Adaptive attitude control of H∞ quadrotor UAV based on neural network

A robust attitude control scheme based on disturbance observer is designed to meet the attitude control requirements of quadrotor UAV. The H
∞
control problem of a class of non-affine nonlinear systems based on neural network is studied. A controller based on neural network is designed, which can not only ensure the stability of the closed-loop system, but also reduce the influence of interference on tracking to a given performance index. By means of implicit function theorem, Taylor formula and mean value theorem, the non-affine nonlinear system is transformed into affine nonlinear system. The designed controller is composed of equivalent controller and H
∞
controller. Finally, the effectiveness of the proposed method is proved by theoretical analysis.