Hybrid prediction control model of ship's track

In order to improve the control quality of ship's track, a hybrid prediction control model was established.The uncertain variables of ship's dynamics were estimated by using grey predicting technique, while back propagation adaptive neural network with multilayer perceptrons was used to analyze the trend of control error development for ship's track based on studying ship's response errors, the optimal combination and optimal weight coefficients of the model were ascertained according to the difference of the above two results, so that the optimum control strategy was found.Simulation result shows that the oscillation of ship PID control system will occurs when one index value of demurrage, turning ability and following ability is more than 1, while the model enables ship's track errors to converge quickly with less rudder movement, so that ship's planning track accords with ship's real track, hereby, the robustness, rapidness and stability of the model are higher.