Robust Adaptive Control for Unmanned Helicopter with Stochastic Disturbance

In this paper, the problem of robust adaptive control is concerned for a class of small-scale unmanned helicopter systems in the presence of system uncertainty, stochastic disturbance and output constraint. The adaptive neural network approximator is introduced to handle the unknown system function. Meanwhile, a prescribed performance function is employed to deal with output constraint. It is proved that the proposed control method is able to guarantee the ultimately bounded convergence of all closed-loop system signals in mean square via Lyapunov stability theory. The effectiveness of the developed robust controller are illustrated and confirmed by numerical simulations for a class of unmanned helicopter systems.