Robust Adaptive Finite-time Tracking Control for Unmanned Aerial Vehicle with Uncertainty

This paper investigates finite-time stability and tracking control problem of multirotor unmanned aerial vehicle in the presence of the modeling errors and external disturbances uncertainty. The algorithms for autonomous position and attitude flight tracking system are designed with the help of Lyapunov and nonlinear terminal sliding mode control theorem. Robust and adaptive learning algorithms for both position and attitude dynamics are designed to learn and compensate the modeling errors and external disturbances. Convergence analysis shows that the design can ensure finite-time stability and tracking property of the position and attitude subsystem motion dynamics of the underactuated complex aerial vehicle. The proposed design provides finite-time convergence as opposed to the existing asymptotic results for the multirotor aerial vehicle. The design does not need exact bound of the uncertainty that appears from external disturbance and the modeling errors of the position and attitude subsystem dynamics. The proposed finite-time design ensures faster and robust tracking in the presence of uncertainty as opposed to existing asymptotic designs.