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Katedra Automatyki

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Katalog Publikacji

Rok 2023
  • Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
    Publikacja

    - Rok 2023

    The presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....

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  • Identification of ship’s hull mathematical model with numerical methods
    Publikacja

    - Rok 2023

    The modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...

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  • DYNAMIC POSITIONING CAPABILITY ASSESSMENT BASED ON OPTIMAL THRUST ALLOCATION

    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....

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  • An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
    Publikacja

    - Journal of Artificial Intelligence and Soft Computing Research - Rok 2023

    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...

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