Adaptive Neural Network Dynamic Surface Tracking Control of a VTOL Aircraft

The problem of asymptotic tracking control for a vertical take-off and landing (VTOL) aircraft system is addressed in this paper, in which unknown external disturbances and nonlinear dynamics are added. Unknown nonlinear dynamics are deal with by using neural networks, and some adaptive laws are addressed. Additionally, some control laws for unknown parameters are developed to address unknown nonlinearities resulting from the analysis process. Based on the dynamic surface control approach and neural network control, the adaptive control laws with dynamic surface method and neural network are developed for the system. The results show that the developed control laws insure that the system under consideration asymptotically follows the given desired signal, and the system's tracking errors can converge to zero. At last, a simulation case is shown to validate the effectiveness of developed control strategies.