## 1 Introduction  
In recent years, interest in small unmanned aerial vehicles (UAV) of the quadrotor or quadcopter types has been increasing among researchers due to their wide range of civilian and military applications, for instance, wildfire surveillance [1], search and rescue mission, and environment monitoring [2]. The quadrotor's main advantages are low cost, high maneuverability, small size, simple structure, vertical take-off and landing (VTOL), stationary flight, and low-speed flight [2, 3, 4]. However, with six degrees of freedom and only controlled by four inputs, quadrotors are considered an under-actuated mechanical system that brings complexity in its position and attitude control [5, 6, 7]. A good position and attitude controller are crucial to designing to control and stabilize such a complex system. First, a mathematical model of the system must be understood and formulated. Two formulas can be used to model the quadrotor system, Newton-Euler and Euler-Lagrange [8]. In control, extensive research has been undertaken for linear and non-linear control techniques applied to the system. Among them, we find proportional integral derivative (PID) [9, 10, 11], linear quadratic regulator (LQR) [12, 13, 14], backstepping control (BC) [15, 16], sliding mode control (SMC) [6, 17, 18], and many more. The most commonly used control technique and successfully implemented in the existing system is a PID con troller. The PID controller's popularity is due to its simple structure, being easy to design, and being easy to tune with satisfactory practical implementation performance [8]. A comparative study between PID, PD, and SMC controllers was conducted [18] for a V-tail quadrotor position control based on the robot manipulator theory. In this study, the quadrotor's dynamic equation based on Newton-Euler formulism was modified to suit the V-tail design. The simulation result found that the SMC controller has a faster stabilization time of approximately less than 3 s than the PD and PID controller. Nonetheless, it produces a big pitch and roll angle that exceeds 20\({}^{\circ}\), making it unfavorable in the real-world condition. In contrast, PD and PID controllers are only 3\({}^{\circ}\) which means the quadrotor can operate near a stationary state. In terms of steady-state error, the PID and SMC controllers can eliminate the error while the PD controller cannot increase it. Therefore, it can be concluded that the PID controller can stabilize the quadrotor and perform better than the PD and SMC controllers overall. [PERSON], [PERSON] [19] conducted a study of an optimal PID controller based on a Qball-X4 quadrotor developed by Quanser company as the experimental platform for trajectory tracking control. They designed a corresponding Kalman filter to estimate the target trajectory in consideration of tracking error and delays. The finding shows that the system can reach desired altitude height in an acceptable period without steady-state error but produce a high overshoot. The tracking error under the disturbance greatly improved when the Kalman filter was added. In another work by [PERSON], [PERSON] [20], the PID controller with an extended Kalman filter was used to control and stabilize the quadrotor's altitude and attitude angle. Extended Kalman filter was used to filter out the sensor noise and system noises to stabilize the quadrotor's altitude and attitude angle. In their findings, the controller can quickly stabilize the altitude of the quadrotor within 3.8 s. It can also work, handle disturbance very well, and promptly stabilize the quadrotor's attitude angle within 5.8 s.  
[PERSON], [PERSON] [21] presented a non-linear PID-type controller to guarantee the motion control of the quadrotor. The author provides an explicit tuning guideline for the proposed nonlinear PID-type scheme. The existence of gains is proven by using a Lyapunov-like analysis, where the quadrotor system's nonlinear dynamics are considered.