Aiming at the difficulties of the accuracy maintenance and tracking control of unmanned surface vessels (USVs) operating in narrow lakes and culverts, an intelligent predictive control method for trajectory tracking is proposed on the basis of a self-developed small torpedo-type USV.

First, a self-developed nonlinear state space model of the underactuated USV is constructed. An intelligent predictive controller is designed on the basis of the model predictive control design concept and combined with an improved particle swarm optimization （PSO） algorithm to make online decisions, optimize the performance indicators at every moment and correct the predicted state. Finally, simulation and lake tests are carried out to test the tracking performance of the system on reference trajectories, and the tracking performance is compared with that of the linear model predictive controller.

The results show that the designed intelligent predictive controller has fast response speed, small overshoot and good anti-interference capabilities.

The proposed method can not only be applied to the tracking systems of small torpedo-type USVs, but can also provide references for other USV tracking systems.