Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "nonlinear state space model" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-3 z 3
    Tytuł:
    Nonlinear state-space predictive control with on-line linearisation and state estimation
    Autorzy:
    Ławryńczuk, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330330.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    process control
    model predictive control
    nonlinear state space model
    extended Kalman filter
    online linearization
    proces sterowania
    model sterowania predykcyjnego
    model przestrzeni stanów
    rozszerzony filtr Kalmana
    Opis:
    This paper describes computationally efficient model predictive control (MPC) algorithms for nonlinear dynamic systems represented by discrete-time state-space models. Two approaches are detailed: in the first one the model is successively linearised on-line and used for prediction, while in the second one a linear approximation of the future process trajectory is directly found on-line. In both the cases, as a result of linearisation, the future control policy is calculated by means of quadratic optimisation. For state estimation, the extended Kalman filter is used. The discussed MPC algorithms, although disturbance state observers are not used, are able to compensate for deterministic constant-type external and internal disturbances. In order to illustrate implementation steps and compare the efficiency of the algorithms, a polymerisation reactor benchmark system is considered. In particular, the described MPC algorithms with on-line linearisation are compared with a truly nonlinear MPC approach with nonlinear optimisation repeated at each sampling instant.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 833-847
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Offset-free nonlinear Model Predictive Control with state-space process models
    Autorzy:
    Tatjewski, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/229638.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    nonlinear control
    predictive control
    offset-free control
    state-space model
    state estimation
    Opis:
    Offset-free model predictive control (MPC) algorithms for nonlinear state-space process models, with modeling errors and under asymptotically constant external disturbances, is the subject of the paper. The main result of the paper is the presentation of a novel technique based on constant state disturbance prediction. It was introduced originally by the author for linear state-space models and is generalized to the nonlinear case in the paper. First the case with measured state is considered, in this case the technique allows to avoid disturbance estimation at all. For the cases with process outputs measured only and thus the necessity of state estimation, the technique allows the process state estimation only - as opposed to conventional approach of extended process-and-disturbance state estimation. This leads to simpler design with state observer/filter of lower order and, moreover, without the need of a decision of disturbance placement in the model (under certain restrictions), as in the conventional approach. A theoretical analysis of the proposed algorithm is provided, under applicability conditions which are weaker than in the conventional approach. The presented theory is illustrated by simulation results of nonlinear processes, showing competitiveness of the proposed algorithms.
    Źródło:
    Archives of Control Sciences; 2017, 27, 4; 595-615
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An integer optimization model and algorithms to support the cost-revenue study and provisory designing warehouses or other storage objects
    Autorzy:
    Miatselski, M.
    Staruch, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/298439.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Warmińsko-Mazurski w Olsztynie
    Tematy:
    warehouse design
    cost-revenue recognition
    state space
    model
    algorithm
    nonlinear programming
    integer programming
    Opis:
    An optimization model for the cost–revenue study at the stage of system analysis and preliminary designs of storage objects such as warehouses, containers, packs and similar objects are developed. Our assumptions motivated by warehouses design lead us to a nonlinear integer optimization problem with the only basic constraint. We present algorithmic methods for obtaining the exact solution to the general problem with emphasizing the special case when both the objective and the constraint functions are increasing. The results of the paper may be used in developing software tools intended for supporting designers.
    Źródło:
    Technical Sciences / University of Warmia and Mazury in Olsztyn; 2018, 21(4); 257-269
    1505-4675
    2083-4527
    Pojawia się w:
    Technical Sciences / University of Warmia and Mazury in Olsztyn
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies