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Wyszukujesz frazę "model predictive control" wg kryterium: Temat

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    Wyświetlanie 1-11 z 11
    Tytuł:
    Effectiveness of Dynamic Matrix Control algorithm with Laguerre functions
    Autorzy:
    Tatjewski, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/2083461.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    process control
    model predictive control
    DMC algorithm
    Laguerre functions
    Opis:
    The paper is concerned with the presentation and analysis of the Dynamic Matrix Control (DMC) model predictive control algorithm with the representation of the process input trajectories by parametrised sums of Laguerre functions. First the formulation of the DMCL (DMC with Laguerre functions) algorithm is presented. The algorithm differs from the standard DMC one in the formulation of the decision variables of the optimization problem - coefficients of approximations by the Laguerre functions instead of control input values are these variables. Then the DMCL algorithm is applied to two multivariable benchmark problems to investigate properties of the algorithm and to provide a concise comparison with the standard DMC one. The problems with difficult dynamics are selected, which usually leads to longer prediction and control horizons. Benefits from using Laguerre functions were shown, especially evident for smaller sampling intervals.
    Źródło:
    Archives of Control Sciences; 2021, 31, 4; 795-814
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evacuation by leader-follower model with bounded confidence and predictive mechanisms
    Autorzy:
    Almeida, Ricardo
    Girejko, Ewa
    Machado, Luis
    Malinowska, Agnieszka B.
    Martins, Natália
    Powiązania:
    https://bibliotekanauki.pl/articles/1845516.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multi-agent systems
    emergency
    model predictive control
    bounded confidence
    Opis:
    This paper studies an evacuation problem described by a leader-follower model with bounded confidence under predictive mechanisms. We design a control strategy in such a way that agents are guided by a leader, which follows the evacuation path. The proposed evacuation algorithm is based on Model Predictive Control (MPC) that uses the current and the past information of the system to predict future agents’ behaviors. It can be observed that, with MPC method, the leader-following consensus is obtained faster in comparison to the conventional optimal control technique. The effectiveness of the developed MPC evacuation algorithm with respect to different parameters and different time domains is illustrated by numerical examples.
    Źródło:
    Archives of Control Sciences; 2021, 31, 3; 629-644
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evacuation by leader-follower model with bounded confidence and predictive mechanisms
    Autorzy:
    Almeida, Ricardo
    Girejko, Ewa
    Machado, Luis
    Malinowska, Agnieszka B.
    Martins, Natália
    Powiązania:
    https://bibliotekanauki.pl/articles/1845527.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multi-agent systems
    emergency
    model predictive control
    bounded confidence
    Opis:
    This paper studies an evacuation problem described by a leader-follower model with bounded confidence under predictive mechanisms. We design a control strategy in such a way that agents are guided by a leader, which follows the evacuation path. The proposed evacuation algorithm is based on Model Predictive Control (MPC) that uses the current and the past information of the system to predict future agents’ behaviors. It can be observed that, with MPC method, the leader-following consensus is obtained faster in comparison to the conventional optimal control technique. The effectiveness of the developed MPC evacuation algorithm with respect to different parameters and different time domains is illustrated by numerical examples.
    Źródło:
    Archives of Control Sciences; 2021, 31, 3; 629-644
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multivariable predictive control considering time delay for load-frequency control in multi-area power systems
    Autorzy:
    Daniar, S.
    Shiroei, M.
    Aazami, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/229223.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    load frequency control
    model predictive control
    time delay
    generation rate constraint
    Opis:
    In this paper, a multivariable model based predictive control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area interconnected power system. The proposed controller is designed to consider time delay, generation rate constraint and multivariable nature of the LFC system, simultaneously. A new formulation of the MPC is presented to compensate time delay. The generation rate constraint is considered by employing a constrained MPC and economic allocation of the generation is further guaranteed by an innovative modification in the predictive control objective function. The effectiveness of proposed scheme is verified through time-based simulations on the standard 39-bus test system and the responses are then compared with the proportional-integral controller. The evaluation of the results reveals that the proposed control scheme offers satisfactory performance with fast responses.
    Źródło:
    Archives of Control Sciences; 2016, 26, 4; 527-549
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efficient MPC algorithms with variable trajectories of parameters weighting predicted control errors
    Autorzy:
    Nebeluk, Robert
    Marusak, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/230077.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model predictive control
    nonlinear systems
    nonlinear models
    nonlinear control
    simulation
    optimization
    Opis:
    Model predictive control (MPC) algorithms brought increase of the control system performance in many applications thanks to relatively easily solving issues that are hard to solve without these algorithms. The paper is focused on investigating how to further improve the control system performance using a trajectory of parameters weighting predicted control errors in the performance function of the optimization problem. Different shapes of trajectories are proposed and their influence on control systems is tested. Additionally, experiments checking the influence of disturbances and of modeling uncertainty on control system performance are conducted. The case studies were done in control systems of three control plants: a linear non-minimumphase plant, a nonlinear polymerization reactor and a nonlinear thin film evaporator. Three types of MPC algorithms were used during research: linear DMC, nonlinear DMC with successive linearization (NDMC–SL), nonlinear DMC with nonlinear prediction and linearization (NDMC–NPL). Results of conducted experiments are presented in greater detail for the control system of the polymerization reactor, whereas for the other two control systems only the most interesting results are presented, for the sake of brevity. The experiments in the control system of the linear plant were done as preliminary experiments with the modified optimization problem. In the case of control system of the thin film evaporator the researched mechanisms were used in the control system of a MIMO plant showing possibilities of improving the control system performance.
    Źródło:
    Archives of Control Sciences; 2020, 30, 2; 325-363
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Elman neural network for modeling and predictive control of delayed dynamic systems
    Autorzy:
    Wysocki, A.
    Ławryńczuk, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/229646.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    dynamic models
    process control
    model predictive control
    neural networks
    Elman neural network
    delayed systems
    Opis:
    The objective of this paper is to present a modified structure and a training algorithm of the recurrent Elman neural network which makes it possible to explicitly take into account the time-delay of the process and a Model Predictive Control (MPC) algorithm for such a network. In MPC the predicted output trajectory is repeatedly linearized on-line along the future input trajectory, which leads to a quadratic optimization problem, nonlinear optimization is not necessary. A strongly nonlinear benchmark process (a simulated neutralization reactor) is considered to show advantages of the modified Elman neural network and the discussed MPC algorithm. The modified neural model is more precise and has a lower number of parameters in comparison with the classical Elman structure. The discussed MPC algorithm with on-line linearization gives similar trajectories as MPC with nonlinear optimization repeated at each sampling instant.
    Źródło:
    Archives of Control Sciences; 2016, 26, 1; 117-142
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust output feedback Model Predictive Control design
    Autorzy:
    Vesely, V.
    Rosinova, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/229853.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model predictive control
    robust control
    parameter dependent quadratic stability
    Lyapunov functional
    polytopic system
    decentralized control
    Opis:
    The paper addresses the problem of designing a robust output/state model predictive control for linear polytopic systems without constraints. The new robust BMI stability condition for given predictive and control horizon is derived which guarantees the parameter dependent quadratic stability and guaranteed cost.The proposed condition is appropriate for centralized and decentralized control design, as illustrated on example.
    Źródło:
    Archives of Control Sciences; 2010, 20, 3; 303-316
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online continuous-time adaptive predictive control of the technological glass conditioning process
    Autorzy:
    Drapała, Michał
    Byrski, Witold
    Powiązania:
    https://bibliotekanauki.pl/articles/2175115.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    system identification
    modulating functions method
    model predictive control
    continuous-time systems
    glass forehearth
    Opis:
    Glass production has a great industrial importance and is associated with many technological challenges. Control related problems concern especially the last part of the process, so called glass conditioning. Molten glass is gradually cooled down in a long ceramic channels called forehearths during glass conditioning. The glass temperature in each zone of the forehearth should be precisely adjusted according to the assumed profile. Due to cross-couplings and unmeasured disturbances, traditional control systems based on PID controllers, often do not ensure sufficient control quality. This problem is the main motivation for the research presented in the paper. A Model Predictive Control algorithm is proposed for the analysed process. It is assumed the dynamic model for each zone of the forehearth is identified on-line with the Modulating Functions Method. These continuous-time linear models are subsequently used for two purposes: for the predictive controller tuning, measurable disturbances compensation and for a static set point optimisation. Proposed approach was tested using Partial Differential Equation model to simulate two adjacent zones of the forehearth. The experimental results proved that it can be successfully applied for the aforementioned model.
    Źródło:
    Archives of Control Sciences; 2022, 32, 4; 755--782
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Real-time implementation of multiple model based predictive control strategy to air/fuel ratio of a gasoline engine
    Autorzy:
    Wojnar, S
    Polóni, T
    Šimončič, P
    Rohal’-Ilkiv, B
    Honek, M
    Csambál, J
    Powiązania:
    https://bibliotekanauki.pl/articles/229632.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model predictive control
    multiple models
    air/fuel ratio
    spark ignition engine
    ARX models
    Opis:
    Growing safety, pollution and comfort requirements influence automotive industry ever more. The use of three-way catalysts in exhaust aftertreatment systems of combustion engines is essential in reducing engine emissions to levels demanded by environmental legislation. However, the key to the optimal catalytic conversion level is to keep the engine air/fuel ratio (AFR) at a desired level. Thus, for this purposes more and more sophisticated AFR control algorithms are intensively investigated and tested in the literature. The goal of this paper is to present for a case of a gasoline engine the model predictive AFR controller based on the multiple-model approach to the engine modeling. The idea is to identify the engine in particular working points and then to create a global engine's model using Sugeno fuzzy logic. Opposite to traditional control approaches which lose their quality beside steady state, it enables to work with satisfactory quality mainly in transient regimes. Presented results of the multiple-model predictive air/fuel ratio control are acquired from the first experimental real-time implementation on the VW Polo 1390 cm3 gasoline engine, at which the original electronic control unit (ECU) has been fully replaced by a dSpace prototyping system which execute the predictive controller. Required control performance has been proven and is presented in the paper.
    Źródło:
    Archives of Control Sciences; 2013, 23, 1; 93-106
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust output predictive sequential controller design
    Autorzy:
    Vesely, V.
    Rosinova, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/229887.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model predictive control
    robust control
    parameter dependent quadratic stability
    Lyapunov function
    polytopic system
    sequential approach
    Opis:
    The paper addresses design problem of a robust parameter dependent quadratically stabilizing output/state feedback model predictive control for linear polytopic systems without constraints using original equential approach. The design procedure ensures stability, robustness properties and guaranteed cost for the closed-loop uncertain system
    Źródło:
    Archives of Control Sciences; 2010, 20, 1; 31-46
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    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
      Wyświetlanie 1-11 z 11

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