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    Wyświetlanie 1-8 z 8
    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:
    Design of unknown input observers for non-linear stochastic systems and their application to robust fault diagnosis
    Autorzy:
    Witczak, M.
    Korbicz, J.
    Józefowicz, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/205987.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    fault diagnosis
    unknown input
    unscented Kalman filter
    interactive multiple models
    non-linear systems
    Opis:
    The paper deals with the problem of designing filters for non-linear discrete-time stochastic systems. In particular, it is shown how to design an unknown input filter for a single (constant) unknown input distribution matrix, which guarantees that the effect of a fault will not be decoupled from the residual. Subsequently, the problem of using one, fixed disturbance distribution matrix is eliminatek by using the interacting multiple models algorithm to select an appropriate unknown input distribution matrix from a predefined set of matrices. The final part of the paper shows an illustrative example, which confirms the effectiveness of the proposed approach.
    Źródło:
    Control and Cybernetics; 2013, 42, 1; 227-256
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Motor Control: Neural Models and Systems Theory
    Autorzy:
    Doya, K.
    Kimura, H.
    Miyamura, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/908323.pdf
    Data publikacji:
    2001
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    adaptacyjny układ sterowania
    model wielokrotny
    inverse model
    adaptive control
    cerebellum
    reinforcement learning
    basal ganglia
    multiple models
    Opis:
    In this paper, we introduce several system theoretic problems brought forward by recent studies on neural models of motor control. We focus our attention on three topics: (i) the cerebellum and adaptive control, (ii) reinforcement learning and the basal ganglia, and (iii) modular control with multiple models. We discuss these subjects from both neuroscience and systems theory viewpoints with the aim of promoting interplay between the two research communities.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2001, 11, 1; 77-104
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Land clayey deposits compressibility investigation using principal component analysis and multiple regression tools
    Autorzy:
    Berrah, Yacine
    Chegrouche, Aymen
    Brahmi, Serhane
    Boumezbeur, Abderrahmane
    Powiązania:
    https://bibliotekanauki.pl/articles/2201674.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
    Tematy:
    compressibility index
    geotechnical parameters
    principal component analysis
    PCA
    multiple regression models
    indeks ściśliwości
    parametry geotechniczne
    analiza głównych składowych
    regresja wielokrotna
    Opis:
    The settlement and compressibility magnitude of the major clayey and marly sediments in Tebessa area (N-E of Algeria) depends on several geotechnical parameters such as compression Cc and recompression Cs indices. The aim of this study was to investigate the parameters related to soil compressibility through tools of statistical analysis, which save time in comparison to multiply repeated laboratory tests. The study also adopted the principal component analysis (PCA) method to eliminate a number of uncorrelated variables that have no influence on the compressibility magnitude, or their impact is insignificant. The highest mean correlation coefficients were obtained for different contributing parameters. Multiple regression analysis has been performed to obtain the best fit model of the output Cc parameter taking into account the best correlation by adding parameters as regressors to reach the highest coefficient of regression R2 . The final obtained model of the present case study gives the best fit model with R2 of 0.92 which is a better value compared to different published models in the literature (R2 of 0.7 as maximum). The chosen input parameters using PCA combined with multiple regression analysis allow identifying the most important input parameters that noticeably affect the soil compression index, and provide with the best model for estimating the Cc index.
    Źródło:
    Geomatics, Landmanagement and Landscape; 2022, 4; 95--107
    2300-1496
    Pojawia się w:
    Geomatics, Landmanagement and Landscape
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimization of safety instrumented system design and maintenance frequency for oil and gas industry processes
    Autorzy:
    Redutskiy, Y.
    Powiązania:
    https://bibliotekanauki.pl/articles/407133.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    emergency shutdown system
    Markov models
    multiple-criterion optimization
    safety instrumented system
    systems design
    risk management
    Opis:
    Oil and gas industry processes are associated with significant expenditures and risks. Adequacy of the decisions on safety measures made during early stages of planning the facilities and processes contributes to avoiding technological incidents and corresponding losses. Formulating straightforward requirements for safety instrumented systems that are followed further during the detailed engineering design and operations is proposed, and a mathematical model for safety system design is introduced in a generalized form. The model aims to reflect the divergent perspectives of the main parties involved in oil and gas projects, and, therefore, it is formulated as a multi-objective problem. Application of black box optimization is suggested for solving real-life problem instances. A Markov model is applied to account for device failures, technological incidents, continuous restorations and periodic maintenance for a given process and safety system configuration. This research is relevant to engineering departments and contractors, who specialize in planning and designing the technological solution.
    Źródło:
    Management and Production Engineering Review; 2017, 8, 1; 46-59
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Impatient customers in Markovian queue with Bernoulli feedback and waiting server under variant working vacation policy
    Autorzy:
    Bouchentouf, Amina Angelika
    Yahiaoui, Lahcene
    Kadi, Mokhtar
    Majid, Shakir
    Powiązania:
    https://bibliotekanauki.pl/articles/1181936.pdf
    Data publikacji:
    2020
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    queueing models
    variant of a multiple working vacation
    balking
    reneging
    retention of reneged customers
    simulation
    Opis:
    This paper deals with customers’ impatience behaviour for single server Markovian queueing system under K-variant working vacation policy, waiting server, Bernoulli feedback, balking, reneging, and retention of reneged customers. Using the probability generating function (PGF) technique, we obtain the steady-state solution of the system. Besides, we prove the stochastic decomposition properties. Useful performance measures of the considered queueing system are derived. A cost model is developed. Then, the parameter optimisation is carried out numerically, using a quadratic fit search method (QFSM). Finally, numerical examples are provided to visualise the analytical results.
    Źródło:
    Operations Research and Decisions; 2020, 30, 4; 5-28
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bias Reduction of Finite Population Imputation by Kernel Methods
    Autorzy:
    Pettersson, Nicklas
    Powiązania:
    https://bibliotekanauki.pl/articles/465881.pdf
    Data publikacji:
    2013
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    bayesian bootstrap
    boundary and nonresponse bias missing data
    multiple imputation
    Pólya urn models
    real donor imputation
    Opis:
    Missing data is a nuisance in statistics. Real donor imputation can be used with item nonresponse. A pool of donor units with similar values on auxiliary variables is matched to each unit with missing values. The missing value is then replaced by a copy of the corresponding observed value from a randomly drawn donor. Such methods can to some extent protect against nonresponse bias. But bias also depends on the estimator and the nature of the data. We adopt techniques from kernel estimation to combat this bias. Motivated by Pólya urn sampling, we sequentially update the set of potential donors with units already imputed, and use multiple imputations via Bayesian bootstrap to account for imputation uncertainty. Simulations with a single auxiliary variable show that our imputation method performs almost as well as competing methods with linear data, but better when data is nonlinear, especially with large samples.
    Źródło:
    Statistics in Transition new series; 2013, 14, 1; 139-160
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A decision rule for uncertain multicriteria mixed decision making based on the coefficient of optimism
    Autorzy:
    Gaspars-Wieloch, Helena
    Powiązania:
    https://bibliotekanauki.pl/articles/578578.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Ekonomiczny w Katowicach
    Tematy:
    Modele optymalizacyjne
    Niepewność
    Optymalizacja wielokryterialna
    Planowanie scenariuszowe
    Podejmowanie decyzji w warunkach niepewności
    Wielokryterialne podejmowanie decyzji
    Decision making under uncertainty
    Multiple criteria optimization
    Multiple-criteria decision making
    Optimizing models
    Scenario planning
    Uncertainty
    Opis:
    This paper is devoted to multicriteria decision making under uncertainty with scenario planning. This topic has been explored by many researchers since almost all real-world decision problems contain multiple conflicting criteria and a deterministic criteria evaluation is often impossible. We propose a procedure for uncertain multi-objective optimization which may be applied when a mixed strategy is sought after. A mixed strategy, as opposed to a pure strategy, allows the decision maker to select and perform a weighted combination of several accessible alternatives. The new approach takes into account the decision maker’s preference structure and attitude towards risk. This attitude is measured by the coefficient of optimism on the basis of which a set of the most probable events is suggested and an optimization problem is formulated and solved.
    Źródło:
    Multiple Criteria Decision Making; 2015, 10; 32-47
    2084-1531
    Pojawia się w:
    Multiple Criteria Decision Making
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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