Adaptive NN Zeta-Backstepping Control with Its Application to a Quadrotor Hover

This brief presents an adaptive neural network (NN) zeta-backstepping control method for a class of uncertain nonlinear systems with unknown nonlinearities. Different from the traditional adaptive NN backstepping control scheme, the proposed adaptive NN zeta-backstepping control approach can regulate the damping ratio of a system by using prescribed parameter selection rules. To guarantee the stability of the closed-loop system, a second-order Lyapunov function method is presented, which proves that the target signal can be boundedly tracked by the system output with adjustable damping ratios. Finally, experimental results on a real quadrotor hover system are given to show the effectiveness of the proposed control scheme.