Finite-Time Adaptive Reinforcement Learning Control for a Class of Morphing Unmanned Aircraft with Mismatched Disturbances and Coupled Uncertainties

This paper proposes a finite-time adaptive reinforcement learning (RL) control law for a class of morphing unmanned aircraft with mismatched disturbances and coupled uncertainties. To handle the mismatched disturbances, an adaptive upper-bound estimator as well as the parameter adaptive laws have been proposed. Aiming at the coupled uncertainties, an RL-based online uncertainty estimator and a corresponding finite-time compensation control law have been developed. To deal with the non-affine characteristics, an auxiliary integral system has been introduced. By systematically integrating the aforementioned adaptive upper-bound estimators, finite-time control law, and the auxiliary signals, a novel RL-based adaptive finite-time control framework is constructed for morphing unmanned aircraft. Simulation results reveal the finite-time convergence and the advantages of the proposed method.