Online recorded data-based finite-time composite neural trajectory tracking control for underactuated MSVs.This paper presents an online recorded data-based composite neural finite-time control scheme for underactuated marine surface vessels (MSVs) subject to uncertain dynamics and time-varying external disturbances.  The underactuation problem of the MSVs was solved by introducing the line-of-sight (LOS) method.  The uncertain dynamics of MSVs are approximated by the composite neural networks (NNs).  Moreover, the smooth function is inserted into the design of the control scheme, and the finite-time composite neural trajectory tracking control of MSVs is achieved.  The stability of the MSVs trajectory tracking closed-loop control system is guaranteed rigorously by the Lyapunov approach, and the tracking error will converge to the set of residuals around zero within a finite time. 
MSVs
The uncertain dynamics of MSVs are approximated by the composite neural networks (NNs).  Furthermore, disturbance observers can be devised to estimate the compound disturbances consisting of the approximation errors of NNs and external disturbances. 
NNs
The underactuation problem of the MSVs was solved by introducing the line-of-sight (LOS) method.  The stability of the MSVs trajectory tracking closed-loop control system is guaranteed rigorously by the Lyapunov approach, and the tracking error will converge to the set of residuals around zero within a finite time. 
LOS