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Wyszukujesz frazę "Jerome, J." wg kryterium: Autor

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Driver Workload Response to In-Vehicle Device Operations
    Autorzy:
    Jerome, C. J.
    Ganey, H. C. N.
    Mouloua, M.
    Hancock, P. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/91075.pdf
    Data publikacji:
    2002
    Wydawca:
    Centralny Instytut Ochrony Pracy
    Tematy:
    driver distraction
    telematics
    workload
    cellular phones
    obciążenie fizyczne
    telefonia komórkowa
    fizjologia pracy
    kierowcy i maszyniści
    psychologia pracy
    radio
    systemy nawigacji
    Opis:
    A central concern of Intelligent Transportation Systems (ITS) is the effect of in-vehicle devices (e.g., cell phones, navigation systems, radios, etc.) on driver performance and safety. As diverse and innovative technologies are designed and implemented for in-vehicle use, questions regarding the presence and use of these devices assume progressively greater importance. Further concerns for advanced driver training require us to develop and validate reliable and effective procedures for assessing such effects. This work examines a number of candidate procedures, in particular the evaluation of change in cognitive workload as a strategy by which such goals might be achieved.
    Źródło:
    International Journal of Occupational Safety and Ergonomics; 2002, 8, 4; 539-546
    1080-3548
    Pojawia się w:
    International Journal of Occupational Safety and Ergonomics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Algebraic Riccati equation based Q and R matrices selection algorithm for optimal LQR applied to tracking control of 3rd order magnetic levitation system
    Autorzy:
    Kumar E, V.
    Jerome, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/140600.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    algebraic Riccatti equation
    linear quadratic regulator
    magnetic levitation
    system
    weighting matrices
    command following
    cost function
    Opis:
    This paper presents an analytical approach for solving the weighting matrices selection problem of a linear quadratic regulator (LQR) for the trajectory tracking application of a magnetic levitation system. One of the challenging problems in the design of LQR for tracking applications is the choice of Q and R matrices. Conventionally, the weights of a LQR controller are chosen based on a trial and error approach to determine the optimum state feedback controller gains. However, it is often time consuming and tedious to tune the controller gains via a trial and error method. To address this problem, by utilizing the relation between the algebraic Riccati equation (ARE) and the Lagrangian optimization principle, an analytical methodology for selecting the elements of Q and R matrices has been formulated. The novelty of the methodology is the emphasis on the synthesis of time domain design specifications for the formulation of the cost function of LQR, which directly translates the system requirement into a cost function so that the optimal performance can be obtained via a systematic approach. The efficacy of the proposed methodology is tested on the benchmark Quanser magnetic levitation system and a detailed simulation and experimental results are presented. Experimental results prove that the proposed methodology not only provides a systematic way of selecting the weighting matrices but also significantly improves the tracking performance of the system.
    Źródło:
    Archives of Electrical Engineering; 2016, 65, 1; 151-168
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An adaptive particle swarm optimization algorithm for robust trajectory tracking of a class of under actuated system
    Autorzy:
    Kumar, V. E.
    Jerome, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/141105.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    inverted pendulum
    LQR controller
    particle swarm optimization (PSO)
    genetic algorithm
    adaptive inertia weight factor
    state feedback control
    Opis:
    This paper presents an adaptive particle swarm optimization (APSO) based LQR controller for optimal tuning of state feedback controller gains for a class of under actuated system (Inverted pendulum). Normally, the weights of LQR controller are chosen based on trial and error approach to obtain the optimum controller gains, but it is often cumbersome and tedious to tune the controller gains via trial and error method. To address this problem, an intelligent approach employing adaptive PSO (APSO) for optimum tuning of LQR is proposed. In this approach, an adaptive inertia weight factor (AIWF), which adjusts the inertia weight according to the success rate of the particles, is employed to not only speed up the search process but also to increase the accuracy of the algorithm towards obtaining the optimum controller gain. The performance of the proposed approach is tested on a bench mark inverted pendulum system, and the experimental results of APSO are compared with that of the conventional PSO and GA. Experimental results prove that the proposed algorithm remarkably improves the convergence speed and precision of PSO in obtaining the robust trajectory tracking of inverted pendulum.
    Źródło:
    Archives of Electrical Engineering; 2014, 63, 3; 345-365
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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