4.7 Article

Event-Triggered Adaptive Fault-Tolerant Pinning Control for Cluster Consensus of Heterogeneous Nonlinear Multi-Agent Systems Under Aperiodic DoS Attacks

Journal

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TNSE.2021.3077766

Keywords

Multi-agent systems (MASs); fault-tolerant pinning control; event-triggered mechanism; denial-of-service (DoS) attacks; cluster consensus; integral quadratic constraints (IQCs)

Funding

  1. National Natural Science Foundation of China [61773056]
  2. Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB [BK19AE018]
  3. Fundamental Research Funds for the Central Universities of USTB [FRF-TP-20-09B, 230201606500061, FRFDF-20-35, FRF-BD-19-002A]
  4. National Research Foundation of Korea (NRF) - Korea government (Ministry of Science and ICT) [NRF-2020R1A2C1005449]
  5. Zhejiang Natural Science Foundation [LD21F030001]

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This paper presents an event-triggered cluster consensus scheme for heterogeneous nonlinear second-order multiagent systems subject to cyber attacks and actuator faults. The proposed control scheme does not require the communication topology to satisfy the in-degree balance between different clusters, and an event-triggered mechanism is developed to save network resources and exclude Zeno behavior. Simulation results confirm the effectiveness and superiority of the proposed control scheme.
This paper presents an event-triggered cluster consensus scheme for heterogeneous nonlinear second-order multiagent systems (MASs) subject to cyber attacks (i.e., aperiodic denial-of-service (DoS) attacks), actuator faults and integral quadratic constraints (IQCs) under directed communication topology containing a directed spanning tree. Based on local communication, an event-triggered adaptive fault-tolerant pinning control scheme is designed to achieve cluster consensus under simultaneous cyber attacks and actuator faults. The proposed control scheme does not require the communication topology to satisfy the in-degree balance between different clusters. Furthermore, the fault-tolerant control part only needs to estimate one parameter for each agent. Instead of requiring continuous information on its neighbors to determine the trigger instants as in the previous literature, an event-triggered mechanism that does not require periodic sampling of neighbors' information is developed to save network resources, and the Zeno behavior is excluded. Finally, a simulation example confirms the effectiveness and superiority of the proposed control scheme.

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