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    Wyświetlanie 1-4 z 4
    Tytuł:
    Parameter identification approach using improved teaching and learning based optimization for hub motor considering temperature rise
    Autorzy:
    Li, Yong
    Wang, Yuan
    Zhang, Taohua
    Hu, Han
    Wu, Hao
    Powiązania:
    https://bibliotekanauki.pl/articles/2203368.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    parameters identification
    teaching–learning-based optimization
    hub motor
    temperature rise
    Opis:
    Temperature rise of the hub motor in distributed drive electric vehicles (DDEVs) under long-time and overload operating conditions brings parameter drift and degrades the performance of the motor. A novel online parameter identification method based on improved teaching-learning-based optimization (ITLBO) is proposed to estimate the stator resistance, -axis inductance, -axis inductance, and flux linkage of the hub motor with respect to temperature rise. The effect of temperature rise on the stator resistance, -axis inductance, -axis inductance, and magnetic flux linkage is analysed. The hub motor parameters are identified offline. The proposed ITLBO algorithm is introduced to estimate the parameters online. The Gaussian perturbation function is employed to optimize the TLBO algorithm and improve the identification speed and accuracy. The mechanisms of group learning and low-ranking elimination are established. After that, the proposed ITLBO algorithm for parameter identification is employed to identify the hub motor parameters online on the test bench. Compared with other parameter identification algorithms, both simulation and experimental results show the proposed ITLBO algorithm has rapid convergence and a higher convergence precision, by which the robustness of the algorithm is effectively verified.
    Źródło:
    Metrology and Measurement Systems; 2023, 30, 1; 99--115
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Novel Technique of Optimization for the COCOMO II Model Parameters using Teaching-Learning-Based Optimization Algorithm
    Autorzy:
    Khuat, T. T.
    Le, M. H.
    Powiązania:
    https://bibliotekanauki.pl/articles/309064.pdf
    Data publikacji:
    2016
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    COCOMO II
    cost estimation
    NASA software
    optimization
    teaching-learning-based optimization algorithm
    Opis:
    Software cost estimation is a critical activity in the development life cycle for controlling risks and planning project schedules. Accurate estimation of the cost before the start-up of a project is essential for both the developers and the customers. Therefore, many models were proposed to address this issue, in which COCOMO II has been being widely employed in actual software projects. Good estimation models, such as COCOMO II, can avoid insufficient resources being allocated to a project. However, parameters for estimation formula in this model have not been optimized yet, and so the estimated results are not close to the actual results. In this paper, a novel technique to optimize the coefficients for COCOMO II model by using teaching-learning-based optimization (TLBO) algorithm is proposed. The performance of the model after optimizing parameters was tested on NASA software project dataset. The obtained results indicated that the improvement of parameters provided a better estimation capabilities compared to the original COCOMO II model.
    Źródło:
    Journal of Telecommunications and Information Technology; 2016, 1; 84-89
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Design of an optimal fuzzy controller of an under-actuated manipulator based on teaching-learning-based optimization
    Autorzy:
    Mahmoodabadi, Mohammad Javad
    Yazdizadeh-Baghini, Amineh
    Powiązania:
    https://bibliotekanauki.pl/articles/386516.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
    Tematy:
    optimal controller
    fuzzy control
    teaching-learning-based optimization
    underactuated system
    2R planar horizontal manipulator
    Opis:
    In this paper, an optimal fuzzy controller based on the Teaching-Learning-Based Optimization (TLBO) algorithm has been presented for the stabilization of a two-link planar horizontal under-actuated manipulator with two revolute (2R) joints. For the considered fuzzy control method, a singleton fuzzifier, a centre average defuzzifier and a product inference engine have been used. The TLBO algorithm has been implemented for searching the optimum parameters of the fuzzy controller with consideration of time integral of the absolute error of the state variables as the objective function. The proposed control method has been utilized for the 2R under-actuated manipulator with the second passive joint wherein the model moves in the horizontal plane and friction forces have been considered. Simulation results of the offered control method have been illustrated for the stabilization of the considered robot system. Moreover, for different initial conditions, the effectiveness and the robustness of the mentioned strategy have been challenged.
    Źródło:
    Acta Mechanica et Automatica; 2019, 13, 3; 166-172
    1898-4088
    2300-5319
    Pojawia się w:
    Acta Mechanica et Automatica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Solving a stochastic time-cost-quality trade-off problemby meta-heuristic optimization algorithms
    Autorzy:
    Mohammadi, Mohammad Owais
    Dede, Tayfun
    Grzywiński, Maksym
    Powiązania:
    https://bibliotekanauki.pl/articles/31342639.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Częstochowska
    Tematy:
    stochastyczny kompromis czas-koszt-jakość
    algorytmy optymalizacji
    problemy optymalizacji
    stochastic time-cost-quality trade-off
    non-dominating sorting-II
    teaching-learning-based optimization
    Opis:
    Actual time, cost, and quality of execution options for various activities within a considered project cannot be certainly determined prior to construction, there could be three different values of time and cost for each execution option, namely, optimistic value, most likely or normal value, and pessimistic value; and the quality could be described in linguistic terms.The objective of this research is to optimize time, cost, and quality of construction projects under uncertainty utilizing the program evaluation and review technique. In this study, multi-objective functions are used to decrease total project time and total project cost whilemaximizing overall project quality. For satisfying time-cost-quality trade-off optimization, a multi-objective optimization strategy is required. The non-dominating sorting-II conceptand the crowding distance computation mechanism are combined with the teaching learning-based optimization algorithm to optimize time-cost-quality optimization problems. Non-dominating sorting-II teaching learning-based optimization algorithm is coded in MATLAB to optimize the trade-off between time, cost, and quality optimization problems. In the proposed model, the non-dominating sorting-II approach and crowding distance computationmechanism are responsible for handling objectives effectively and efficiently. Teaching learning-based optimization algorithm’s teacher and learner phases ensure that the searched solution space is explored and exploited. The proposed algorithm is applied to a 13-activity example problem, and the results show that it provides satisfactory results.
    Źródło:
    Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2022, 11; 41-48
    2299-8535
    2544-963X
    Pojawia się w:
    Budownictwo o Zoptymalizowanym Potencjale Energetycznym
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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