Event-triggered finite-time tracking control of underactuated MSVs based on neural network disturbance observer

Abstract

In this work, a trajectory tracking control issue is discussed for the underactuated marine surface vessels (MSVs) with uncertain dynamic and unknown external disturbances. In the control design, the neural network approximation technology is applied to reconstruct the unknown dynamic, and a finite-time disturbance estimator is established to reconstruct the lumped uncertainties including the unknown external disturbance and approximation error online. Under the design framework of line-of-sight, a new finite-time trajectory tracking control scheme for underactuated MSVs is developed combining the finite-time control theory with the backstepping design method. The developed control scheme has the following remarkable characteristics: (1) it realizes the fast and accurate online reconstruction of lumped uncertainties; (2) it can release the requirement of online disturbance estimation technology on an accurate MSV motion model and expand the application range of online disturbance estimation technology; (3) the unnecessary wear and tear of actuators is suppressed by introducing the event-triggered control (ETC) approach. Based on the Lyapunov theory, it is proved that all signals in the closed-loop tracking control system are bounded. Finally, the effectiveness of the proposed control scheme is verified by the simulation and comparison.