Model reference adaptive control design for quadrotor UAV transporting unknown payloads

Abstract

In this paper, Research on adaptive control that compensates for the uncertainty caused by a quadrotor transporting the unknown payloads is performed. To transport goods or people using a quadrotor, the hybrid-power system using alternative energy sources such as gasoline and hydrogen fuel is required to ensure operating hours and what model parameters change from the payload is essential. Therefore, the stable controller is essential to compensate for the uncertainty of the mass, the moment of inertia, and the center of gravity due to payload and fuel consumption. We proposed the Feedback Linearization-based Model Reference Adaptive Control (FL-MRAC) method to solve the flight performance degradation caused by model parameter uncertainty. First, we derive the mathematical model of the quadrotor considering the effect of the off-diagonal inertia tensor, the change rate of mass and moment of inertia over time and center of gravity. Second, the reference model is selected through the feedback linearization of response dynamics. In addition, the closed-loop reference model is used to improve the transient response and robustness. Third, adaptive laws are derived using a Lyapunov candidate function that satisfies uniform ultimate boundedness under the sensor noise, external disturbance, time-varying mass, and moment of inertia. Lastly, we give numerical simulation results illustrating FL-MRAC, which shows more accurate control performance than the feedback linearization with integral action. The transient response of proposed controller is analyzed using the open-loop reference model and closed-loop reference model.