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    Wyświetlanie 1-2 z 2
    Tytuł:
    Derivative free optimal thrust allocation in ship dynamic positioning based on direct search algorithms
    Autorzy:
    Valčić, M.
    Prpić-Oršić, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/116991.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    algorithm
    dynamic positioning
    direct search algorithms
    sequential quadratic programing (SQP)
    Singular Values Decomposition (SVD)
    Lagrangian Multiplier Method (LMM)
    Direct Search (DS)
    Mesh Adaptive Direct Search (MADS)
    Opis:
    In dynamic positioning systems, nonlinear cost functions, as well as nonlinear equality and inequality constraints within optimal thrust allocation procedures cannot be handled directly by means of the solvers like industry-standardized quadratic programing (QP), at least not without appropriate linearization technique applied, which can be computationally very expensive. Thus, if optimization requirements are strict, and problem should be solved for nonlinear objective function with nonlinear equality and inequality constraints, than one should use some appropriate nonlinear optimization technique. The current state-of-the-art in nonlinear optimization for gradient-based algorithms is surely the sequential quadratic programing (SQP), both for general applications and specific thrust allocation problems. On the other hand, in recent time, one can also notice the increased applications of gradient-free optimization methods in various engineering problems. In this context, the implementation of selected derivative free direct search algorithms in optimal thrust allocation is proposed and discussed in this paper, and avenues for future research are provided.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2020, 14, 2; 309-314
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parameter identification of ship maneuvering models using recursive least square method based on support vector machines
    Autorzy:
    Zhu, M.
    Hahn, A.
    Wen, Y.
    Bolles, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/116455.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    ship manoeuvering
    recursive least square method
    ship manoeuvering model
    ship maneuverability prediction
    Support Vector Machines (SVM)
    empirical mode decomposition (EMD)
    Computational Fluid Dynamics (CFD)
    Extended Kalman Filter (EKF)
    Opis:
    Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS), are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM), is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD) are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 1; 23-29
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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