Quadrotor UAV Motion Control and Rendezvous with Ground Moving Targets

As an underactuated system, quadrotor UAVs achieve six-degree-of-freedom motion control—including attitude adjustment and spatial positioning—solely through regulating the rotational speeds of four rotors. Due to their simple structure and superior performance, these drones demonstrate broad application prospects in military reconnaissance, logistics distribution, and disaster rescue operations.

For dynamic modeling, Newton-Euler equations accurately describe the UAV's position and attitude variations. By analyzing lift and torque generated by rotors, complete dynamic equations encompassing both translational and rotational motions can be established. However, the strong coupling characteristics of quadrotor systems pose control challenges, requiring well-designed control strategies for stable flight and precise trajectory tracking. In code implementation, the dynamics are typically represented using state-space equations with rotation matrix transformations for attitude representation.

For control solutions, PID controllers are commonly employed to regulate the four channels (pitch, roll, yaw, and altitude). PID parameter tuning is crucial for ensuring system response speed and stability—excessive gains may cause oscillations while insufficient gains compromise tracking accuracy. Building simulation models in Matlab/Simulink allows validation of control algorithms and parameter optimization for different mission requirements. The implementation typically involves separate PID loops for each control channel with cross-coupling compensation.

When achieving rendezvous with ground moving targets, the UAV must perceive target positions and velocities in real-time, adjusting its trajectory to ensure meeting at predetermined spatiotemporal points. This requires coordinated control of path planning and trajectory tracking. Simulation results demonstrate that PID-based control systems efficiently accomplish this task, achieving complex motion control through rotor speed adjustments alone, fully showcasing quadrotor UAVs' flexibility and practicality in dynamic environments. The rendezvous algorithm typically incorporates predictive filtering for target motion estimation and waypoint generation for interception paths.