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

Abstract

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 system adaptability and robustness, a real-time fuzzy adaptive controller is introduced to dynamically adjust the controller parameters. Furthermore, to tackle uncertainty disturbances arising from sensor noise and unknown external disturbances, the Kalman filter is employed to predict the output state, which provides the optimal estimation input for the LESO. The approach not only realizes the 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 in accommodating variations in load mass, sensor noise, and external interferences within unfamiliar environments.

UAV Multi-Dynamic Target Interception: A Hybrid Intelligent Method Using Deep Reinforcement Learning and Fuzzy Logic

“…The UAV platform selected in this paper for both ownship and intruder aircraft is the "+" type quadrotor, assumed to be center symmetric. Although this study employs a model-free SAC method, meaning the algorithm learns the optimal policy through interaction with the environment without relying on a predefined dynamic model of the environment, understanding the UAV model (including both dynamic and kinematic models) as referenced from [45,46] is still beneficial for effective training and control, as it provides critical physical constraints. Based on the rotation matrix, the dynamic model equations of this type of quadrotor are as shown in Equation (1).…”