Unmanned aerial vehicles (UAVs) equipped with communication devices are easy to deploy and can serve as temporary mobile communication stations, covering dynamic ground users and establishing communication links. The proper planning of UAV paths can improve user coverage while maintaining communication quality. The traditional particle swarm optimization (PSO) algorithm exhibits strong global search capabilities; however, it suffers from challenges such as uneven search coverage owing to the random distribution of the initial particle positions. Additionally, improper parameter selection often leads to premature convergence to local optima. This study proposes a method for multi-UAV coverage of dynamic users by combining Tent chaotic mapping with PSO (Tent–PSO). By using Tent chaotic mapping to adjust a UAV’s speed and position, the method ensures that particles are evenly distributed in the search space. Simulation results demonstrate that Tent–PSO improves the coverage of the global optimal solution by 10% and increases throughput by at least 37%, confirming its effectiveness in covering dynamic user scenarios.