# Quadrotor Cascade Control System Design Based on Linear Active Disturbance Rejection Control
###### Abstract  
In this paper, we propose a cascade control system design based on linear active disturbance rejection control (SMC&A-LABRC) to address the following quadrotor UAV problems: that the path is easily yawed when disturbed, the control parameters are difficult to optimize, and the tracking accuracy is low. The strategy can effectively eliminate external disturbances and adjust the controller parameters online so that the quadrotor UAV always flies on the optimal path to achieve energy optimization and long-endurance flight. The proposed cascade control system combines the advantages of sliding mode control (SMC) and linear active-disturbance rejection control (LABRC), using the linear extended state observer (LESO) to estimate the uncertain external disturbances and unmodeled internal dynamics of the quadrotor system, compensate for the uncertain signals under SMC chattering, optimize the PD controller parameters online using adaptive control to eliminate the effects of parameter deviations, and simplify the parameter adjustment process. Finally, a stability analysis of the quadrotor cascade control system is carried out by using the Lyapunov theorem of stability, and a simulation analysis is carried out using MATLAB to compare the results with those obtained with classical LADRC. The test results indicate that the control strategy of this paper is reasonable for utilization with a quadrotor attitude and displacement control system, allowing the quadrotor to fly on the optimal path with good anti-interference ability and a fast response speed. L +
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models. Reference [16] proposed a controller parameter that uses a multi-objective particle swarm optimization (PSO) algorithm to improve PID performance and adjusts the PID online to solve the problems of system instability, slow response, and error tracking due to parameter deviations. In reference [17], a novel adaptive neural network-based controller was proposed that does not require knowledge of the system parameters and achieves online updating of the output weight matrix, which can effectively eliminate the bias caused by the parameter uncertainty of the inner loop. Reference [18] proposed an adaptive fuzzy tracking control scheme, which applies a nonlinear disturbance observer to compensate for the external disturbances and the approximation error of the fuzzy logic system, and in most cases, adaptive control is mostly applied to identify the quadrotor dynamics and external disturbances online or to design robust controllers in combination with other control techniques [19]. The LQR controller [20] is able to track the desired position and attitude trajectory and the spiral trajectory well, and this strategy is able to compensate for the effect of the load on the control system dynamics. LADRC [21] has a good tracking capability and anti-interference capability, and can treat external disturbances as well as internal uncertainties as a total disturbance by LESO and compensate for them with a PD controller, but it has too many adjustment parameters and a limited ability to handle external disturbances. Reference [22] proposed a modified terminal-sliding mode controller, which is a strategy with a time-varying delayed output observer that allows the quadrotor UAV to operate smoothly for a limited period of time. In references [23; 24], an improved LADRC controller was proposed to improve the dynamic capability of the distribution network under various grid defect scenarios. In summary, conventional control methods are subject to internal uncertainties, unmodeled parts, and external nonlinear disturbances that can lead to poor control performance and make it difficult to design controllers due to the complexity of the quadrotor itself.