Adaptive control of quadrotor MAV using interval type-II fuzzy neural network

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.