The formation of a heterogeneous unmanned aerial vehicle ( UAV) swarm cooperative combat coalition under dynamic,unknown or contested conditions is a crucial aspect of practical UAV swarm operations. A decision control process framework for UAV swarm based on the dynamic consensus-based grouping algorithm ( DCBGA) is constructed. A communication networking model with communication constraints is designed for UAV swarm,and a dynamic adaptive mechanism is introduced to effectively cope with high dynamic task scenarios. Based on the"operation loop"theory,the aggregation effect of non-linear combat effectiveness of heterogeneous units under the network architecture is described,and included in the global performance function to guide the formation of the heterogeneous UAV cooperative combat coalition. The coalition formation process is divided into three stages:target selection,consensus,and information and state update. The dynamic consensus-based grouping algorithm is used to support the UAV swarm in completing the information decision control of each stage from the bottom up. Simulated results show that the proposed algorithm system can effectively promote the heterogeneous UAV swarms to realize the formation of combat coalitions and complete the coordinated combat missions,demonstrating good dynamic adaptability and scalability,and exhibiting better resilience in contested environments.
维普
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