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    Wyświetlanie 1-4 z 4
    Tytuł:
    Model predictive control of four-leg three-level flying capacitor converter: influence of model parameter mismatch
    Autorzy:
    Antoniewicz, K.
    Rafał, K.
    Jasiński, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/1193479.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    multilevel converter
    current control
    model predictive control
    MPC
    shunt active power filter
    SAPF
    Opis:
    This paper presents a control method for a four-leg three-level flying capacitor converter (FCC) operating as a shunt active power filter (SAPF), based on model predictive control with finite number of control states (FS-MPC). Current control and capacitor voltage balancing are described. Influence of the mismatch of the inductive filter model parameters on the current control precision is analysed. Results are supported by the experimental waveforms obtained with a 10kVA set-up.
    Źródło:
    Power Electronics and Drives; 2018, 3, 38; 1-9
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Disturbance modeling and state estimation for offset-free predictive control with state-space process models
    Autorzy:
    Tatjewski, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/330146.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    model predictive control
    state space model
    disturbance rejection
    state observer
    Kalman filter
    sterowanie predykcyjne
    model przestrzeni stanów
    eliminacja zakłóceń
    obserwator stanu
    filtr Kalmana
    Opis:
    Disturbance modeling and design of state estimators for offset-free Model Predictive Control (MPC) with linear state-space process models is considered in the paper for deterministic constant-type external and internal disturbances (modeling errors). The application and importance of constant state disturbance prediction in the state-space MPC controller design is presented. In the case with a measured state, this leads to the control structure without disturbance state observers. In the case with an unmeasured state, a new, simpler MPC controller-observer structure is proposed, with observation of a pure process state only. The structure is not only simpler, but also with less restrictive applicability conditions than the conventional approach with extended process-and-disturbances state estimation. Theoretical analysis of the proposed structure is provided. The design approach is also applied to the case with an augmented state-space model in complete velocity form. The results are illustrated on a 2 x 2 example process problem.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 313-323
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cascade tanks system identification for robust predictive control
    Autorzy:
    Jakowluk, Wiktor
    Jaszczak, Sławomir
    Powiązania:
    https://bibliotekanauki.pl/articles/2173722.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    application-oriented input design
    Kalman filter
    model predictive control
    MPC
    system identification
    projektowanie wejścia zorientowanego na aplikację
    filtr Kalmana
    sterowanie predykcyjne modelu
    identyfikacja systemu
    Opis:
    The main goal of estimating models for industrial applications is to guarantee the cheapest system identification. The requirements for the identification experiment should not be allowed to affect product quality under normal operating conditions. This paper deals with ensuring the required liquid levels of the cascade system tanks using the model predictive control (MPC) method. The MPC strategy was extended with the Kalman filter (KF) to predict the system’s succeeding states subject to a reference trajectory in the presence of both process and measurement noise covariances. The main contribution is to use the application-oriented input design to update the parameters of the model during system degradation. This framework delivers the least-costly identification experiment and guarantees high performance of the system with the updated model. The methods presented are evaluated both in the experiments on a real process and in the computer simulations. The results of the robust MPC application for cascade system water levels control are discussed.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143646
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    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
      Wyświetlanie 1-4 z 4

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