蜂群对抗决策故障下的容错博弈控制

针对大规模分簇蜂群无人机的任务分配问题，考虑对抗场景下某些无人机由于受到敌方攻击或操控，决策规则遭到篡改，进而导致群决策行为与期望的均衡点产生偏差的决策故障。在演化矩阵博弈的框架下，运用多群体复制子动态方程对蜂群无人机和故障建模，基于李雅普诺夫函数对故障发生前后均衡点的局部渐近稳定性及其吸引域进行了分析，从而建立了自容错条件，并设计了基于激励的簇间协同容错博弈控制方法，对群决策行为偏差进行补偿，使得蜂群任务分配状态在故障下仍能达到期望的均衡点，获得理想的分工收益。

Fault tolerant game control of swarm confrontation with decision faults

Some UAVs of the swarm are attacked or manipulated by the enemy in the confrontation scenario, and their decision-making rules are tampered to lead to a deviation between the swarm behaviors and the expected equilibrium. In the framework of the evolutionary matrix game, the equations for the multi- population replicator dynamics are used to model the UAV swarm and faults. Based on the Lyapunov functional approach, the local asymptotic stability of the equilibrium point as well as its domain of attraction is analyzed in both healthy and faulty cases. A self fault-tolerant condition is established. Moreover, an incentive based cooperative fault tolerant game control method between clusters is proposed to compensate for the deviation of swarm behaviors. With the method, the task allocation state of the UAV swarm can still reach the desired equilibrium point when there are faults, and the ideal payoff of the division of labor can be obtained.