Quadrotor Attitude Control via Feedforward All-coefficient Adaptive Theory

The use of quadrotors is proliferating across many civil applications, including those in the areas of the Internet of Things (IoT) and communications. Attitude control plays an important role in these applications, and designing a quadrotor attitude controller is a challenging task. Recently, several design methods for the attitude controller were presented with an accurate model. However, during the flying state, the quadrotor may be affected by several factors that cause unpredictable disturbances to the model. As a result, an accurate model of disturbances is difficult to establish. To address this problem, in this paper, a novel linear feedforward all-coefficient adaptive control (FACAC) strategy based on characteristic modeling is proposed. The contributions of our work are as follows. First, a second-order characteristic model of the quadrotor attitude control is established based on the dynamic equations. Second, an all-coefficient adaptive control (ACAC) controller that consists of the golden-section adaptive control law, the logic integral, and logic differential control laws is designed. The feedforward maintaining and tracking control law is integrated into the ACAC controller to shorten the settling time. Finally, extensive simulation results demonstrate that the performance of the proposed FACAC controller outperforms the state-of-the arts.