# Simulation of a Quadrotor under Linear Active Disturbance Rejection
## 1 Introduction  
In recent years, quadrotors have had broad application value in military strategy [1], disaster rescue [2], tracking and shooting [3], monitoring and reconnaissance [4], etc. Replacing manual execution of dangerous tasks in an environment can minimize casualties [5] and bring breakthrough and subversive product innovations to the military and civilian fields and makes UAS technology more secure and reliable [6]. When a quadrotor takes off in harsh environments or offshore platforms, due to external disturbances such as wind, rain and air friction, it may not take off horizontally after being disturbed. Landing [7], if it is forced to take off in a disturbed attitude, the quadrotor will be out of control during the flight, which will affect the tasks performed and people's property safety [8]. Up to now, the control schemes of quadrotors mainly include: PID control [9], LQR control [10], sliding mode control [11], LADRC [12], neural network [13] and adaptive control [13]. The mainstream control algorithm of quadrotors is undoubtedly PID control [14]. Although PID control can make the quadrotor fly smoothly, it can only maintain stability in the state of small interference, and the ability to handle interference is limited,as the robustness of the control system is not strong. On the basis of PID control, Professor [PERSON] improved it into an ADRC. In the literature [15], a quadrotor control scheme based on LADRC was proposed. LESO can quickly estimate the real\(-\)time error; the anti\(-\)interference performance of LADRC is more accurate and reliable than PID control, but it needs to adjust too many parameters. In the literature [16; 17], it is proposed to combine adaptive control and a neural network, and an adaptive compensation scheme based on a neural network is proposed, but it has obvious control deviation and is not robust; low\(-\)order LADRC can deal with relatively complex high order power systems [18; 19] and combustion oscillation processes [20]. The literature [21] proposes a new NMP ADRC control scheme, which solves the conflict between stability and feedback adjustment from an engineering point of view. For the quadrotor, we hope that its control system can quickly identify and eliminate external interference, so as to take off smoothly and safely when it is not on a horizontal plane or is subjected to strong interference. Therefore, in combination with the advantages and disadvantages of the above control schemes, this paper adopts adaptive control to optimize the parameters of LADRC and enhance the control performance of PD controllers. The neural network approaches the nonlinear control function with its unique characteristics and designs a quadrotor with simple tuning, stronger robustness and full attitude taking off. The innovation points of this paper are shown as follows:  
Firstly, this paper proposes an Adaptive Law - Based LADRC (AP\(-\)ADRC) and Robust Control\(-\)Based LADRC (RBF\(-\)ADRC) control system with independent an AP\(-\)ADRC control on each position control channel, and an independent RBF\(-\)ADRC control on each attitude control channel is controlled by an independent RBF\(-\)ADRC on each attitude control channel. The results show that the proposed scheme is effective and can achieve fast and stable tracking of the reference input with good robustness. Secondly, this paper optimizes the classical LADRC on the basis of this and designs a linear self\(-\)adaptive control strategy based on adaptive rate for the problem that the linear self\(-\)adaptive control system of the quadrotor has low tracking accuracy and the parameters are difficult to adjust online.