# A Robust Fixed-Time Sliding Mode Control for Quadrotor UAV
## 1 Introduction  
UAVs (Unmanned Aerial Vehicles), also known as drones, have revolutionized the way in which various operations are carried out in different fields of industry. The ability of UAVs to fly at high altitudes and in hard-to-reach areas, combined with advanced sensor and camera technologies, allows inspection and surveillance tasks to be carried out with greater precision and safety [1; 2]. In the field of precision agriculture, UAVs can be used to obtain detailed information on crop conditions, enabling more efficient land and water management [3; 4]. Moreover, UAVs are also used to create detailed maps of specific terrains and geographical areas, which is of great help in activities such as infrastructure planning and natural resource management [5; 6]. In natural disaster situations, UAVs can be used to carry out rapid and accurate assessments of damage and the needs of affected communities [7]. Furthermore, in the field of air transport of payloads, UAVs offer an economical and safe alternative for the delivery of supplies and materials to remote or inaccessible areas. In addition, the versatility and efficiency of UAVs make them indispensable tools in various areas of industry and society [8; 9; 10; 11]. The following are just a few examples. Proportional-Integral-Derivative (PID) control is a control technique commonly used in industry. Its implementation requires several iterative tunings of its parameters. In a recent study [12], a nonlinear PID controller for total thrust and torques applied to follow a desired trajectory of the Quadrotor aircraft was proposed. This robust controller is highly adaptable to different types of UAVs and offers a promising approach for controlling aerial vehicles that require fast, accurate, and robust responses in challenging and dynamic situations. On the other hand, the work in [13] compared the tracking capability of three different controllers in the design of a flight controller for a V-tail Quadrotor aircraft. The controllers compared were proportional derivative (PD), PID and sliding mode controller (SMC). According to their simulation results, the PD controller presented a steady-state error that was not corrected, which could be problematic in applications requiring high precision. In contrast, the SMC allowed the Quadrotor aircraft to quickly converge to the desired point. In this context, controllers based on sliding modes present an inherent phenomenon called chattering, which is a problem for engineers because it wears out and reduces the useful life of the actuators in a given process [14]. This effect is characterized by rapid oscillations and high frequency in the control signal. In addition, this phenomenon cancause problems in the operation of the system, such as noise high-frequency generation and wear on mechanical components, as well as degradation of the accuracy of the system response in some cases. For this reason, chattering has been studied to find solutions to reduce this effect. Among the solutions proposed to reduce chattering in sliding mode control systems are the use of filtering techniques, the implementation of soft control laws, the modification of the controller gain and the design of adaptive control algorithms. These solutions have proven to be effective in reducing chattering and improving control system performance [15]. In the case of UAVs, chattering can be especially critical because these systems often operate in variable conditions and dynamic environments. Therefore, it is important to consider effective solutions to reduce chattering in UAV control systems, which can improve the navigation accuracy and energy efficiency of the system. Therefore, this research focuses on one of the controls that have been investigated in the literature to improve the accuracy and robustness of flight control for UAVs. In reference [16], an SMC approach based on a fixed-time disturbance observer is proposed to improve flight control in the presence of external disturbances.