The application provides a task energy efficiency optimization-oriented unmanned aerial vehicle dynamic position deployment control method and device, and relates to the technical field of unmanned aerial vehicle
communication control.The application constructs an unmanned aerial vehicle
mobile edge computing system model, collects a current environment state at each discrete
time step to generate a local observation vector, and generates a deterministic action vector; then, a distributed
matching game with a ground
mobile device is performed to complete task association; then, position updating is performed, a multi-target reward function is calculated, and centralized
network model training is performed to iteratively update a Critic evaluation network and an Actor strategy network; when the model training reaches a preset requirement, the training is terminated, and a task energy efficiency optimal unmanned aerial vehicle dynamic position deployment control strategy is obtained. The application can realize deep
coupling optimization of physical trajectories and offloading decisions, effectively solve user association conflicts and uneven computing load problems in a dynamic scene, and significantly improve
system comprehensive energy efficiency while guaranteeing
service quality.