船舶姿态运动实时预报算法研究

Research on Real-time Prediction Algorithm of Ship Attitude Motion

根据大型舰船在随机海浪作用下的非平稳运动特性,提出基于AR模型的实时建模预报方法,详细讨论了改进隅角实时快速定阶算法和RLS递推在线参数辨识方法。针对典型航行工况,对船舶纵摇运动进行了仿真研究,并与AIC定阶算法进行了比较。仿真结果表明:AR算法适用于舰船在非平稳运动情况下的建模预报。AIC准则、改进隅角两种定阶方法均可实现AR模型阶数的在线估计问题,预报长度均可达到7-10秒,但改进隅角定阶算法简单,独立性好,易于编程实现,预报实时性好。该方法在理论和工程应用方面具有重要的意义。

Based on the Automation Regressive （AR） model, a real-time modeling and prediction method for the huge ship attitude motion forced by random waves was introduced. A real-time fast order selection algorithm-based on improved comer condition and the RLS algorithm-recursion model parameter identification online was given. The ship longitudinal motion was simulated in the typical voyages condition, and it was compared with AIC rule order selection algorithm. The simulation results show that AR model is suitable to modeling and prediction for the ship in the condition of non-steady motion, and the two kinds of order selection algorithm both would realize estimating AR model order on-line, and prediction time would reach 7-10s. But the order selection algorithm-based on improved comer condition are simpler, programming easer, and that the prediction time is shorten. This method has important meaning in the aspects of theories and engineering application.