Fuzzy Adaptive Linear Active Disturbance Rejection Control for Quadrotor Load UAV Based on Kalman Filter

In order to solve the problem of load variation and nonlinear strong coupling of the quadrotor load unmanned aerial vehicle (UAV), this paper proposes a fuzzy adaptive linear active disturbance rejection control algorithm based on the Kalman filter (KFFA-LADRC). Firstly, according to the established dynamics model of the quadrotor load UAV, the linear extended state observer (LESO) and the controller based on the bandwidth method are designed. Secondly, to enhance the system’s adaptability and robustness, a real-time fuzzy adaptive controller is introduced to dynamically adjust the controller parameters. Furthermore, to tackle uncertainties disturbances arising from sensor noise and unknown external disturbances, the Kalman filter is utilized to predict the output state, thereby providing the optimal estimation input for the LESO. The approach not only achieves stable control of internal interference, but also reduces the dependence of the Kalman filter on the mathematical model. Finally, simulation results substantiate the efficacy of the proposed KFFA-LADRC, highlighting its robustness and adaptability when accommodating variations in load mass, sensor noise, and external interferences within unfamiliar environments.