船舶航向保持运动的间接自回归历遍模型建模

Indirect auto-regressive exogenous modeling of ship course-keeping motion

中文关键词  船舶  建模  自回归  预测  长期预测

英文关键词  ship  modeling  autoregressive  prediction  long-run forecast

中文摘要

      本文针对船舶航向保持过程提出了一种间接的建模方法来描述船舶舵角与艏摇角之间的关系. 建模数据 来源于东京海洋大学实验船舶“夕路丸”的真实航行数据. 首先, 以船舶舵角为输入船舶艏摇角速度为输出, 建立 一个过渡自回归历遍(ARX)模型; 然后根据艏摇角速度和艏摇角间的差分关系, 得到最终的ARX模型. 再多组测试 数据下, 与机动建模组(MMG)模型和直接ARX模型的长期预测性能做了比较. 仿真结果显示, 本文提出的间接建模 方法对船舶的航向保持过程有更好的长期预测效果.

英文摘要

      This paper proposes an indirect modeling method for the ship’s course-keeping control process which could describe the relationship between the rudder angle and the heading angle deviation. The modeling data is from the actual sampling data of the ship“Shioji-Maru”which is an experimental ship of Tokyo university of marine science and technology. Firstly, using ship’s rudder angle as input and ship’s yaw rate as output, a transitional ARX model could be built; then according to the relationship between the yaw rate and the heading angle deviation, the final ARX model could be obtained. The long-term prediction comparisons with the MMG model and the direct ARX model are conducted under a group of testing data. The simulation results show that the indirect modelling method proposed in this paper could give a preferable modeling performance for the ship’s course-keeping control process.