Improved Adaptive Neural Network Autopilot for Track-keeping Control of Ships

This paper presents an improved adaptive neural network autopilot based on our previous study for track-keeping control of ships. The: proposed optimal neural network controller am automatically adapt its learning rate and number of iterations. Firstly, the track-keeping control system of ships is described For the track-keeping control task, a way-p oint based guidance system is applied To improve the track-keeping ability, the off-track distance caused by external disturbances is considered in learning process of neural network controller. The simulations of track-keeping performance are presented under the influence of sea current and wind as well as measurement noise. The toolbox for track-keeping simulation on Mercator chart is also introduced.