## 1 Introduction  
Unmanned aerial vehicles (UAVs) have become a popular and active research topic among scholars worldwide [1; 2]. It could work at locations where entry is difficult and humans cannot access [3]. Recently, they are not only used in traditional scenes, such as monitoring, aerial photography, surveying, and patrol, but are also employed in new application scenarios requiring physically interacting with external environment. Then, to conduct physical interaction, aerial robots are either equipped with a rigid tool [4] or an n-degree-of-freedom (DoF) robotic arm [5; 6; 7; 8], which are called UAV manipulators. As for the UAV equipped with a robotic arm, several disturbances cannot be avoided, such as wind gust and model uncertainties, during task execution. Therefore, to meet the aerial operation task requirements with high reliability, disturbance rejection control problem should be investigated. Many controllers have been proposed for disturbance rejection. The Robust Model Predictive Control (MPC) method is used for multirotor UAV to provide robust performance under an unknown but bounded disturbance [9]. Meanwhile, the adaptive control structure is built to obtain coefficients of system with uncertainty online. A controller based on Model Reference Adaptive Control is proposed in [10], which performs better on disturbance rejection compared with non-adaptive controllers. However, as what we know, one of the biggest drawbacks of adaptive controllers is that they perform little robust under the bursting phenomenon. Adopting the disturbance and uncertainty estimation and attenuation (DUEA) strategy, such as Disturbance observer (DOB) [11], unknown input observer (UIO) [12], and extended state observer (ESO) [13], would be a potential solution for disturbance rejection. Meanwhile, there are several types of DOBs applied to UAVs. Work [14] proposes an inner-loop control structure to recover the dynamics of a multirotor combined with additional objects similar to the bare multirotor using DOB-based method. A linear dual DOB is built in [15] to reject modeling error and external disturbance when designing the control system. The authors of [16] propose a DOB-based tracking flight control method for a quadrotor to reject disturbance, which is supposed to be composed of some harmonic elements, and applies it to flight control of the UAV Quanser Qball 2. A disturbance observer with finite time convergence (FTDO), which could conduct online estimation of the unknown uncertainties and disturbances, is incorporated into an hierarchical controller to solve the problem of path tracking of a small coaxial rotor-type UAV [17]. The authors of [18] introduce a robust DOB for an aircraft to compensate the uncertain rotational dynamics into a nominal plant and proposes a nonlinear feedback controller implemented for desired tracking performance. As for ESO, it was first proposed by [PERSON] [19] and has been introduced in many control methods [20]. Traditionally, ESO methods mainly focus on coping with disturbances which slowly change [21]. Nevertheless, it is evident that the disturbance caused by the wind gust sometimes performs drastic change so that it can not be estimated by traditional ESO thoroughly. Thus, an enhanced ESO that could quickly estimate the disturbance is necessary in this field. A high order sliding mode observer is built to estimate unmodeled dynamics and external disturbances for an aerial vehicle to track the trajectory [22]. Moreover, a sliding mode observer is proposed for equivalent-input-disturbance approach to control the under-actuated subsystem of a quadrotor UAV [23]. However, chattering phenomenon is normal in traditional sliding mode observer (SMO) because of the discontinuous sign function. In order to reduce the chattering problem, the super-twisting algorithm is introduced in a ESO to mitigate estimation chattering [24], but there is still a little chattering.