An on line training functional link neural network predictor/controller for dynamic positioning of water surface structures is described in this paper. The on line training neural network predictor acquires the knowledge about the system using a small number of samples of the latest system status measured on board of the structure. The trained function link neural network is used with an optimal controller to control the output of the system. The accuracy and robustness of the on line training predictor are demonstrated through the numerical simulations of two ship maneuvers. The on line training neural network predictor/controller is applied to the dynamic positioning (station keeping) of a ship in a uniform current with and without external environmental disturbances. The results of the numerical simulations are very satisfactory. An on line training functional link neural network predictor / controller for dynamic positioning of water surface structures is described in this paper. The on line training neural network predictor acquires the knowledge about the system using a small number of samples of the latest system status measured on The accuracy and robustness of the on line training predictor are demonstrated through the numerical simulations of two ship maneuvers. The on line training neural network predictor / controller is applied to the dynamic positioning (station keeping) of a ship in a uniform current with and without external environmental disturbances. The results of the numerical simulations are very satisfactory.