# Research and Verification of Trajectory Tracking Control of a Quadrotor Carrying a Load
## 1 Introduction
Similarly, the literature does not consider the wind disturbances usually encountered during quadrotor flight. In [15], the authors use a downward camera to observe the load and use an extended Kalman filter method to estimate its state relative to the quadrotor for the first time to realize the flexible maneuverability of the lifting load and the closed-loop control of the maximum load angle. Regrettably, the literature does not verify the effectiveness of the algorithm under wind field disturbance. In [16], the authors linearize and decouple the quadrotor model at the hovering point to generate four subsystem models, which are linear. An improved adaptive L1 control method and a self-disturbance suppression linear controller are proposed. This method is very effective for interference suppression, but the suppression effect for the swing angle is not good enough. At the same time, it is too simplified for the model of the quadrotor carrying a load. In [17], two ways of transporting load with quadrotor, namely, grab and rope hanging, are studied, and different control methods and maneuvering strategies are analyzed. From the literature, there are two advantages of rope hanging. The first is that there is no requirement for the shape of the load, and there is no mismatch between the quadrotor and the load. The second is that the quadrotor can hover at a fixed point to facilitate the loading and unloading of the load. In [18], the authors use a new type of passive flexible grasping structure and servo positioning control, combined with detection algorithms, which can make the micro-air vehicle grasp and transport loads with different shapes and weights. However, the load cannot be too heavy during crawling, and the adjustment parameters of the algorithm are too complicated. In [19], the quadrotor robot transports the quadrotor robot with the load at an acceleration exceeding the ability of the previous collaborative method, but there is no clear communication between the collaborative robots. They rely entirely on visual cues and inertia obtained from airborne sensors. So, the airborne sensor will be interfered with and lose its function in the case of the mixed and complex interference of the wind field and the magnetic field. In [20], the authors show that the PID-controlled helicopter refuses to increase the load within the allowable load range and adjusts the period to simulate dominance. This means the load is only allowed to be placed once, and PID tuning is relatively slow. The control of the trajectory tracking of a quadrotor carrying a load has been widely and deeply researched both at home and abroad. However, considering the uncertainty of the model parameters, the unknown time-varying wind field magnetic field perturbation under the actual working conditions and the need to combine specific engineering practices to achieve load swing suppression and accurate trajectory tracking, the research on quadrotors carrying load suspensions combining all the above points is relatively less. Therefore, on the basis of summarizing the research results of the predecessors on the quadrotor carrying a load [21; 22; 23; 24; 25; 26; 27; 28; 29] and the algorithms involved in the article [30; 31], combined with our team's non-linear control of the quadrotor [12; 32; 33], a neural network control algorithm based on adaptive integral backstepping trajectory tracking is proposed to solve the complex and variable wind field and the disturbance problem caused by unmodeled dynamics. The contributions of this paper are the following: In Section 1, the current status of research on a quadrotor carrying a load and its algorithm is described, and the previous research results and their shortcomings are summarized, which leads to the problem addressed in this paper. In Section 2, the quadrotor and its load are treated as a whole system for force analysis, and the mathematical model of the coupled quadrotor carrying a load with eight degrees of freedom is established.