## 1 Introduction  
Due to its high degree of freedom, strong flexibility, strong adaptability to complex terrain and low cost, quadrotor aircrafts are often used to carry out inspection, search and rescue missions in dangerous areas or complex terrain environments. These aircrafts are widely used in civil and military fields, such as surveillance and reconnaissance tasks in the military field [1, 2], as well as civil applications, such as electric power inspection, energy system inspection, bridge inspection, forest fire rescue and agricultural plant protection [3, 4, 5]. However, the quadrotor aircraft is a nonlinear, underactuation and strongly coupled system, and it is difficult to establish an accurate system model [6]. How to design a controller with high stability and strong robustness according to the system characteristics of quadrotor aircraft is a difficult point in research. The Proportional-Integral-Derivative (PID) controller is widely used in the control system of the quadrotor due to its simple structure and easy implementation. In the control application of quadrotor UAV, it is proved that the PID controller with proper design and tuning has good robustness and performance among the other types of controllers [7, 8, 9]. Nevertheless, many scholars still try to apply modern control methods to improve the control performance of quadrotor aircrafts, such as an LQR controller [10, 11], sliding mode controller [12], model predictive controller [13, 14], robust controller [15] and so on. In order to solve the unknown disturbance problem of quadrotors in flight, many researchers have studied the control system of quadrotors based on ADRC theory. In order to enhance the disturbance rejection ability of the attitude control of a quadrotor Unmanned Aerial Vehicle (UAV), an ADRC based on a quadrotor UAV has been designed in the literature [16; 17]. In the literature [18], attitude control is investigated for a quadrotor subjected to wind disturbances, and a double closed-loop control strategy, which integrates the advantages of ADRC and integral sliding mode control, is presented. The literature [19] presents an original approach to the design of a complete digital attitude control unit for a quadrotor UAV based on the framework of ADRC and Embedded Model Control (EMC). Although ADRC has proved many advantages in theory, in engineering practice, ADRC needs to adjust more parameters than the PID controller, and the parameters affect each other, which brings great obstacles to the practical engineering application of ADRC. Therefore, many scholars are committed to solving the problem of ADRC with too many adjustable parameters, aiming to make the tuning of ADRC parameters more convenient and greatly promote the application of ADRC in engineering practice. In the literature [20], an adaptive genetic algorithm-particle swarm optimization (AGA-PSO) is used to optimize the controller parameters to solve the problem that the controller parameters are difficult to tune. Additionally, the performance of the proposed ADRC and sliding mode controller (SMC) is compared. The simulations revealed that the dynamic performance and robustness of the ADRC is better than that of the SMC. In the literature [21], the chaotic grey wolf optimization (CGWO) algorithm is developed with chaotic initialization and chaotic search to obtain the optimal parameters of attitude and position controllers. Considering the difficulty of the parameter tuning of ADRC as well as the requirement of accuracy and rapidity of the controller, a Multi-Strategy Pigeon-Inspired Optimization (MSPIO) algorithm is employed in the literature [22]. The literature [23] presents a parameter tuning method based on the genetic algorithm (GA) for an ADRC of a three-axis inertially stabilized platform (ISP) with imaging sensors. The results show that the proposed ADRC with a GA-based parameter tuning method has significant disturbance rejection ability, which can improve the stabilization accuracy.