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Event-triggered predictive control for cooperation-competition multi-agent systems under DoS attacks.

Ming Shi1, Xin Wang1

  • 1College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China.

ISA Transactions
|April 25, 2024
PubMed
Summary
This summary is machine-generated.

This study addresses bipartite consensus in multi-agent systems (MASs) facing denial-of-service (DoS) attacks. It introduces an event-triggered mechanism and predictive method to ensure system stability and resilience against attacks.

Keywords:
Bipartite consensusCooperation and competitionDoS attacksEvent-triggered controlPredictive control

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Area of Science:

  • Control Theory
  • Networked Systems
  • Cybersecurity

Background:

  • Multi-agent systems (MASs) often exhibit complex network topologies, including competitive-cooperative interactions.
  • Denial-of-service (DoS) attacks pose significant threats to the stability and performance of MASs by disrupting communication.
  • Achieving bipartite consensus, where agents converge to two distinct values, is crucial for coordinated behavior in certain MAS applications.

Purpose of the Study:

  • To investigate the bipartite consensus problem in MASs under competitive-cooperative network topologies and DoS attacks.
  • To analyze competitive phenomena in agent information exchange beyond simple cooperation.
  • To develop a robust control strategy that ensures bipartite consensus despite adversarial conditions.

Main Methods:

  • Analysis of competitive phenomena in agent interactions within the MAS.
  • Derivation of necessary conditions for achieving bipartite consensus.
  • Implementation of an event-triggered mechanism (ETM) to optimize information exchange and prevent Zeno behavior.
  • Application of a predictive method to enhance resistance against energy-limited DoS attacks and compensate for information loss.

Main Results:

  • Identified necessary conditions for bipartite consensus in the presence of competitive-cooperative dynamics.
  • Demonstrated that the ETM effectively reduces communication load and avoids Zeno behavior.
  • Showcased the predictive method's capability to resist DoS attacks and recover from information loss.
  • Validated the proposed approach's feasibility through numerical simulations.

Conclusions:

  • The proposed approach effectively achieves bipartite consensus in MASs under challenging network conditions and DoS attacks.
  • The combination of ETM and predictive methods offers a robust solution for secure and efficient multi-agent coordination.
  • The findings contribute to the development of resilient MASs for critical applications.