## 1 Introduction  
Today, quadrotors have become popular in many application scenarios due to their high flexibility and high degrees of freedom, such as power inspection, data collection, surveillance and reconnaissance missions, forest fire rescue, and precision agriculture [1, 2, 3]. The quadrotor system is a typical underactuated system, which has the characteristics of nonlinearity, strong coupling, and susceptibility to interference, so it is difficult to establish an accurate mathematical model. A way to design a controller with high stability and strong robustness is a difficult research point. Due to the advantages of simple structure and easy implementation, linear controllers are widely used in quadrotor control systems. Research by [PERSON] et al. [4] presented that the Linear Quadratic Regulator (LQR) controller has a good control effect by analyzing and evaluating several different control schemes of the quadrotor. However, many scholars still try to use modern control methods to improve the control performance of quadrotor controllers, such as predictive control [5, 6], sliding film control [7], LQR [8, 9] and so on. Based on backstepping control and Lyapunov theory, research by [PERSON] et al. [10] presented a robust control algorithm in order to increase the endurance time of the quadrotor and reduce unnecessary energy dissipation. Research by [PERSON] et al. [11] presented a new type of quadrotor aircraft by adding a driving gimbal mechanism to provide multi-directional thrust. At the same time, a double closed-loop motion control scheme was proposed to enhance the robustness of the system. However, the above studies are all based on the nominal conditions of the quadrotor, that is, the influence of disturbance is ignored. This leads to the poor control effect of the controller designed in some scenes with large disturbances. The quadrotors are usually affected by external unknown wind disturbances and unmodeled dynamics within the system, which will lead to poor stability of the quadrotorsystem. Designing a robust controller to overcome the influence of disturbances to ensure the stability of the quadrotor system has always been a key topic for some scholars. For example, considering the uncertainty of system parameters, research by [PERSON] et al. [12] presented a control scheme combining neural network and adaptive control, and provided the simulation results. Based on the backstepping control theory, research by [PERSON] et al. [13] presented a nonlinear adaptive integral backstepping control algorithm. The simulation results prove that the controller still has strong robustness in the presence of wind disturbance. However, these studies did not address specific mathematical models of wind disturbance, nor did they explain how wind disturbance acts on the system. Nowadays, in order to solve the problem of unknown disturbance of the quadrotor system, many scholars have carried out in-depth research on the quadrotor control system based on the Active Disturbance Rejection Control (ADRC) theory. The ADRC does not require an accurate mathematical model of the controlled object, and its structure is simple, so it can be used in the controller design of a quadrotor system [14]. Aiming at the problem that the ADRC controller has many parameters, it is difficult to tune these parameters. Research by [PERSON] et al. [15] applied the fractional fuzzy particle swarm optimization (FOFPSO) algorithm to optimize the ADRC controller parameters, and it was compared with several other optimization algorithms to optimize the ADRC parameters. Finally, the authors propose a novel wind field model; this model is employed to prove the effectiveness of the controller under the action of wind disturbance. Research by [PERSON] and [PERSON] et al. [16; 17], aiming at the problem of grid voltage fluctuation in power grid systems such as wind power grid-connected inverters, proposed an improved LADRC controller to improve the disturbance observation accuracy of the system by reducing the phase lag of the observer.