Reinforcement Learning Algorithm for UAV Control Based on Communication Control Transmission Rate

In order to solve the problem that terahertz communication beams are difficult to align and track in highspeed motion scenarios, this paper designs a UAV control algorithm based on communication control transmission rate under cellular-assisted motion control for UAV-assisted terahertz communication scenarios, which is an event-triggered control algorithm. The control stability of the scheme proposed in this paper is proved by the analysis, and the results show that the system designed in this paper is mean square stable. Finally, the scheme in this paper is simulated and analyzed. The results show that the designed UAV control algorithm scheme based on communication control fusion has good effectiveness compared with the traditional periodic control scheme while ensuring excellent communication performance and control stability. It reduces the time, resource overhead and transmission power loss of the system.