RESEARCH ON UNMANNED CLUSTER RECONNECTION DECISION-MAKING METHOD CONSIDERING RESOURCE SUPPLEMENTATION

In recent years, with the widespread application, intelligence, and increasing complexity of task scenarios of unmanned cluster systems in various fields, the system capability of clusters has become increasingly dynamic and flexible. It is not only related to the state of individuals but also to the reconnection patterns of clusters. Consequently, the capability can be reversibly enhanced through structural adjustments or resource replenishment in the system. Therefore, addressing the issue of how to make decisions on resource replenishment methods to efficiently and reasonably utilize resources, and thereby ensuring the high reliability operation of unmanned clusters, this paper focuses on the unmanned aerial vehicle (UAV) cluster system in open environments. It analyzes the available states of unmanned clusters under conditions of no reconnection, reconnection, and resource replenishment, and proposes methods for decision optimization of cluster resource replenishment based on degree-preferred connections and particle swarm algorithm. This provides a systematic approach to solving the problems of replenishment, scale changes, and decision optimization of unmanned cluster resources.