According to the nonlinear characteristics of ship course control, and taking the first-order KT model of ship course motion as the research object, the selftuning PID algorithm course controller based on BP neural network was designed. Combining the traditional PID and the BP neural network, the controlled object was identified by the BP neural network, the PID control parameters were given, and the PID control algorithm was used to control and optimize the

convergence speed. Based on a true ferry′s characteristic parameters, the ship′s course motion control system model was established using MATLAB/Simulink simulation software. The simulation results show that the design has small overshoot, good robustness, capable to work steadily for a long time, and almost no steadystate error. The practicability of the control algorithm and the superiority of the PID control system were verified.