Real-Time Prediction And Control Of Ship Roll

A ship is inevitably subjected to stochastic external force such as sea waves and ocean currents. This may cause the stochastic roll motion which would bring about safety trouble for operations on the seaway. It is important to predict the motion of ship in advance for the effective rolling control.The prediction of ship motion in advance is usually called short-time prediction or real-time prediction. This research employed the self-adaptive AR (Auto Regressive) model to complete the real-time prediction of the ship roll motion. The mathematical principle of AR model including the parameter estimation and order selection criterion was fully explored. The influence of sample frequencies and zero mean normalization of roll data on the accuracy of the prediction results were studied carefully. The great improvement on the accuracy of prediction was achieved. The developed algorithm was applied to predict the roll motion of 60 series standard ship model and verified by the prediction results.Based on the established real-time prediction method, the roll predictive control method was proposed to improve the roll stabilization effects. The whole control scheme was developed in the simulation package Simulink. This stabilization algorithm eliminates the lag influence of general feedback control methods and improves the roll stabilization effectively.