Robust attitude control of helicopters with actuator dynamics using neural networks

In this study, attitude control is proposed for helicopters with actuator dynamics. For the nominal helicopter dynamics, model-based control is firstly presented to keep the desired helicopter attitude. To handle the model uncertainty and the external disturbance, radial basis function neural networks are adopted in the attitude control design. Using neural network approximation and the backstepping technique, robust attitude control is proposed with full state feedback. Considering unknown moment coefficients and the mass of helicopters, approximation-based attitude control is developed for the helicopter dynamics. In all proposed attitude control techniques, multi-input and multi-output non-linear dynamics are considered and the stability of the closed-loop system is proved via rigorous Lyapunov analysis. Extensive numerical simulation studies are given to illustrate the effectiveness of the proposed attitude control.