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Two different propulsion systems are analyzed from point of view of future control applications. The traditional one consists of a pushing single screw propeller and a blade rudder. The other system is based on pod (pods): pulling or pushing ones. The equations describing forces and moments generated in both systems, are presented. Exemplary results of a simulation in comparison to the real-time experiments for two ships are also shown
This paper presents the application of the reinforcement learning algorithms to the task of autonomous determination of the ship trajectory during the in-harbour and harbour approaching manoeuvres. Authors used Markov decision processes formalism to build up the background of algorithm presentation. Two versions of RL algorithms were tested in the simulations: discrete (Q-learning) and continuous form (Least-Squares Policy Iteration). The results show that in both cases ship trajectory can be found. However discrete Q-learning algorithm suffered from many limitations (mainly curse of dimensionality) and practically is not applicable to the examined task. On the other hand, LSPI gave promising results. To be fully operational, proposed solution should be extended by taking into account ship heading and velocity and coupling with advanced multi-variable controller
The paper presents the physical model of the sea-going ship. The wooden hull of this ship was obtained from Ship Design and Research Centre and next rebuilt and reconstructed for future tests of the different control systems in the real-time experiments. The paper describes the succeeding stages of the work, steering and driving devices installed on board, power electric diagrams and navigational equipment designated for ship. The range of the possible applications of the constructed vessel are presented at the end of the paper
The paper presents software environement for fast prototyping and verification of motion control systems for ship. The environement is prepared for isomorphic reduced ship model which is used for training and in research in a area of ship motion control. The control system is build using Matlab-Simulink-xPC package which simplifies and accellerates design and verification of new control algorithms. The systems was prepared also for Hardware-in-the-loop trials when a designed control system is tested inside a virtual environment instead of real actuators, disturbances, communication and measurement devices
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