Robust Adaptive Attitude Trajectory Tracking Control for a Quadrotor System

In this paper, three robust control strategies are proposed to achieve attitude stabilization of a quadrotor system. The attitude dynamics of quadrotor system is first introduced. Then, a basic dynamic surface control with disturbance rejection is presented. However, the parameter uncertainty is not considered in the control scheme. To address this problem, two adaptive control design techniques based on dynamic surface method are suggested. Their difference lies in suppression of disturbance, one of which is to design an adaptive learning algorithm for disturbance bound, and the other is to use a signum function. Meanwhile, an adaptive learning law is proposed to estimate physical parameters of attitude channel. As a result, parameter uncertainty and disturbance rejection are addressed simultaneously. The asymptotical convergence of attitude tracking errors in the three control methods are proved. The transient performance based on L∞ norm is considered by analyzing the solution of the defined Lyapunov function. Finally, simulation is performed to demonstrate the effectiveness of the three controllers, and the statistical indexes are further given to quantitatively evaluate the three control schemes.