Aiming at the shortcomings such as poor real-time performance and low precision of the current water surface unmanned course control

a new method of optimizing proportional-integral-derivative（ PID） parameters by using ant colony algorithm with mutation features to carry out unmanned surface vehicle（ USV） course control is proposed. On the basis of USV course control kinematics model

the integral of the moment of absolute error is taken as the objective function

and the improved mutation operator suitable for PID parameter optimization is introduced into the ant colony algorithm to optimize the PID parameters of the USV course control process. The control effects of ant colony optimization PID course control algorithm

conventional ant colony PID course control algorithm and PID course control algorithm on USV course control are compared. The simulation experiment and field test show that the control method has faster convergence speed and better optimizing ability than the conventional ant colony algorithm in the parameter optimization process

and has the advantages of small heading control overshoot

fast tracking speed and stable control.