Improving the Performance of Dynamic Ship Positioning Systems: A Review of Filtering and Estimation Techniques
Improving the Performance of Dynamic Ship Positioning Systems: A Review of Filtering and Estimation Techniques
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DOI：
10.3390/jmse8040234
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发表时间：
2020-03
影响因子：
2.9
通讯作者：
D. Selimović;J. Lerga;J. Prpić-Oršić;Sasa Kenji
中科院分区：
文献类型：
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作者：
D. Selimović;J. Lerga;J. Prpić-Oršić;Sasa Kenji
在海上的各种操作，如保持恒定的船舶位置和方向，需要复杂的控制系统。在这种情况下，船舶需要一种高效的定位技术。动力定位(DP)系统提供了执行器机构、关键船舶变量分析和环境条件的组合应用。作用在船体上的诱导非线性波浪的自然力对系统产生干扰。为了准确地产生执行器的控制信号，需要对传感器测量数据进行滤波和处理。此外，为了安全和绿色的航线，作用在船体上的力和力矩在它们的预测方面应该被考虑在内。因此，这种系统的设计考虑了获得关于方向波谱(DWS)的数据的问题。传感器系统单独不能提供高精度和可靠性，因此它们的测量需要组合和补充。基于递归卡尔曼滤波(KF)的技术被用于这一目的。当一些测量值不可用时，估计程序应该预测它们，并基于理论状态和测量状态的比较，减少分析信号的误差方差。多年来，随着改进的迹象，不同的改进估计算法的方法已经演变。本文概述了在DP系统中提供最佳估计状态的最新估计和滤波技术。
Various operations at sea, such as maintaining a constant ship position and direction, require a complex control system. Under such conditions, the ship needs an efficient positioning technique. Dynamic positioning (DP) systems provide such an application with a combination of the actuators mechanism, analyses of crucial ship variables, and environmental conditions. The natural forces of induced nonlinear waves acting on a ship’s hull interfere with the systems. To generate control signals for actuators accurately, sensor measurements should be filtered and processed. Furthermore, for safe and green routing, the forces and moments acting on the ship’s hull should be taken into account in terms of their prediction. Thus, the design of such systems takes into account the problem of obtaining data about the directional wave spectra (DWS). Sensor systems individually cannot provide high accuracy and reliability, so their measurements need to be combined and complemented. Techniques based on the recursive Kalman filter (KF) are used for this purpose. When some measurements are unavailable, the estimation procedure should predict them and, based on the comparison of theoretical and measured states, reduce the error variance of the analyzed signals. Different approaches for improving estimation algorithms have evolved over the years with the indication of improvement. This paper gives an overview of the state-of-the-art estimation and filtering techniques for providing optimum estimation states in DP systems.