Game Theory
• Network Security

Background:

• Nonlinear multiagent systems (MASs) are susceptible to denial-of-service (DoS) attacks, disrupting communication and control.
• Existing Nash equilibrium (NE) seeking methods often fail under such adversarial conditions.
• Resilient control strategies are crucial for maintaining system performance in MASs with compromised communication.

Purpose of the Study:

• To develop a resilient distributed Nash equilibrium (NE) control strategy for nonlinear multiagent systems (MASs) under denial-of-service (DoS) attacks.
• To address the limitations of existing NE seeking algorithms in adversarial communication environments.
• To ensure the convergence of MASs to NE despite intermittent communication loss.

Main Methods:

• A layered NE control method integrating a resilient distributed NE seeking algorithm, two-stage cascade filters, and a resilient adaptive controller.
• Development of a novel NE seeking algorithm robust to DoS attacks.
• Design of two-stage cascade filters for smoothing control actions and their derivatives.

Main Results:

• The proposed resilient distributed NE seeking algorithm ensures convergence to NE even with DoS attacks.
• The two-stage cascade filters generate smooth control actions, enhancing system stability.
• The resilient adaptive controller guarantees that the MAS outputs converge to the NE under attack conditions.
• Simulation results validate the effectiveness of the proposed control strategy.

Conclusions:

• The novel layered control method effectively addresses the resilient distributed NE control problem for nonlinear MASs under DoS attacks.
• The developed algorithms and filters provide a robust solution for maintaining NE convergence in adversarial environments.
• This work contributes a significant advancement in secure and resilient control for networked multiagent systems.