Cooperative control for cyber-physical multi-agent networked control systems with unknown false data-injection and...

Area of Science:

• Cyber-Physical Systems
• Networked Multi-Agent Systems
• Control Theory
• Cybersecurity

Background:

• Cyber-physical multi-agent networked systems face security vulnerabilities.
• Cascaded cyber-attacks, including false data injection and replay attacks, can disrupt system operations.
• Partial system knowledge and dissimilar attack types across network parts complicate security.

Purpose of the Study:

• To develop a robust cooperative tracking strategy for cyber-physical multi-agent systems under sophisticated cyber-attacks.
• To design adaptive observers and security controllers that can handle unknown attacks and partially known system parameters.
• To ensure follower agents asymptotically track the leader agent's state despite adversarial conditions.

Main Methods:

• Design of local adaptive observers to estimate states under unknown false data-injection and replay cyber-attacks.
• Development of a novel technique to compensate for unmatched terms arising from adaptive observers.
• Proposal of distributed adaptive leader-follower security controllers utilizing local estimates and neighbor information.

Main Results:

• Successful state estimation for follower agents using adaptive observers despite cyber-attacks.
• Effective compensation for unmatched terms, enhancing control accuracy.
• Guaranteed asymptotic cooperative tracking of followers to the leader under the proposed security control method.

Conclusions:

• The developed adaptive leader-follower security controllers effectively mitigate cascaded cyber-attacks in networked multi-agent systems.
• The proposed method ensures robust cooperative tracking performance even with partially known system parameters.
• The efficacy is validated through an illustrative example, demonstrating practical applicability.