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    Wyświetlanie 1-4 z 4
    Tytuł:
    Fundamental limitations of the decay of generalized energy in controlled (discrete-time) nonlinear systems subject to state and input constraints
    Autorzy:
    Selek, István
    Ikonen, Enso
    Powiązania:
    https://bibliotekanauki.pl/articles/330074.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    decay rate maximization
    Lyapunov function
    nonlinear control system
    rozkład wykładniczy
    funkcja Lapunowa
    układ sterowania nieliniowy
    Opis:
    This paper is devoted to the analysis of fundamental limitations regarding closed-loop control performance of discrete-time nonlinear systems subject to hard constraints (which are nonlinear in state and manipulated input variables). The control performance for the problem of interest is quantified by the decline (decay) of the generalized energy of the controlled system. The paper develops (upper and lower) barriers bounding the decay of the system’s generalized energy, which can be achieved over a set of asymptotically stabilizing feedback laws. The corresponding problem is treated without the loss of generality, resulting in a theoretical framework that provides a solid basis for practical implementations. To enhance understanding, the main results are illustrated in a simple example.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2019, 29, 4; 629-639
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Design of a multivariable neural controller for control of a nonlinear MIMO plant
    Autorzy:
    Bańka, S.
    Dworak, P.
    Jaroszewski, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/330790.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    MIMO multivariable control system
    nonlinear system
    neural control
    wielowymiarowy układ sterowania
    układ nieliniowy
    sterowanie neuronowe
    Opis:
    The paper presents the training problem of a set of neural nets to obtain a (gain-scheduling, adaptive) multivariable neural controller for control of a nonlinear MIMO dynamic process represented by a mathematical model of Low-Frequency (LF) motions of a drillship over the drilling point at the sea bottom. The designed neural controller contains a set of neural nets that determine values of its parameters chosen on the basis of two measured auxiliary signals. These are the ship’s current forward speed measured with respect to water and the systematically calculated difference between the course angle and the sea current (yaw angle). Four different methods for synthesis of multivariable modal controllers are used to obtain source data for training the neural controller with parameters reproduced by neural networks. Neural networks are designed on the basis of 3650 modal controllers obtained with the use of the pole placement technique after having linearized the model of LF motions made by the vessel at its nominal operating points in steady states that are dependent on the specified yaw angle and the sea current velocity. The final part of the paper includes simulation results of system operation with a neural controller along with conclusions and final remarks.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 357-369
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Linear adaptive structure for control of a nonlinear MIMO dynamic plant
    Autorzy:
    Bańka, S.
    Dworak, P.
    Jaroszewski, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/329882.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    MIMO multivariable control systems
    nonlinear system
    modal control
    wielowymiarowy układ sterowania
    układ nieliniowy
    sterowanie modalne
    Opis:
    In the paper an adaptive linear control system structure with modal controllers for a MIMO nonlinear dynamic process is presented and various methods for synthesis of those controllers are analyzed. The problems under study are exemplified by the synthesis of a position and yaw angle control system for a drillship described by a 3DOF nonlinear mathematical model of low-frequency motions made by the drillship over the drilling point. In the proposed control system, use is made of a set of (stable) linear modal controllers that create a linear adaptive controller with variable parameters tuned appropriately to operation conditions chosen on the basis of two measured auxiliary signals. These are the ship’s current forward speed measured in reference to the water and the systematically calculated difference between the course angle and the sea current (yaw angle). The system synthesis is carried out by means of four different methods for system pole placement after having linearized the model of low-frequency motions made by the vessel at its nominal “operating points” in steady states that are dependent on the specified yaw angle and the sea current velocity. The final part of the paper includes simulation results of system operation with an adaptive controller of (stepwise) varying parameters along with conclusions and final remarks.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 47-63
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Sub-Optimal Nonlinear Predictive and Adaptive Control Based on the Parametric Volterra Model
    Autorzy:
    Haber, R.
    Bars, R.
    Lengyel, O.
    Powiązania:
    https://bibliotekanauki.pl/articles/908307.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie predykcyjne
    sterowanie nieliniowe
    sterowanie optymalne
    układ nieliniowy
    adaptacyjny układ sterowania
    predictive control
    nonlinear control
    optimal control
    nonlinear systems
    adaptive control
    Opis:
    Predictive control algorithms have been worked out mainly to control linear plants. There is a great demand to apply different control ideas to nonlinear systems. Using predictive control algorithms for nonlinear systems is a promising technique. Extended horizon one-step-ahead and long-range optimal predictive control algorithms are given here for the parametric Volterra model (which includes also the generalized Hammerstein model). A quadratic cost function is minimized which considers the quadratic deviations of the reference signal and the output signal at a future point (or points) beyond the dead time and also penalizes large control signal increments. For prediction of the output signal, a predictive model is applied which uses information about the input and output signals up to the current time. A predictive transformation of the nonlinear dynamic model is given. The incremental model is advantageous since the cost function contains the control increment and not the control signal itself. An incremental transformation of the predictive forms is also described. Sub-optimal solutions to the optimal control algorithms are discussed with different assumptions for the control signal during the control horizon. The effect of the different strategies and the effect of the tuning parameters is investigated through simulation examples.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 1; 161-173
    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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