Ship collision avoidance methods : State-of-the-art

This paper surveys the recent advances in marine mechatronic systems from a control perspective. The survey is by no means exhaustive, but introduces some notable results in marine control area. New developments in terms of control system designs for surface vessels, underwater robotic vehicles, profiling floats, underwater gliders, wave energy converters, and offshore wind turbines are briefly reviewed. In addition, a few avenues for future research are identified.

Advanced Control in Marine Mechatronic Systems: A Survey

COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach

In this paper, we propose enhancements to Beetle Antennae search &#x0028 BAS &#x0029 algorithm, called BAS-ADAM, to smoothen the convergence behavior and avoid trapping in local-minima for a highly non-convex objective function. We achieve this by adaptively adjusting the step-size in each iteration using the adaptive moment estimation &#x0028 ADAM &#x0029 update rule. The proposed algorithm also increases the convergence rate in a narrow valley. A key feature of the ADAM update rule is the ability to adjust the step-size for each dimension separately instead of using the same step-size. Since ADAM is traditionally used with gradient-based optimization algorithms, therefore we first propose a gradient estimation model without the need to differentiate the objective function. Resultantly, it demonstrates excellent performance and fast convergence rate in searching for the optimum of non-convex functions. The efficiency of the proposed algorithm was tested on three different benchmark problems, including the training of a high-dimensional neural network. The performance is compared with particle swarm optimizer &#x0028 PSO &#x0029 and the original BAS algorithm.

/pdf/bas-adam-an-adam-based-approach-to-improve-the-performance-1mel0kdceb.pdf

BAS-ADAM: an ADAM based approach to improve the performance of beetle antennae search optimizer

Quantifying hourly suspended sediment load using data mining models: Case study of a glacierized Andean catchment in Chile

Vessel traffic flow forecasting is of significant importance for the water transport safety, especially in the multi-bridge water areas. An improved Kalman model combining regression analysis and Kalman filtering is proposed for short-term vessel traffic flow forecasting between Wuhan Yangtze River Bridge (hereafter WYRB) and the Second Wuhan Yangtze River Bridge (hereafter SWYRB). Given the vessel traffic flow of WYRB is positively correlated with that of SWYRB, its regression coefficient is obtained as well as the regression predictions. The predictions are further used to replace the state transition equation of Kalman filtering. The prediction results of the improved Kalman model demonstrate better agreements with field observations, and hence, illustrate good capability of the proposed method in the short-term traffic flow forecasting. The discrepancy between the model predictions and field observations is generally attributed to the inherent deficiency of Kalman filtering method and the errors resulted from automatic identification system (AIS) data (e.g. missed AIS data). The proposed method can provide a support for the real-time and accurate basis for the ship traffic planning management.

https://link.springer.com/content/pdf/10.1007/s10586-017-1491-2.pdf

Short-term vessel traffic flow forecasting by using an improved Kalman model

An autonomous vessel can improve the intelligence, efficiency and economy of shipping logistics. To realize autonomous navigation control of underactuated vessels (USVs), this paper presents a controller that can make USV track a reference trajectory with only 2 inputs, i.e., surge and yaw. A nonlinear state-space model with 2 inputs considering environmental disturbances induced by wind, current and waves for a 3 degree of freedom (DOF) surface vessel is considered. Based on this model, a trajectory tracking controller using Nonlinear Model Predictive Control (NMPC) is designed. System constraints on inputs, input increment and output are incorporated in the NMPC framework. Simulation results show that the controller can track an ellipse trajectory well and that the tracking errors are within acceptable ranges, while system constraints are satisfied.

Trajectory Tracking Control for Underactuated Surface Vessels Based on Nonlinear Model Predictive Control

The AIS broadcasts the ship's navigation data automatically and autonomously through VHF band. It plays an important role in collision avoidance and maritime situational awareness. However, in inland waterways, it is common that the AIS data-link was obstructed by the river bank and mountains, or sometimes the AIS was encountered with the electromagnetic interference. Consequently, the AIS dynamic data is often lost and mixed with inaccurate, which may lead to misjudgment of the traffic situation. To address this problem, a method was proposed to enhance the availability of AIS data in this paper. Firstly, according to the ships' maneuverability, a set of factors, such as the moving distance, speed, acceleration, and course change rate, were designed to screen the inaccurate AIS data. Then, the piecewise cubic Hermite interpolation and cubic spline interpolation were employed to restore the AIS data. A real AIS trajectory was introduced to validate the accuracy of the two interpolation methods, which proves that the cubic spline interpolation performance is better than piecewise cubic Hermite interpolation. Field experiments in Wuhan reach of Yangtze River show that the method proposed in this paper is highly effective. The accuracy of the location is 3.5m, the speed accuracy is 0.05m/s, and the course accuracy is up to 0.7 degrees, the AIS data can be accurately repaired.

Enhance the AIS data availability by screening and interpolation

Underwater sonar imaging is a significant means for a variety of maritime work However, the sonar images are corrupted by signal dependent speckle noise, which restricts the potential practical applications In this paper, we propose a novel variational approach that addresses the adaptive sonar image denoising problem To accurately describe the signal dependent characteristic of noise for real sensors, we utilize a generalized noise model, which can be adapted to represent various types of noise With the generalized noise model, we formulate the denoising problem via a variational approach Finally, we present a modified primal and dual method to efficiently solve the variational minimization problem Experimental results on both simulated and real data validate the effectiveness and efficiency of our method

A variational approach for adaptive underwater sonar image denoising

AIS data are of great significance to ensure the safety of ship navigation and strengthen maritime management. The present study focuses on the situations of AIS data loss in practical applications to research coverage of AIS base station. The original AIS data is pre-processed in accordance with structure characteristics, including data packet, data filtering and so on. Data reconstruction has been performed by applying piecewise cubic Hermite interpolation function. In order to identify AIS data loss for different segments, the study area is divided into several sub-areas, on basis of which AIS data loss rate has been statistically computed and visually presented by using mapping technique. The characteristics of individual vessel passing through the area are investigated as well. By applying visual analysis method, the coverage of AIS base station at the upper Yangtze River is revealed. The present study provides novel insights into AIS base station arrangement strategies, thus AIS data loss rate could be reduced.

Xiumin Chu

Papers

Short-term vessel traffic flow forecasting by using an improved Kalman model

Trajectory Tracking Control for Underactuated Surface Vessels Based on Nonlinear Model Predictive Control

Enhance the AIS data availability by screening and interpolation

A variational approach for adaptive underwater sonar image denoising

Coverage effectiveness analysis of AIS base station: A case study in Yangtze River