Task-oriented Clustering Topology Control Algorithm for Heterogeneous Spacecraft Swarm

In this paper, the topology control problem of heterogeneous spacecraft swarms with parallel multi-missions is investigated, and a topology control algorithm based on a clustering hierarchical structure is proposed. According to the specific mission requirements, the spacecraft swarm is divided into several clusters by taking intra-cluster similarity and mission completion as the fitness factors, based on the improved particle swarm algorithm (PSO). Next, the node with the minimum weight (weighted sum of intra-cluster communication delay and intra-cluster average distance) within each cluster is defined as the cluster head. Then, the intra-cluster topology is determined by a tree search algorithm. In addition, a Hopfield neural network is introduced to further optimize the intra-cluster topology. Finally, the simulation results show that the proposed algorithm can well support the parallel multitasking requirements of spacecraft clusters.