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首页> 外文期刊>Journal of ocean engineering and marine energy >Time-series forecasting of ships maneuvering in waves via dynamic mode decomposition
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Time-series forecasting of ships maneuvering in waves via dynamic mode decomposition

机译：基于动态模态分解的船舶波浪机动时间序列预报

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摘要

A data-driven and equation-free approach is proposed and discussed to forecast responses of ships maneuvering in waves, based on the dynamic mode decomposition (DMD). DMD is a dimensionality-reduction/reduced-order modeling method, which provides a linear finite-dimensional representation of a possibly nonlinear system dynamics by means of a set of modes with associated oscillation frequencies and decay/growth rates. This linear representation is entirely derived from available data and does not require the knowledge of the underlying system equations, which are and remain unknown. Based on the linear representation, DMD allows for short-term future estimates of the system state, which can be used for real-time prediction and control. Here, the objective of the DMD is the analysis and forecast of the trajectories/motions/forces of ships operating in waves, offering a complementary efficient method to equation-based system identification approaches. Results are presented for the course keeping of a free-running naval destroyer (5415M) in irregular stern-quartering waves and for the free-running KRISO Container Ship performing a turning circle in regular waves. Results are overall promising and show how DMD is able to identify the most important modes and forecast the system state with reasonable accuracy upto two wave encounter periods.
机译：一个数据驱动和equation-free方法提出并讨论了预测的反应船舶操纵在波浪,基于动态模态分解(DMD)。降维/降维建模方法,它提供了一个线性的一个可能的有限维表示通过一组非线性系统动力学与相关的振荡频率和模式衰变/增长率。完全来自可用数据,不需要底层系统的知识方程,并保持未知。线性表示,模式允许短期未来估计系统的状态,可以用于实时预测和哪一个控制。分析和预测的轨迹/运动/船只在部队波,提供互补的有效方法equation-based系统识别方法。保持的不同步的海军驱逐舰(5415米)stern-quartering波和不规则的不同步的KRISO集装箱船执行转弯半径在常规波。总体承诺和显示模式可以最重要的模式识别和预测系统状态与合理的准确性高达两个波遇到时期。

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