Finite-Time Neuro-Sliding-Mode Controller Design for Quadrotor UAVs Carrying Suspended Payload

Due to the quadrotor’s underactuated nature, suspended payload dynamics, parametric uncertainties, and external disturbances, designing a controller for tracking desired trajectories quadrotor that carries is challenging task. Furthermore, one of most significant disadvantages nonlinear systems infinite-time convergence trajectory. In this paper, finite-time neuro-sliding mode (FTNSMC) with subject uncertainties disturbances designed. By constructing sliding controller, can follow reference in finite time. despite time-varying neural network structure added effectively reduce chattering phenomena caused by high switching gains, significantly size control signals. Following completion design, system’s stability demonstrated using Lyapunov criterion. Extensive numerical simulations various scenarios are run demonstrate effectiveness proposed controller.