Backstepping-based attitude control for a quadrotor UAV with input saturation and attitude constraints

We investigate the robust backstepping-based attitude control strategy for a quadrotor unmanned aircraft vehicle (UAV). Because of its complex structure, a nonlinear mathematical model of UAV is difficult to be built accurately. Thus, in the process of controller design, we need to consider the following factors comprehensively: model uncertainties, unknown external disturbances, input saturations and attitude constraints. A neural network (NN) method is employed to estimate the model uncertainties of the system; the nonlinear disturbance observer is introduced to compensate for the external disturbances; the hyperbolic tangent function is used to approximate the saturation function for solving the input saturation problem. In designing the controller, we use the barrier Lyapunov function (BLF) to guarantee the constraints of the attitude. Finally, a backstepping-based controller is developed to control the attitude of the quadrotor UAV. The closed-loop control system is proved to be uniformly bounded by using Lyapunov stability theory. Simulation results are given to demonstrate the effectiveness of the proposed control strategy. © 2015, Editorial Department of Journal of Control Theory & Applications. All right reserved.