This paper investigates the formation keeping problem of heterogeneous ships with underactuated inputs, uncertain dynamics, and environmental disturbances. The control objective is to make the heterogeneous followers keep the desired formation while tracking a leader. To solve the problem effectively, a novel virtual leader–follower formation scheme considering the ship heterogeneity is proposed by utilizing the backstepping method, adaptive neural network, and adaptive control law. The stability of the formation control system is proved based on Lyapunov's direct method where all tracking errors are guaranteed to be uniformly ultimately bounded. Finally, simulations and comparisons are conducted to verify the effectiveness of the proposed control law.

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Autonomous docking and undocking control is an important part of intelligent ship motion control. In this study, the adaptive-mutation beetle swarm prediction (AMBS-P) algorithm is used to propose a control approach for autonomous docking and undocking. Firstly, this paper introduces the principle of the AMBS-P algorithm, then the convergence is proved. Secondly, the “Tito-Neri” model ship is introduced as a case study, and the thrust allocation process is described. Finally, the effect of docking and undocking is verified in multiple scenarios starting from different angles. In the verification, first of all, when designing the docking and undocking controllers, the correctness of the algorithm and the practicality of the control are verified by whether there is ship drag or not. Secondly, by analyzing the parameters of the algorithm, the optimal parameters of it are determined and verified in the real environment. Thirdly, compared with typical proportion–integral–derivative (PID) algorithm and nonlinear model predictive control (NMPC) algorithm, the AMBS-P algorithm has better results for autonomous docking and undocking control, no matter in long-distance or short-distance. The research shows that the AMBS-P algorithm has a fast response and good effect for the ship autonomous docking and undocking, and does not rely too much on the system model.

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A good mesh is a prerequisite for achieving reliable results from Computational Fluid Dynamics (CFD) calculations. Mesh properties include mesh types, computational domain sizes, and node distributions. However, in literature, we found no clear consensus about what these properties should be. In this article, we performed a case study on ship rudders to determine what the suitable mesh properties are for airfoil-shaped profiles. A classic NACA 0012 profile is chosen as an example, and commercial packages ANSYS ICEM are applied for meshing with an ANSYS Fluent solver. With a strategy in consideration of relationships among different mesh properties, a comprehensive parametric investigation is conducted to study the impacts of these properties on the accuracy of rudder hydrodynamic coefficients obtained by CFD methods. The step-by-step study outputs recommended Reynolds numbers, domain sizes, and near-and far-field node distributions for mesh types with distinct topology structures, i.e., C-mesh, O-mesh, H-mesh, and Hybrid-mesh. Specifically, the study shows that a critical Reynolds number is needed for the perspective of efficiency, while a domain extending 60 times of the chord length enables the boundary effects to be negligible. As for node distributions, the near-field nodes should be treated carefully, compared with those in the far-field. After that, corresponding mesh properties for different calculation objectives are illustrated in detail based on the characteristics of mesh types mentioned above. With the proposed strategy for mesh refinements, impacts of different mesh properties on rudder hydrodynamics are clarified and recommended settings are applicable for other airfoil-shaped profiles such as wind turbines and marine propellers.

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Human experience is regarded as an indispensable part of artificial intelligence in the process of controlling or decision making for autonomous cargo ships. In this paper, a novel Deep Q-Network-based (DQN) approach is proposed, which performs satisfactorily in controlling a cargo ship automatically without any human experience. At the very beginning, we use the model of KRISO Very Large Crude Carrier (KVLCC2) to describe a cargo ship. To manipulate this ship has to conquer great inertia and relatively insufficient driving force. Subsequently, customary waterways, regulations, conventions are described with Artificial Potential Field and value-functions in DQN. Based on this, the artificial intelligence of planning and controlling a cargo ship can be obtained by undertaking sufficient training, which can control the ship directly, while avoiding collisions, keeping its position in the middle of the route as much as possible. In simulation experiments, it is demonstrated that such an approach performs better than manual works and other traditional methods in most conditions, which makes the proposed method a promising solution in improving the autonomy level of cargo ships.

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Autonomous shipping refers to the ability of a ship to independently control its own actions while transporting cargo from one port to another, which places higher requirements on ship motion control methods. When a ship enters a port, it is important to ensure that the ship sails from the fairway area to the assigned position at the berth with a desirable speed and that it finally stops at the desired position. Ship docking is known as one of the most challenging tasks due to the non-linearity of low-speed ship movements and the high requirements on collision avoidance with the quayside. This paper proposes a nonlinear model predictive control (NMPC)-based approach for underactuated ships, providing optimal ship rudder angles and propeller revolution rate to automate the ship docking process. At each sampling instant, a finite horizon optimal control problem is formulated based on a nonlinear ship maneuverability model. A lexicographic multi-objective optimization strategy is proposed in the design of the NMPC controller, saving the efforts on control parameters tuning. Simulation experiments are carried out to evaluate the effectiveness of the proposed approach.

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The future autonomous ships will be operating in an environment where different autonomous and non-autonomous vessels with different characteristics exist. These vessels are owned by different parties and each uses its owned unique approaches for guidance and navigation. The Collaborative Autonomous Shipping Experiment (CASE) aims at emulating such an environment and also stimulating the move of automatic ship control algorithms towards practice by bringing together different institutes researching on autonomous vessels under an umbrella to experiment with collective sailing in inland waterways. In this paper, the experiments of CASE 2020 are explained, the characteristics of different participating vessels are discussed and some of the control and perception algorithms that are planned to be used at CASE 2020 are presented. CASE 2020 will be held in parallel to iSCSS 2020 at Delft University of Technology, the Netherlands.

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.@en

Ship collision is the main type of maritime accidents, which causes great losses on human lives and economy, and brings negative impacts to the maritime environment. In crowded waters such as the sea area near a seaport, multiple ships encountering situations happen frequently. While several methods have been proposed for solving multiple ships collision avoidance problem, most research focuses on the safety guarantee and time-availability of anti-collision decisions, and less attention is paid on improving the efficiency of collision avoidance maneuvers. This paper proposes a rolling horizon optimization approach for multiple ships from a global optimal perspective, with the aim to minimize the time costs and course angle alterations of the anti-collision operations. A ship maneuverability model is used to make predictions and calculations of inter-ship collision risks, upon which an overall optimization problem is formulated. Continuous time is divided into a set of discrete time slots, and an iterative optimization procedure is carried out to determine the optimal course angles for the ships at each time slot. A PID heading controller is designed to implement the optimal course angles. When collision risks among ships no longer exist, the optimization procedure terminates. To evaluate the performance of the proposed approach, simulation experiments regarding 7-ships and 12-ships encounter situations are carried out.

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The performance of ship rudders affects ship maneuvering, including, but not limited to, turning ability, yaw checking ability, and course-keeping ability. Previous empirical formulas for the rudder forces did not properly address the impacts of the rudder profile and the interaction between rudders in case there are more than one. To take these factors into account during the selection of rudder configurations, the regression formulas of rudder hydrodynamics that were formulated based on a series of RANS simulations and presented by Liu et al. (2016, 2017b) are applied in this study. With a more accurate estimation of rudder hydrodynamic coefficients, the impacts of rudder configurations on ship maneuvering and resistance are studied with an integrated mathematical model introduced by Liu et al. (2017a) through maneuvering simulations. The impacts of rudder configurations, more specifically rudder profiles, the spacing between twin rudders, and the spacing among quadruple rudders, on ship maneuvering and resistance are summarized. This can be used as a guide for designers to quickly assess their design choices. Accordingly, a design flow is proposed for naval architects to choose a proper rudder configuration, especially for large seagoing ships and inland vessels which commonly have multiple-rudder configurations.@en

Intelligent motion control is one of the key technologies of ships. This paper studies the application of Adaptive Mutation Beetle Particle Swarm (AMBPS)-PID algorithm in ship motion control. Firstly, the ship MMG model is established. Then the BAS algorithm is introduced, and AMBPS algorithm is improved and designed on this basis. Secondly, ship heading and path following controllers are designed according to the algorithm, and rudder turning rate constraint is introduced to limit the rudder angle. Thirdly, through the test function effect analysis of AMBPS and other similar algorithms, the improved effect of this algorithm is verified. Finally, from manual tuning PID parameters to off-line and on-line optimizing parameters based on AMBPS algorithm, the optimal control parameters are obtained step by step, and the optimal heading and path following simulation results are achieved. Compared with the results of traditional PID, AMBPS-PID algorithm has a better adaptive control effect on ship motion control, reduces the error of manual tuning parameters and improves efficiency.@en

Ships that equipped with flapped rudders have better manoeuvring performance than ships fitted with traditional spade rudders. Moreover, this advantage is achieved without significantly affecting the ship's resistance during normal cruising. Flapped rudders are, therefore, favourable for ships that require high manoeuvring performance and sail long distance. Nowadays, there is a trend of using twin flapped rudders on newly built inland vessels in the Yangtze River. To properly design these ships and analyse their manoeuvring performance, the hydrodynamic characteristics of the flapped rudders are required. In this paper, a RANS study is performed to analyse the impacts of the three main properties of a flapped rudder on its hydrodynamic coefficients. The target properties are the rudder profile, the flaplinkage ratio (the flapped angle relative to the rudder chord line divided by the applied rudder angle), and the flap-area ratio (the sectional area of the flap divided by the total sectional area). The RANS simulations are carried out with commercial meshing tool ANSYS Meshing and CFD solver ANSYS Fluent.

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