Abstract
To address the requirements for multi-channel decoupling and high-precision control in quadrotor UAV systems, this paper proposes a novel intelligent controller (TD3-ADRC) which integrates Active Disturbance Rejection Control (ADRC) with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Firstly, the dynamic model of the quadrotor is established. Secondly, a parameterized tanh function is introduced and applied to design the tracking differentiator, extended state observer, and nonlinear feedback control law. Then, the TD3 learning mechanism is incorporated to automatically learn and optimize controller parameters, thereby significantly enhancing the system’s disturbance rejection capability. Finally, simulation studies comparing conventional PID, ADRC, DDPG and the proposed TD3-ADRC algorithms are conducted in Simulink. In addition, a bench test system is developed using the PX4 flight controller. Experimental results show that, under complex environmental conditions, the proposed TD3-ADRC controller outperforms both conventional PID and linear ADRC methods in terms of reliability and adaptability, validating the effectiveness of the proposed control approach.