# Aerial Grasping of an Object in the Strong Wind: Robust Control of an Aerial Manipulator
## 1 Introduction  
In recent years, aerial manipulation has become a hot research topic in the field of UAVs [1; 2]. To complete aerial manipulation tasks, researchers have integrated tools with UAVs. For example, in one study, a gripper was installed on an UAV in so that the UAV could complete aerial grasping tasks [3; 4]. For canopy sampling tasks, a quadrotor was equipped with scissors [5]. Although an UAV with a tool can accomplish simple aerial manipulation tasks, it has weaker operational capability. When a multilink robotic arm is installed on the UAV, it will give the traditional UAV a strong operational capability. So, the aerial manipulator composed of a rotorcraft UAV and a multi-link robotic arm can extend the application prospects of the UAV greatly. For example, a dual-arm aerial manipulator is used to screw the valve in disaster scenarios [6]. An open-tilted hex-rotor with a passive arm aids human operators to move long bars for assembly tasks [7], and a hex-rotor with a 7 degree of freedom (DoF) manipulator grasps a moving target [8]. In addition, an aerial manipulator system with advanced manipulation capability for industrial inspection and maintenance is being developed in such projects as AEROARMS [9] and AEROWORKS [10] financed by the European Community. Without doubt, the steady flight of the UAV and the accurate operation of the end-effector are essential for an aerial manipulator to complete manipulation tasks. Thus, the aerial manipulator system control has attracted considerable attention, and a variety of control methods have been used in aerial manipulator systems. These include adaptive control [11; 12; 13], back-stepping [14; 15], model predictive control (MPC) [16; 17; 18], impedance control [19; 20], and so on. In one study, in order to carry and transport an unknown payload, an adaptive controller was designed for an aerial manipulator, composed of a quadrotor and a 2-DoF of robotic arm, which can estimate parameters of the payload online and track the desired trajectory [12]. In another study, a passive decomposition method is applied to decouple the dynamic of the aerial manipulator [14]. Based on the decoupled dynamic, a back-stepping controller was designed to control the UAV and end-effector simultaneously. In order to achieve optimal performance in the pick-and-place task, the nonlinear MPC method was used in an aerial manipulator composed of a quadrotor and a 2-DoF of robotic arm in [17]. To complete contact tasks, in one study an impedance control method was applied in an aerial manipulator composed of a helicopter and 7-DoF manipulator to pull a pole out of the fixing [20]. The above works on aerial manipulator system control have provided various methods to complete different manipulation tasks. These methods have been applied in experiments in structured environments, in which nothing can affect UAV control performance. However, in practical applications, there are various threats from the environment, such as strong gusty wind. The wind disturbance seriously damages the steady flight performance of the aerial manipulator, since the UAV's driving force almost comes from aerodynamic force. Thus, robustness against wind disturbance is a critical characteristic of the aerial manipulator in practical applications. So far, numerous studies have been focused on disturbance rejection control of the UAV, using different disturbance estimators. In one study a wind disturbance estimator was used in quadrotor control to reject wind disturbance based on the wind model, in which measurement of wind velocity is needed to estimate the disturbance [21]. In another study, a generalized extend state observer (GESO)-based disturbance estimator is used in the quadrotor attitude wind disturbance reject control, in which the disturbance is considered as a time polynomial function [22]. In a third study, a disturbance observer (DOB)-based method was used in quadrotor position control to reject the external force disturbance, in which the disturbance was estimated by the disturbance observer [23].