This chapter details an event-triggered approach to achieving cluster consensusCluster consensus in heterogeneous nonlinear second-order multi-agent systems (MASs) that are susceptible to cyber attacks (aperiodic denial-of-service (DoS) attacks), actuator faults, and IQCs, all within a directed communication structure that has a directed spanning tree. The event-triggered adaptive fault-tolerantFault-tolerant pinning control strategy is designed to reach cluster consensusCluster consensus through local communication, despite concurrent cyber attacks and actuator faults. This scheme operates without the need for a communication topology that maintains in-degree balance among different clusters. Moreover, the fault-tolerantFault-tolerant controller only necessitates the estimation of one parameter per agent. Unlike the need for continuous overall information about MASs to set trigger instants as discussed in Chap.  9 , this chapter develops an event-triggered mechanism (ETM) that dispenses with the need for periodic neighbor information sampling, thus conserving network resources. In addition, the Zeno behaviorZeno behavior is excluded.

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Fault-Tolerant Cluster Consensus of MASs Under Aperiodic DoS Attacks

  • Xiang-Gui Guo,
  • Pei-Ming Liu,
  • Dong-Yu Zhang,
  • Jian-Liang Wang,
  • Lei Guo

摘要

This chapter details an event-triggered approach to achieving cluster consensusCluster consensus in heterogeneous nonlinear second-order multi-agent systems (MASs) that are susceptible to cyber attacks (aperiodic denial-of-service (DoS) attacks), actuator faults, and IQCs, all within a directed communication structure that has a directed spanning tree. The event-triggered adaptive fault-tolerantFault-tolerant pinning control strategy is designed to reach cluster consensusCluster consensus through local communication, despite concurrent cyber attacks and actuator faults. This scheme operates without the need for a communication topology that maintains in-degree balance among different clusters. Moreover, the fault-tolerantFault-tolerant controller only necessitates the estimation of one parameter per agent. Unlike the need for continuous overall information about MASs to set trigger instants as discussed in Chap.  9 , this chapter develops an event-triggered mechanism (ETM) that dispenses with the need for periodic neighbor information sampling, thus conserving network resources. In addition, the Zeno behaviorZeno behavior is excluded.