The adaptive control scheme of a quadrotor Micro Aerial Vehicle (MAV) by using Interval Type-II Fuzzy Neural Network (IT_IIFNN) was proposed to improve the control accuracy that was declined by the uncertainty, external disturbances,etc. Based on the quadrotor MAV dynamic modeling, an adaptive controller composing of two parts was designed by using the IT_IIFNN,in which the IT_IIFNN was developed to approximate the uncertainty function and a robust compensator was proposed to confront the approximate errors of IT_IIFNN and external disturbances in real-time. Moreover, the Lyapunor stability theory was taken to prove the stability of the closed-loop control system in the quadrotor MAV. Finally, the superiority of the adaptive controller was verified by a prototype of the quadrotor MAV,which is shown that the tracking error approximated is 10-2 under the interference conditions of wind speed of 1. 5 m/s. Experiments demonstrate that proposed control scheme can offer perfect tracking accuracy, stability and robustness.%针对四旋翼微型飞行器控制系统中存在不确定性、外界干扰等影响控制精度的问题,提出了基于区间二型模糊神经网络(IT_IIFNN)的四旋翼微型飞行器自适应控制方案.首先,根据四旋翼微型飞行器的动力学模型,设计了基于IT_IIFNN的四旋翼微型飞行器自适应控制器,该控制器由两部分构成,其中IT_IIFNN用来在线逼近系统不确定性；鲁棒补偿器用来实时补偿IT_IIFNN的逼近误差以及外界干扰.其次,利用Lyapunov稳定理论证明此飞行器控制系统闭环稳定性.最后,通过四旋翼微型飞行器样机来验证IT_IIFNN自适应控制器的优越性.验证结果显示,在加入风速为1.5 m/s的外界干扰条件下,跟踪误差可近似达到10-2.结果表明,IT_IIFNN自适应控制器具有良好的跟踪精度、稳定性及鲁棒性.
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