Adaptive Trajectory Tracking Control for Double-Pendulum Aerial Transportation System

Cable-suspended aerial transportation systems are receiving increased attention due to their simple structure and flexible maneuverability. In most existing studies, the hook and payload are often simplified as a single point mass, disregarding the hook’s movement. However, in practical applications, the payload is suspended from the unmanned aerial vehicle (UAV) by a hook, resulting in a double-pendulum dynamic effect, where both the payload and the hook exhibit swinging motions. This effect causes the double-pendulum aerial transportation system to exhibit strong nonlinearity and state coupling, posing significant challenges for controller design. To address this issue, an adaptive trajectory tracking controller based on the adaptive dynamic programming (ADP) method is proposed for the double-pendulum aerial transportation system under external disturbances. Specifically, by defining the actor neural network (NN) and the critic NN, the optimal control input term is first obtained. Compensation and robustness terms are then introduced to address system uncertainties and external disturbances. The Lyapunov method is employed to rigorously prove the asymptotic convergence of the tracking errors. Comparative simulations and experiments validate the proposed method’s trajectory tracking performance and robustness, underscoring its practical effectiveness.