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Wyszukujesz frazę "state predictive control" wg kryterium: Temat

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    Wyświetlanie 1-9 z 9
    Tytuł:
    Design of the state predictive model following control system with time-delay
    Autorzy:
    Wang, D.
    Wu, S.
    Okubo, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/907660.pdf
    Data publikacji:
    2009
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie predykcyjne
    opóźnienie
    kontrola przeciążeń
    state predictive control
    time delay
    model following control system (MFCS)
    TCP/AQM network
    congestion control
    Opis:
    Time-delay systems exist in many engineering fields such as transportation systems, communication systems, process engineering and, more recently, networked control systems. It usually results in unsatisfactory performance and is frequently a source of instability, so the control of time-delay systems is practically important. In this paper, a design of the state predictive model following control system (PMFCS) with time-delay is discussed. The bounded property of the internal states for the control is given, and the utility of this control design is guaranteed. Finally, examples are given to illustrate the effectiveness of the proposed method, and state predictive control techniques are applied to congestion control synthesis problems for a TCP/AQM network.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2009, 19, 2; 247-254
    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:
    Dynamic Algorithm for Linear Quadratic Gaussian Predictive Control
    Autorzy:
    Ordys, A. W.
    Hangstrup, M. E.
    Grimble, M. J.
    Powiązania:
    https://bibliotekanauki.pl/articles/911167.pdf
    Data publikacji:
    2000
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    przestrzeń fazowa
    sterowanie wielowymiarowe
    sterowanie predykcyjne
    state-space design
    multivariable control
    linear quadratic Gaussian predictive control
    generalized predictive control
    Opis:
    In this paper, the optimal control law is derived for a multi-variable state-space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady-state controller. Knowledge of future reference values is incorporated into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how the well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive controllers is that, based on stabilizing properties of LQG control, it enables a systematic approach to selection of the design parameters to yield a stable closed-loop system. The system model considered in this paper can be further extended toalso include direct feed-through and knowledge about future external inputs.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2000, 10, 2; 227-244
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cooperation of model predictive control with steady-state economic optimisation
    Autorzy:
    Ławryńczuk, M.
    Marusak, P. M.
    Tatjewski, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/971007.pdf
    Data publikacji:
    2008
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    sterowanie optymalne
    optymalizacja
    predictive control
    optimal control
    optimisation
    economic steady-state optimisation
    nonlinear control systems
    constrained control
    Opis:
    The problem of cooperation of Model Predictive Control (MPC) algorithms with steady-state economic optimisation is investigated in this paper. It is particularly important when the dynamics of disturbances is comparable with the dynamics of the process, since in such a case the classical hierarchical multilayer structure is likely to be not efficient and give the economic yield smaller than expected. This is because the economic nonlinear optimisation problem cannot be then solved on-line to update the optimal operating point as frequently as needed. On the other hand, simple target set-point optimisation based on linear models can be also insufficiently accurate. This paper introduces approximate formulations of the target set-point optimisation problem which tightly cooperates with the MPC and is solved as frequently as the MPC controller executes. Linear, linear-quadratic and piecewise-linear formulations are discussed, tuning guidelines are also given.
    Źródło:
    Control and Cybernetics; 2008, 37, 1; 133-158
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    High-performance PMSM servo-drive with constrained state feedback position controller
    Autorzy:
    Tarczewski, T.
    Skiwski, M.
    Niewiara, L. J.
    Grzesiak, L. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/200374.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    constrained control
    model predictive approach
    permanent magnet synchronous motor
    position control
    state feedback control
    model predykcyjny
    silnik synchroniczny z magnesem trwałym
    sprzężenie zwrotne
    Opis:
    This paper describes high-performance permanent magnet synchronous motor (PMSM) servo-drive with constrained state feedback (SFC) position controller. Superior behavior of the control system has been achieved by applying SFC with constraints handling method based on a posteriori model predictive approach (MPAC). The concept utilizes predictive equations obtained from discrete-time model of the PMSM to compute control signals which generate admissible values of the future state variables. The novelty of the proposed solution lies in the limitation of several state-space variables in servo-drive control system. Since MPAC has firstly been applied to limit more than one state-space variable of the plant, necessary conditions for introducing constraints into multivariable control system with SFC are depicted. Due to the low complexity of proposed algorithm, a low cost microprocessor, STM32F4, is employed to execute the state feedback position control with model predictive approach to constraints handling. Experimental results show that the proposed control method provides superior performance of PMSM servodrive with modern SiC based voltage source inverter (VSI).
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 1; 49-58
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optymalizacja wzmocnienia obserwatora Luenbergera w układzie predykcyjnego sterowania systemem aktywnego zawieszenia
    Luenberger Observer Gain Optimization in Model Predictive Control System for Car Active Suspension
    Autorzy:
    Maślak, Grzegorz
    Orłowski, Przemysław
    Powiązania:
    https://bibliotekanauki.pl/articles/2068639.pdf
    Data publikacji:
    2021
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    obserwator stanu
    sterowanie predykcyjne
    optymalizacja obserwatora
    zawieszenie aktywne
    state observer
    model predictive control
    observer optimization
    active suspension
    Opis:
    Układy sterowania wykorzystujące regulatory predykcyjne bardzo często wymagają wprowadzenia do ich struktury mechanizmów umożliwiających estymację niedostępnego pomiarowo stanu obiektu. Zależnie od przypadku nieosiągalne mogą być informacje o różnej liczbie zmiennych stanu. Szeroko stosowanymi układami pozwalającymi na uzyskanie niezbędnych informacji o stanie obiektu są obserwator Luenbergera oraz różnego typu filtry Kalmana. Autorzy proponują metodę syntezy obserwatora Luenbergera opartą na optymalizacji wzmocnienia owego obserwatora, przy czym wyznacznik jakości uzyskanego wzmocnienia wykorzystywanego przez optymalizator stanowi ogólna jakość regulacji układu sterowania z regulatorem predykcyjnym. Opracowana metoda pozwala na uzyskanie, z punktu widzenia przyjętego kryterium, obserwatora o właściwościach lepszych niż analogiczny układ, którego syntezę przeprowadzono przy wykorzystaniu równania Sylvestera oraz klasycznego filtru Kalmana, mimo występowania zakłóceń. Metoda zaprezentowana zostanie na przykładzie układu predykcyjnego sterowania systemem aktywnego zawieszenia.
    MPC Driven control systems very often are requiring the introduction of a mechanism predicting the state of the object unavailable for measurements. Depending on the case, a different number of state variables will be unobtainable. Widely used systems to obtain essential data of the condition of an object are Luenberger state observer and different types of Kalman filters. The authors propose a new method of Luenberger observer synthesis based on Luenberger gain optimization using performance index corresponding to generalized system performance. The developed method allows us to obtain better-performing observer from the point of view of the adopted criterion, compared to similar estimators derived from the Sylvester equation and classic Kalman filters, even despite the occurrence of disturbances. The developed method will be presented on an example of an active suspension system with MPC.
    Źródło:
    Pomiary Automatyka Robotyka; 2021, 25, 2; 5--10
    1427-9126
    Pojawia się w:
    Pomiary Automatyka Robotyka
    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:
    An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems
    Autorzy:
    Rauh, A.
    Senkel, L.
    Aschemann, H.
    Saurin, V. V.
    Kostin, G. V.
    Powiązania:
    https://bibliotekanauki.pl/articles/331160.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    heat transfer
    predictive control
    optimal control
    state estimation
    disturbance estimation
    distributed parameter systems
    sensitivity analysis
    wymiana ciepła
    regulacja predykcyjna
    układ o parametrach rozłożonych
    analiza wrażliwości
    Opis:
    In this paper, control-oriented modeling approaches are presented for distributed parameter systems. These systems, which are in the focus of this contribution, are assumed to be described by suitable partial differential equations. They arise naturally during the modeling of dynamic heat transfer processes. The presented approaches aim at developing finite-dimensional system descriptions for the design of various open-loop, closed-loop, and optimal control strategies as well as state, disturbance, and parameter estimation techniques. Here, the modeling is based on the method of integrodifferential relations, which can be employed to determine accurate, finite-dimensional sets of state equations by using projection techniques. These lead to a finite element representation of the distributed parameter system. Where applicable, these finite element models are combined with finite volume representations to describe storage variables that are—with good accuracy—homogeneous over sufficiently large space domains. The advantage of this combination is keeping the computational complexity as low as possible. Under these prerequisites, real-time applicable control algorithms are derived and validated via simulation and experiment for a laboratory-scale heat transfer system at the Chair of Mechatronics at the University of Rostock. This benchmark system consists of a metallic rod that is equipped with a finite number of Peltier elements which are used either as distributed control inputs, allowing active cooling and heating, or as spatially distributed disturbance inputs.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 1; 15-30
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    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 1-9 z 9

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