The Course Control of Air Cushion Vehicle With Uncertainties and Input Saturation

In the presence of input saturation and unknown the internal uncertainties, external disturbances, including sea wind, waves and currents, this paper develops a course control law for the system of air cushion vehicle (ACV) using neural network and auxiliary dynamic system to improve the maneuverability and safety. In the design process of the course control law of air cushion vehicle, the two problems of input saturation and uncertainties are considered. On one hand, an effective auxiliary dynamic system is introduced to solve the input saturation problem and reduce its impact on the system. On the other hand, in order to deal with the internal and external disturbances of the system, the fully turned radial basis function network (FTRBFNN) is combined with the control law, and its adaptive ability makes the system compensate better for unknown uncertainties better than RBFNN. The stability of closed-loop system is proved by Lyapunov analysis. It is proved that the designed course control law can maintain ACV’s heading at desired value, while guaranteeing the uniform ultimate boundedness of all signals in the ACV closed-loop control system. Finally, simulations on ACV are carried out to demonstrate the effectiveness of the developed ACV course control law.