## 1 Introduction  
In past decades, aircraft design has been changed radically in the aviation industry. As the conventional aircraft cannot meet our requirement for a higher lift-to-drag (L/D) ratio, higher payload carrying capacity and more excellent stealth effect, etc., lifting body/blended wing body (BWB) becomes a potential solution to bridge the gaps. A lifting body is an aerial vehicle that chiefly, even solely, produces lift in the body [1], which is always designed as a unique tailless single entity where the fuselage is merged with the wings. Since such aircrafts cancel the vertical tail and typical rudders, several kinds of innovative control effectors (ICEs) are introduced to improve the aerodynamic efficiency and manoeuvrability, such as leading-edge flaps (LEFs), split drag rudders (SDRs) and spoiler-slot-deflectors (SSDs) [2], etc. Motivated by the aforementioned design philosophy, more and more lifting bodies/BWBs such as M2-F3, HL-20, X-24B, BWB-450, etc. (_see also in_[3]) have been developed successively. The saucer-shaped unmanned aerial vehicle (UAV) studied in this paper is also derived from the same design concept. However, BWB aircrafts suffer from disadvantages such as the high nonlinearity, strong interactions and coupling effects between control effectors (which is difficult for modelling) as well as serious parameter uncertainties. Moreover, during actual flight, the existence of gust wind and turbulence needs to be taken into consideration, which also brings challenges to controller design. Until now, abundant approaches have been proposed by worldwide researchers. Most of the approaches are related to advanced, nonlinear methodologies, such as nonlinear model predictive controller (NMPC) [4], trajectory linearization control (TLC) [5; 6] and sliding mode control (SMC) [7], to name a few. An improved \(H\infty\) robust controller is established to handle the coupling effects considering longitudinal turbulence in [8]. By addressing stability control in the presence of disturbances, a finite time convergence sliding mode control scheme is developed in the linear parameter-varying model of the aircraft [9]. However, the methods mentioned above are either inherently model-dependent with computational concerns or only insensitive to the matched disturbance. It is noted that both matched and mismatched disturbances/uncertainties should be considered for the flight control system design, as it is inevitable that the un-modelled coupling effect uncertainty and external disturbance would arise in different channels as the control input. To estimate and suppress the mismatched disturbances/uncertainties, some effective techniques have been investigated including disturbance observer (DO)-based SMC method in [10; 11], the Riccati approach combined with SMC in [12] and active disturbance rejection control (ADRC) in [13; 14]. However, most of these approaches require that the disturbances \(d(t)\) satisfy \(\lim\limits_{x\to\infty}\dot{d}(t)=0\), which is so-called \"mismatched vanishing disturbances\", or the accurate expressions of the mismatched uncertain terms were assumed to be known in [13; 14]. The backstepping technique is a powerful tool for nonlinear systematic design in the presence of mismatched uncertainties. Since the core of this method is to design a controller recursively by considering some of the state variables as \"virtual controls\" and by designing for their intermediate control laws, the \"backward steps\" can accommodate the uncertainties missing the matching conditions. A composite anti-disturbance controller [15] is synthesized by introducing disturbance estimations into the design of virtual control laws to compensate for mismatched disturbances with partial known information. [PERSON] et al. [16] proposed a new robust adaptive fuzzy control method by combining \(H\infty\) theory with backstepping technique for a class of uncertain nonlinear systems with unstable dynamics and mismatched disturbances.