## 1 Introduction  
The ducted fan micro aerial vehicle (MAV) with small size and compact structure is used mainly for low-speed flight missions in addition to hover, vertical takeoff, and landing capabilities. Compared to a conventional configuration micro unmanned helicopter (MUH) or a multi-rotor craft (MRC), the ducted fan MAV is a much safer platform since its propeller is mounted inside the duct which can act as a shield to avoid the risk of injury. The MUH and MRC, however, are rather dangerous due to the exposed rotor blades.  
Although many related research was previously almost under stagnation, ducted fan MAVs have recently attracted great interest, such as Cypher [1], iSTAR9 [2], and HoverEye [3]. Again, the studies have been conducted for ducted fan MAVs, mainly including multidisciplinary design optimization [4,5], system modeling [6, 7, 8], and control design [9, 10, 11, 12]. As for the control design, [PERSON] systematically developed the aerodynamic model and the attitude and position control systems for a ducted fan MAV with considering the crosswind, gyroscopic coupling and unknown aerodynamics, and successfully demonstrated the proposed control strategies on the HoverEye platform [13, 14]. The results of these investigations have certainly shown that the proposed control strategies, mainly based on decoupling and backstepping techniques, can significantly enhance the flight performance of the MAV with guaranteed stability. Sliding mode techniques are developed for improving the control qualities of ducted fan MAVs in [15,16], which show superior performance over classical control techniques when variations in vehicle dynamics and actuator characteristics are introduced. [PERSON] [17] adopted a nonlinear dynamic inversion method, and [PERSON] [18] proposed a compensator to accommodate for the effect of the actuator dynamics. However, most of these methods heavily rely on accurate dynamic models that are difficult to obtain, and the resulting performance is deteriorated in practical applications, especially in the presence of measurement noises. Other existing methods include PID control [19], linear-quadratic regulator (LQR) [20], robust control [21,22], neural adaptive control [23], fuzzy control [24,25], and nonlinear feedback control [26], _etc_. The actuator dynamics, however, have not been systematically considered, derived, and applied in the control system design.  
Overall, most related studies reported in the literature are based on the assumption that the actuator dynamics are fast enough to be negligible. However, the actuators actually show limited performance in real situations and, accordingly, the control qualities would be severely degraded if the actuator dynamics are neglected.  
In this study, a near-hover adaptive attitude control strategy is designed for a prototype ducted fan MAV. The combination of online parameter estimation and adaptive gain scheduling algorithms in the proposed strategy can accommodate parametric uncertainties and approximately eliminate the coupling among axes, which can simultaneously lead to enhance the resulting performance. The proposed strategy is tested and the results also illustrate that it can significantly improve the flight performance of the MAV.  
This paper is organized as follows: Section 2 is devoted to the description of the attitude control problem of the prototype ducted fan MAV. The adaptive attitude control strategy of the MAV with actuator dynamics is formulated in Section 3, and experimental tests are presented in Section 4. The last section offers conclusions.