Stall-Induced Nonlinear Vibration and Aeroservoelasticity Control of UAV Rotor Blades

Unmanned aerial vehicles (UAVs) are widely used in the civilian field. However, structural dynamics issues, especially the nonlinear vibration of UAV blades, remain a key bottleneck that limits their operational reliability, dynamic stability, and mission load performance. This study focuses on the vibration generated by a special and highly destructive stall-induced nonlinear (SIN) aerodynamic excitation under downburst weather, as well as its control methods and data monitoring. Starting from structural improvement and structural modeling, and incorporating nonlinear aerodynamic forces, an aeroelastic system equation for reconnaissance quadcopter blades was established. The structural improvement was based on a swing hydraulic cylinder (SHC) and the implementation of small-angle pitch control. The structural modeling and aeroelastic system integrate composite structural damping to enable the description of coupling effects, and artificial damping is considered to analyze flutter wind speed. And based on a deep reinforcement learning (DRL) proportional–integral (PI) controller, the aeroservoelasticity control and response analysis are described in detail. In the DRL-PI control process, the Twin Delayed DDPG (TD3) algorithm was deeply analyzed; the network structure, PI parameter adjustment mechanism, and standard control system diagram were integrated and logically reorganized; and the output results were visualized. Meanwhile, this study elaborates in detail on the interaction between mechanical vibration and onboard electronic equipment, using a 5.8 G microwave communication link to achieve remote sensing signal feedback for medium-to-low (MtL)-altitude UAVs, with a focus on UAV telemetry signals, remote downlink monitoring (RDM), and ground station signal reception. Finally, practical and feasible suggestions are provided for future research directions.