Finite-time adaptive sliding mode trajectory tracking control of ship with input saturation

A finite-time adaptive sliding mode ship trajectory tracking control strategy is designed to address the problems of unknown external disturbances, model uncertainties and input saturation of underactuated ship during navigation. By using neural networks to approximate the model uncertainties and using adaptive laws to estimate upper bound on the sum of the unknown disturbances and the neural network approximation errors. The "differential explosion"problem is solved by using dynamic surface technique, and design the controller with the finite-time convergence theory. Finally, the theoretical analysis is carried out by Lyapunov method, which proves that all signals of the closed-loop system are bounded. The simulation results show that the proposed control scheme is able to achieve trajectory tracking for underactuated ship regardless of whether input constraints are considered or not, and has satisfactory robustness in the face of unknown external time- varying disturbances and model uncertainties. The research done can provide effective reference for ship trajectory tracking control and has certain theoretical guidance significance.