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Content available Dynamic positioning capability assessment based on optimal thrust allocation
Piekło Agnieszka, Witkowska Anna, Zubowicz Tomasz
Polish Maritime Research
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2023
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nr 2
28--38
EN
The article presents an efficient method of optimal thrust allocation over the actuators in a dynamically positioned ship, according to the DNV-ST-0111 standard, Level 1. The optimisation task is approximated to a convex problem with linear constraints and mathematically formulated as quadratic programming. The case study is being used to illustrate the use of the proposed approach in assessing the DP capability of a rescue ship. The quadratic programmingbased approach applied for dynamic positioning capability assessment allows for fast calculations to qualitatively compare different ship designs. In comparison with the DNV tool, it gives 100% successful validation for a ship with azimuth thrusters and a pessimistic solution for a ship equipped with propellers with rudders. Therefore, it can be safely applied at an early design stage.
2
Content available An intelligent approach to short-term wind power prediction using deep neural networks
Niksa-Rynkiewicz Tacjana, Stomma Piotr, Witkowska Anna, Rutkowska Danuta, Słowik Adam, Cpałka Krzysztof, Jaworek-Korjakowska Joanna, Kolendo Piotr
Journal of Artificial Intelligence and Soft Computing Research
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2023
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Vol. 13. No. 3
197--210
EN
In this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent Unit), and H-MLP (Hierarchical Multilayer Perceptron). The DNN architectures are part of the Deep Learning Prediction (DLP) framework that is applied in the Deep Learning Power Prediction System (DLPPS). The system is trained based on data that comes from a real wind farm. This is significant because the prediction results strongly depend on weather conditions in specific locations. The results obtained from the proposed system, for the real data, are presented and compared. The best result has been achieved for the GRU network. The key advantage of the system is a high effectiveness prediction using a minimal subset of parameters. The prediction of wind power in wind farms is very important as wind power capacity has shown a rapid increase, and has become a promising source of renewable energies.
3
Content available remote Analysis of data fusion algorithms for the vessel with the dynamic positioning system
Jaroś Krzysztof, Śmierzchalski Roman, Witkowska Anna
Przegląd Elektrotechniczny
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2022
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R. 98, nr 12
35--39
EN
The dynamic positioning (DP) system on the vessel is operated to control the position and heading of the vessel with the use of propellers and thrusters installed on the board. On DP vessels redundant measurement systems of position, heading and the magnitude and direction of environmental forces are required for safety at sea. In this case, a fusion of data is needed from individual measurement devices. The article proposes a new solution data fusion algorithm of particle Kalman filter as a cascade combination of particle filter and extended Kalman filter. The estimation quality of the proposed data fusion algorithm is analysed in comparison with the classic: extended Kalman filter (EKF), nonlinear observer (NO), and particle Kalman filter (PKF). Simulation studies were executed for emergency scenarios to evaluate the robustness of the algorithm analyses to measurement errors.
PL
System dynamicznego pozycjonowania (DP) na statku jest wykorzystywany do sterowania pozycją i kursem statku za pomocą pędników zainstalowanych na pokładzie. Na statkach DP dla zapewnienia bezpieczeństwa na morzu wymagane są redundantne systemy pomiarowe pozycji oraz wielkości i kierunku działania sił środowiskowych. W tym przypadku konieczna jest fuzja danych z poszczególnych urządzeń pomiarowych. W artykule zaproponowano nowy algorytm fuzji danych jako kaskadowe połączenie filtru cząsteczkowego i rozszerzonego filtru Kalmana. Analizowana jest jakość estymacji proponowanego algorytmu fuzji danych w porównaniu z klasycznymi algorytmami: rozszerzonym filtrem Kalmana (EKF), obserwatorem nieliniowym (NO) oraz cząsteczkowym filtrem Kalmana (PKF). Przeprowadzono badania symulacyjne algorytmów fuzji danych dla scenariuszy awaryjnych w celu oceny odporności algorytmów na błędy pomiarowe.
4
Content available Monitoring the gas turbine start-up phase on a platform using a hierarchical model based on multi-layer perceptron networks
Niksa-Rynkiewicz Tacjana, Witkowska Anna, Głuch Jerzy, Adamowicz Marcin
Polish Maritime Research
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2022
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nr 4
123--131
EN
Very often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition of the gas turbine start-up process was proposed, enabling a modular analysis of selected parameters of the process. Real data sets obtained from observations of the turbo-generator set located on a North Sea platform were used.
5
Content available Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network
Niksa-Rynkiewicz Tacjana, Szewczuk-Krypa Natalia, Witkowska Anna, Cpałka Krzysztof, Zalasiński Marcin, Cader Andrzej
Journal of Artificial Intelligence and Soft Computing Research
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2021
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Vol. 11, No. 2
143--155
EN
Artificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper presents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to similar monitoring applications of other industrial dynamic objects.
6
Content available Analysis of impact of ship model parameters on changes of control quality index in ship dynamic positioning system
Rynkiewicz Tacjana Niksa, Witkowska Anna
Polish Maritime Research
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2019
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nr 1
6--14
EN
In this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective function. Simulation investigations were carried out with taking into account integral control quality indices.
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