No abstract

In this paper, a distributed control approach is proposed to enable fuel-efficient Vessel Train Formations (VTF) in inland waterways and port areas for addressing the efficiency and environmental issues of transport over water. For path tracking, collision avoidance, and consensus over the VTF speed a distributed Model Predictive Control (MPC) algorithm is adopted which uses the Alternating Direction Method of Multipliers (ADMM) to guarantee path following and consensus between vessels. The all-electric Direct Current (DC) configuration is considered for the Power and Propulsion Systems (PPS) of the autonomous vessels under study. Considering their PPS specification, the vessels negotiate with each other to agree on the most efficient speed for all the vessels in the VTF. Simulation results suggest that a significant amount of fuel saving can be obtained by using the proposed approach.

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 decentralised 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.

The future autonomous ships will be operating in an environment where different autonomous and nonautonomous 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.

No abstract

Floating structures have raised interest in the recent years for different applications, from living and farming at sea to renewable energy production. To support the logistics on the floating structures, floating cranes are necessary and their designs are constantly improved. Increasing developments in the automation industry paved the way for automated crane operations. In this work, motion control of a smart crane is presented with particular attention to the performance under wave motion. In this research, a scaled down, two-dimensional mathematical model of a gantry crane is derived using Lagrangian mechanics and DC motors dynamics. This results in a nonlinear system that is capable of simultaneous traversing and hoisting a container. The system is simulated in MATLAB Simulink environment and a proportional-derivative control and a state feedback control are designed and implemented. Their robustness is explored by modelling sensor behavior, external disturbances and floating platform dynamics. Both control strategies were able to keep stability in a disturbed system. During simulation, the sway angles never exceed 10 degrees. Smaller oscillations occurred using the state feedback control. Therefore, it creates a smoother response compared to the proportional derivative control, which ultimately translates to increased safety, turnover rate and durability of the crane.

No abstract