Camilla Fruzzetti

1. With the rise of containerisation and the emergence of the offshore oil & gas industry in the 1960s, the ocean has become a hub of economic activities, which have experienced an exponential grow...

Autonomous electric ferries offer an eco-friendly solution for sustainable and intelligent urban mobility. Currently, these ferries are undergoing successful trial operations on short routes for passenger transportation in European and Scandinavian cities. This paper presents experimental results on model identification, thrust allocation (TA), and dynamic positioning (DP) system for the milliAmpere1 (mA1) autonomous electric ferry prototype. The mA1 is a small prototype ferry used as a test platform in several research projects at the Norwegian University of Science and Technology (NTNU). It recently went through a system upgrade and is now equipped with four symmetrically distributed azimuth thrusters. These new systems require a new mathematical model and a reliable DP and TA system to enable autonomous operation. The DP system is responsible for calculating the total force and moment required to keep position or move between waypoints. At the same time, the TA algorithm coordinates the thrusters to ensure that the resulting force they generate matches the request from the DP control algorithm. The DP is designed with a horizontal plane control law, using a feedforward plus feedback control. The TA is formulated as a quadratic programming problem, which includes cost functions for power consumption. A third-order reference guidance system is implemented to ensure smooth and continuous signals for the DP desired position, velocity, and acceleration. Additionally, system model identification was performed to determine the parameters of the actuator dynamics. Full-scale trials were conducted to evaluate the performance of the proposed system in a sheltered basin situated in Trondheim, Norway, under low-wind conditions. The field trial results indicate that the proposed approach successfully stabilized and maintained a desired trajectory.

Environmental disturbances represent significant challenges to the performance and accuracy of autonomous systems, especially in marine environments, where their impact varies based on disturbance severity and the employed guidance law. This paper comprehensively investigates a marine target tracking system using time-domain simulations incorporating realistic environmental disturbances. Three guidance laws and four key performance indicators are analysed to evaluate system performance under disturbed and ideal conditions. A robust and systematic evaluation pipeline is developed and applied to a case study featuring a scaled tugboat model. This approach provides a reliable method to assess tracking accuracy and robustness in adverse conditions. The results are selected from a wide range of possibilities to show the effect of the disturbances on the selected target tracking motion control scenario with two manoeuvres and two environmental conditions. The results are measured through the selected key performance indicators, and several phases are identified for each manoeuvre to extend the analysis not only to the global KPI values but also to the partial values of defined phases. They reveal the quantitative effects of environmental disturbances, exposing different system behaviours and trends. These findings demonstrate the effectiveness of the proposed pipeline in quantifying tracking system performance, delivering useful understandings of the system under environmental disturbances. The broader implications of this study are substantial, offering enhanced predictive accuracy for the performance of the analysed systems, particularly in the context of target tracking. Furthermore, introducing numerical key performance indicators facilitates a more rigorous comparison of different system characteristics, enabling informed decisions in designing and optimising autonomous operations in challenging environments.

A Dynamic Positioning system automatically maintains both the position and heading of a vessel by using its thrusters in the presence of external disturbances. This goal is ensured by a controller that compensates for the environmental disturbances and computes the proper set-points for each actuator. The core of such a system is composed of force and thrust allocation modules that tailor the required forces and moment over the available actuators. The propulsion systems used are often over-actuated and the thrust allocation algorithm implies an infinite number of solutions since it is impossible to solve analytically the problem. Over the years efforts from the research community dealt with the optimization in terms of accuracy, energy consumption, and maintenance with innovative allocation strategies were investigated. However, no publications or rules indicate the procedure for the evaluation of exhaust gas emission during dynamic positioning operations. For such a reason, the paper aims to develop an optimization procedure that includes an ad-hoc objective function with relative non-linear constraints for the thrust allocation logic that tends to minimize the actuators’ thrust. The procedure accounts for non-linear hydrodynamic effects on the thrust generation, including thruster-thruster and thruster-hull interactions, to obtain the most realistic results as possible. Moreover, following the IMO suggestions, the production of greenhouses gases emissions is evaluated in probabilistic terms. The proposed approach provides indicators in terms of yearly operability, fuel consumption, and environmental footprint during dynamic positioning operations that could be used for proper decisions in ship deployment.