## 1 Introduction  
Due to the advantages of long endurance, fast flight, and high energy availability, fixed-wing unmanned aerial vehicles (FWUAVs) have become increasingly attractive in many areas, such as reconnaissance, patrol inspection, and monitoring. When executing missions, FWUAVs are required to follow a prescribed reference path. The mission execution effect relies on the path-following control performance, making the design of the path-following control system important with engineering significance. Path-following errors are adjusted via attitude angles. According to the path-following errors, the mass center position controller generates the desired attitude angles, which are regarded as the references for the attitude controller so that the control surface deflection angles as well as the control laws of FWUAVs can be derived. In the MCPC, establishing a motion model is quite important. By considering aerodynamic complexities, variable couplings, fast time variations, and high nonlinearities, the geometric approach and control technique are mainly applied for model establishment. The two approaches have the advantages of a simple model structure and irrelevant model information, such that their superiority is obvious when compared with conventional modeling methods [1]. The commonly utilized geometric approaches include the line-of-sight (LOS) [2; 3; 4; 5; 6; 7], vector field [8; 9; 10; 11; 12; 13; 14], virtual target following [15; 16; 17; 18; 19; 20; 21], and L\({}_{1}\) guidance approaches [22; 23; 24; 25; 26; 27; 28]. Analytical solutions of the desired attitude angles or body rates regarded as reference signals can be derived through the relationships among the path-following errors, the current flow angles, and the current attitude angles. Being different from the geometric approach, the control technique assumes that there is a virtual target point attached to the prescribed reference path. A natural frame also named the Frenet frame [21; 29; 30; 31; 32], whose origin coincides with the virtual target point, is established; in this case, the Frenet frame overlaps with the body frame if the FWUAV can strictly follow the path. In the control technique, path-following error kinematic models whose inputs are the error angles (also called error attitude angles) between the Frenet frame and the body frame are built without using any plant model information. The advantages of the control technique are that the error attitude angles can be designed through different control theories, such as L\({}_{1}\) adaptive control [33], L\({}_{1}\) state feedback control [34], nested saturation control [35], linear model-based predictive control [36], optimal control [37], and nonlinear model predictive control [38], and that the approach has been studied widely. By considering that FWUAVs are easily influenced via external wind fields, approaches such as a new guidance law combined with pure pursuit and the LOS [39], a VTP-based nonlinear guidance law [15], optimal control with the wind amplitude available [16], feedback control with wind estimation and compensation [37], and adaptive backstepping control [40] have been presented. However, the existing path-following control schemes are incomplete since they mainly focus on the establishment of a path-following error kinematic model and the design of mass center position controllers. Once the desired attitude angles/body rates have been obtained, the studies are ceased, meaning that the design of the attitude controllers is ignored and that the final deflection laws of the control surfaces actually used to steer the FWUAVs are not given. It is well known that attitude control plays a decisive role not only in path-following control but also in the field of flight control. Hence, the design of an attitude control system and control performance enhancement cannot be ignored. To address these problems, targeting the movement of FWUAVs on the latitude plane, a robust path-following control approach is presented in this paper.