Control of Dynamic Positioning System with Disturbance Observer for Autonomous Marine Surface Vessels

The main goal of the research is to design an efficient controller for a dynamic positioning system for autonomous surface ships using the backstepping technique for the case of full-state feedback in the presence of unknown external disturbances. The obtained control commands are distributed to each actuator of the overactuated vessel via unconstrained control allocation. The numerical hydrodynamic model of CyberShip I and the model of environmental disturbances are applied to simulate the operation of the ship control system using the time domain analysis. Simulation studies are presented to illustrate the effectiveness of the proposed controller and its robustness to external disturbances.

Artificial Intelligence-Based Methods for Decision Support to Avoid Collisions at Sea

Ship collisions cause major losses in terms of property, equipment, and human lives. Therefore, more investigations should be focused on this problem, which mainly results from human error during ship control. Indeed, to reduce human error and considerably improve the safe traffic of ships, an intelligent tool based on fuzzy set theory is proposed in this paper that helps navigators make fast and competent decisions in eventual collision situations. Moreover, as a result of selecting the shortest collision avoidance trajectory, our tool minimizes energy consumption. The main aim of this paper was the development of a decision-support system based on an artificial intelligence technique for safe ship trajectory determination in collision situations. The ship’s trajectory optimization is ensured by multistage decision making in collision situations in a fuzzy environment. Furthermore, the navigator’s subjective evaluation in decision making is taken into account in the process model and is included in the modified membership function of constraints. A comparative analysis of two methods, i.e., a method based on neural networks and a method based on the evolutionary algorithm, is presented. The proposed technique is a promising solution for use in real time in onboard decision-support systems. It demonstrated a high accuracy in finding the optimal collision avoidance trajectory, thus ensuring the safety of the crew, property, and equipment, while minimizing energy consumption.

Ship control in storm conditions

Приведены выражения для определения периодов собственных поперечных и продольных колебаний судна, как точные, так и приближённые, но в тоже время достаточные для их практического использования на судне. Представлены формулы для расчёта поперечной метацентрической высоты после принятия груза судном перед выходом в море. Выведены формулы для определения критических зон резонансной качки по крену и дифференту, как по скорости судна, так и по курсовому углу по отношению к направлению распространения штормового волнения моря. Представлены формулы для определения кажущегося периода встречи судна с волной, которые являются основой для расчёта резонансных зон. Выведенные соотношения для определения зоны резонанса по скорости судна при заданном курсовом угле и по курсовому углу при заданной скорости судна представлены при условии известного периода штормового волнения моря и курсового угла судна по отношению к направлению распространения волнения моря. Приведены формулы для определения амплитуды качки в условиях резонанса, если отношение периода собственных колебаний судна к кажущемуся периоду волны находится в пределах 0,7 – 1,3. Представлены выражения для определения амплитуд качки по крену и дифференту, вызывающие морскую болезнь у персонала, а также критические значения боковых перегрузок, влияющих на правильность его действия. Expressions for determining the periods of the natural transverse and longitudinal vibrations of the vessel, both exact and approximate, are given, but at the same time sufficient for their practical use on the vessel. The formulas for calculating the transverse metacentric height after the cargo has been accepted by the vessel before going to sea are presented. Formulas are derived for determining the critical zones of resonant pitching in terms of roll and trim, both in terms of the ship's speed and in the heading angle in relation to the direction of propagation of storm waves of the sea. The formulas for determining the apparent period of the ship's meeting with the wave are presented, which are the basis for calculating the resonance zones. The derived relations for determining the resonance zone by the speed of the vessel at a given heading angle and by the heading angle at a given speed of the vessel are presented under the condition of a known period of stormy sea waves and the heading angle of the vessel in relation to the direction of propagation of sea waves. Formulas are given for determining the amplitude of pitching under resonance conditions if the ratio of the period of natural oscillations of the vessel to the apparent period of the wave is within 0.7 - 1.3. Expressions for determining the amplitudes of roll and pitch that cause motion sickness in personnel, as well as the critical values of lateral g-forces that affect the correctness of its action, are presented.

Development of Algorithms for Identifying Parameters of the Maritime Vessel Motion Model in Operating Conditions with Elements of Intellectual Analysis

The article examines the synthesis of algorithms for the estimation of the random parameters of ship movement models, based on measured information in field tests. In addition, accuracy analysis of the synthesized algorithms is provided. The derived algorithms are relatively simple and allow highly precise unknown parameters for estimation of ship motion models at the non-real-time scale to be obtained using the measurements recorded in field tests. The results can be used in the construction of automated ship control systems, or in the development of navigation simulators and the creation of ship models.

Computational Intelligence in Marine Control Engineering Education

This paper presents a new approach to the existing training of marine control engineering professionals using artificial intelligence. We use optimisation strategies, neural networks and game theory to support optimal, safe ship control by applying the latest scientific achievements to the current process of educating students as future marine officers. Recent advancements in shipbuilding, equipment for robotised ships, the high quality of shipboard game plans, the cost of overhauling, dependability, the fixing of the shipboard equipment and the requesting of the safe shipping and environmental protection, requires constant information on recent equipment and programming for computational intelligence by marine officers. We carry out an analysis to determine which methods of artificial intelligence can allow us to eliminate human subjectivity and uncertainty from real navigational situations involving manoeuvring decisions made by marine officers. Trainees learn by using computer simulation methods to calculate the optimal safe traverse of the ship in the event of a possible collision with other ships, which are mapped using neural networks that take into consideration the subjectivity of the navigator. The game-optimal safe trajectory for the ship also considers the uncertainty in the navigational situation, which is measured in terms of the risk of collision. The use of artificial intelligence methods in the final stage of training on ship automation can improve the practical education of marine officers and allow for safer and more effective ship operation.