基于元胞自动机的蜂群无人机故障影响模型

Fault influence model of swarm UAVs based on cellular automata

基于固定翼无人机飞行特性以及蜂群无人机控制策略,针对无人机控制器遭受恶意攻击的情形,采用时序网络与元胞自动机理论分析蜂群无人机故障影响机理.首先,通过时序网络分析蜂群无人机拓扑网络的变化情况,提出基于跳数的故障传播路径的确定方法;其次,考虑蜂群无人机状态信息,建立符合蜂群无人机特征的元胞对象,同时基于局部信息交互原则,确定元胞自动机的状态演变规则,并依据近邻信息对无人机控制律的影响,提出矢量投影法来确定故障影响权值,辨识出各无人机故障影响程度的动态变化情况;最后,建立仿真模型,利用预测与实际故障影响程度结果,基于DCG算法与模式距离验证所建故障影响模型的有效性.

Based on the flight characteristics and the control strategy of UAVs with fixed wings,the temporal network and the cellular automata theory are used to analyze the failure influence mechanism of the swarm UAV in the case of malicious attack to controllers.Firstly,the change of the topology network of the swarm UAV is studied by the temporal network,and a method based on hop number is then proposed to determine the fault propagation path.Secondly,utilizing the status information of the swarm UAV,the cellular object that satisfies the characteristics of the swarm UAVs is established.Based on the principle of local information interaction,the state conversion rules are determined so that the dynamic change of the influence degree of UAVs failure can be identified,by which the weights of failure influence are determined using the vector projection method according to the influence of the neighbour information on the control law of a UAV.Finally,after building a simulation model,the prediction results compared with the actual fault influence degree are obtained via the DCG algorithm and model distance,which verifies the effectiveness of the proposed fault influence model.