The third Naval Engineering and Ship Control special edition of the Journal of Marine Engineering and Technology aims to present cutting-edge research on naval engineering and ship control, as was presented during the International Naval Engineering Conference and Exhibition (INEC) and the International Ship Control Systems Symposium (iSCSS), held together in Delft in 2022.

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Simulation models of the ship propulsion system play an increasingly important role, for instance in controller design and condition monitoring. However, creation of such simulation models requires significant time and effort. In this paper, the application of deterministic identification techniques on a DC-electric ship drive train is explored as an alternative for data-driven identification techniques that require extensive measured data sets collected over long periods of ship operation. First, a nonlinear and a linear simulation model that represent the dynamic behavior of the propulsion plant are developed, and the main parameters to be identified are defined. Then, a set of experiments on a model scale boat in the bollard pull condition are conducted using an ad hoc experimental setup and data acquisition system. Subsequently, various types of identification techniques are applied, aiming to determine the unknown model parameters. Eventually, a comparison is made between experimental and simulated results, using the different sets of the estimated parameters. The value of the demonstrated approaches lies in the fast determination of unknown system parameters. These parameters can be used in simulation models, which in turn can be used for various purposes such as system controller development and tuning. Furthermore, periodic determination of system parameters can support condition monitoring to detect faults or degradation of the system. The latter point directly deals with the condition-based maintenance issue; in fact, monitoring the propulsion plant parameters over time could allow for better management (and timing) of maintenance. Although the developed ideas are far from ready to be used on the full-scale, the authors believe that the methodologies are promising enough to be developed further towards a full-scale application. @en

This paper presents an effective autonomous follow-the-leader strategy for Azimuthal Stern Drive vessels. The control logic has been investigated from a theoretical point of view. A line-of-sight algorithm is exploited to ensure yaw-check ability, while a speed-check feature is implemented to track the velocity of the target along the path. For this purpose, a linearised manoeuvrability model for azimuthal drive surface vessels is presented. A model-based control synthesis is proposed to ensure the stability of the closed-loop system and robust PID controllers are designed by using Linear Matrix Inequalities technique. The control strategy has been successively validated in two steps, initially by using simulation techniques, and then experimentally using an outdoor scenario with model scale tugs. The path planning, navigation, guidance and control modules are studied, detailed, and digitally implemented on-board of the model scale tugs. The models are supplied with GNSS+INS navigation system. Low-level management and control of Azimuthals angles and shaft revolutions is implemented on-board. High-level decen-tralised path planning, guidance, and control sequence evaluation are dealt with at a remote ground station. In particular, the presented follow-the-leader strategy meets the most generic needs of platooning convoys, and, in the specific instance, of Escort convoy tugs. The operative profile of the latter concerns long-lasting and routine chases with the continuous demand of tuning heading and speed to track the target vessels, until the rare occurrence of an emergency event. In a realistic scenario, the proposed control system would be beneficial for the tug master’s lucidity and alertness, while reducing avoidable risks. At the end of the paper, the results of the experimental campaign are shown to demonstrate the effectiveness of the proposed control logic.

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