Modeling is the most important component in predictive controller design. It should predict outputs precisely and fast. Thus, it must be adequate for the ship dynamics while having as simple a structure as possible. In a good ship model the standard deviation of a particular coefficient should not exceed $10\%$ of its value. Fitting the validation data to $80\%$ for short-term prediction and $65\%$ for long-term prediction is treated as a declared benchmark for model usage in ship course predictive controller. Regularization was proposed to ensure better state-space models to fit the real ship dynamics and more accurate standard deviation value control. Usage of the simulation results and real-time trials, as model estimation and validation data, respectively, during the identification procedure is proposed. In the first step a predictive linear model is identified conventionally, and then coefficients are regularized, based on the validation data, using a genetic algorithm. Particular linearized model coefficient standard deviations were decreased from more than $100\%$ of their values to approximately $5\%$ of them using genetic algorithm tuning. Moreover, the proposed method eliminated model output signal oscillations, which were observed during the validation process based on experimental data, gained during ship trials. Improved mapping of ship dynamics was achieved. Fit to validation data increased from $71\%$ and $54\%$ to $89\%$ and $76\%$, respectively, for short-term and long-term prediction. The proposed method, which may be applied to real applications, is easily applicable and reliable. The tuned model is sufficiently suited to plant dynamics and may be used for future predictive control purposes.

The concept of the Marine Autonomous Surface Ship (MASS) requires new solutions in many areas: from law, through economics, social sciences, environmental issues to the technology and even ethics. It also plays a central role in the work of numerous research teams dealing with the ship motion control systems. This article presents the results of the experiments with application of the selected control methods in automatic steering of the movement of an autonomous ship in the two regimes: during the maneuvers at low speed (in a harbor confined waters) and during the lake trials in open water conditions. In the first case, multidimensional state controller synthesized with Linear Matrix Inequalities (LMI) algorithms was used, while, in the second case, Model Predictive Control (MPC) control was adopted. The object for which the experiments were carried out was 1:24 scale model of the Liquefied Natural Gas (LNG) carrier. The paper presents also the design of the measurement and control system and the user interface. The experiments were conducted in the natural conditions on the lake. The results of the experiments indicate the fundamental role of the measurement system in the process of controlling an autonomous ship.

This work is devoted to the second order rational Bézier curve coefficients estimation. We present the methodology of unique coefficients for each type of ship computation. In the presented formulas of ship’s length, a draft and angular path combined with a drift path are used. This approach leads to the simplest and most accurate Maritime Autonomous Surface Ships (MASS) path modeling. Three rational curve control points are waypoints (WPT). Using WPTs as curve control points allows integrating a trajectory intuitive for the navigator with a path predicting model used as a reference in the control system. Research was done based on real-time data originating from the MASS autonomous trajectory tracking system. The presented mathematical modeling tool may be treated as the best way of future trajectory prediction due to low computation power required.

The article presents the synthesis of a multi-layer group control system for a marine autonomous surface vessel with the use of modern control theory methods. First, an evolutionary programming algorithm for determining the optimal route path was presented. Then the algorithms—dynamic programming with neural state constraints, ant colony, and neuro-phase safe control algorithms—were presented. LMI and predictive line-of-sight methods were used for optimal control. The direct control layer is implemented in multi-operations on the principle of switching. The results of the computer simulation of the algorithms were used to assess the quality control.

The forces and moments acting on a marine vessel caused by the wind are most often modeled based on its speed measured at a standard 10 m above the sea level. There exist numerous well-known methods for modeling wind speed in such conditions. These models, by nature, are inadequate for simulating wind disturbances for free-running scale ship models sailing on lakes. Such scale models are being used increasingly for design and testing modern ship motion control systems. The paper describes the hardware and methodology used in measuring wind speed at low altitudes above the lake level. The system consists of two ultrasonic anemometers supplemented with wave sensor acting as a capacitor immersed partially in the water. Obtained measurement results show clear similarity to the values gathered during full-scale experiments. Analysis of the power spectral density functions of turbulence measured for different mean wind speeds over the lake, indicates that, at the present stage of research, the best model of wind turbulence at low altitude above the lake level can be obtained by assembling four of the known, standard turbulence models.

In the process of ship motion control system design, it is necessary to take into account the impact of environmental disturbances such as winds, waves and sea currents. The commonly used representatives of wave influences in this area are the unidirectional wave power spectral density functions describing sea waves of different form: long-crested, fully developed waves, developing wind waves or multi-modal waves (e.g., with swell). The existing standard PSD models describe the surge of open sea or ocean. However, they are inadequate in the case of control system testing of scale ship models for sailing in open water areas such as lakes or test pools. This paper presents a study of wind-generated wave PSD estimations for a small lake used as a test area for free-running scale ships. The publication provides a brief overview of the wave spectral density functions commonly used for control system design. A measurement instrument using the idea of a water-induced variable capacitance that works synchronously with the wind sensors is also described. The process of collected data analysis is presented. As a result of the study, a series of empirical spectral density functions of lake waves for different wind speeds are obtained. They correspond to the rescaled, two-parametric ITTC model.