## 1 Introduction
The nonlinear flight control system shown in Figure 1 highlights the sequence of generating physical control surface commands starting with a predefined path, followed by generating the desired guidance command. The control law is designed based on the two-timescale separation concept, which is discussed in the following [17]. For decades, automatic control occupies increasingly a significant place in aeronautics; many works discuss various aspects related to the control systems automation. The purpose of the controller is to ensure that the output closely tracks the input while optimizing the controller parameters for achieving the best performance, focusing on the responsibilities of the controller to calculate the control commands while keeping the system overshoot, settling time, and steady-state error within defined design margins based on the system requirements. In addition, to meet increasing demands on performance and reliability of UAVs, nonlinear control techniques are often utilized. These techniques are actively being studied to handle nonlinear aerodynamics and kinematic effects, actuator saturation, rate limitations, modeling uncertainty, and time-varying dynamics [6]. Typical linear flight control systems are designed based on linear design models that capture the approximate motion of the system under specific scenarios. [PERSON] [11] assumed the longitudinal  
Figure 1: Nonlinear flight control system. dynamics are decoupled from the lateral-directional dynamics and utilized successive loop closure. However, a problem of this approach is that good performance and robustness properties cannot be guaranteed for a highly nonlinear fighter aircraft. Moreover, there are many hard nonlinearities such as saturation, dead-zones, and backlash whose discontinuous nature does not allow linear approximation, hence cannot be analyzed using linear analysis tools. Nonlinear control methods have been developed to overcome the shortcomings of linear design approaches. NLDI approach is one of the best known and has been used successfully to address some practical control problems, as it is based on algebraically transforming a nonlinear system dynamic into a fully or partly linear one so that linear control techniques can be applied. It differs from the conventional linearization using Jacobian technique [18], which is achieved by exact state transformation and feedback under the assumption of a correct onboard dynamic model, instead of a linear approximation of the dynamics around trim points [17]. However, there are also a number of important shortcomings and limitations associated with NLDI approach as it is model-dependent flight controller [17; 19]. In aircraft flight control, the aerodynamic forces and moments acting on the aircraft are important sources of nonlinearity to be dealt with. In practice, these cannot be modeled exactly and, hence, perfect cancellation is not possible. Consequently, it still has fatal limitations associated with the exact states feedback linearization especially in the case of unmodeled dynamics and parameter uncertainties. Unfortunately, the accurate knowledge of the nonlinear system dynamics is unavailable, which degrades the robustness of the designed controller using NLDI, as it is sensitive to any small perturbations in the system model. Consequently, a modification on the NLDI is required to degrade the model dependency of the flight controller. Based on the literature, a robust UAV flight control methodology is still required to track a severe acute maneuver command with the existence of external disturbance and model uncertainties. For this objective, the main contribution of the current research is to design a fully autonomous guidance and control algorithm by combining simple geometric path following guidance law and a modified NLDI flight controller in one control algorithm. The key contributions of this paper are summarized as follows:  
1. Feedback linearization approach is employed to achieve the best UAV maneuvers.