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    Wyświetlanie 1-9 z 9
    Tytuł:
    Fault-tolerant tracking control for a non-linear twin-rotor system under ellipsoidal bounding
    Autorzy:
    Kukurowski, Norbert
    Mrugalski, Marcin
    Pazera, Marcin
    Witczak, Marcin
    Powiązania:
    https://bibliotekanauki.pl/articles/2124781.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault tolerant control
    simultaneous fault
    external disturbances
    nonlinear system
    robust fault estimation
    fault detection
    fault diagnosis
    sterowanie tolerujące uszkodzenia
    uszkodzenie równoczesne
    zakłócenia zewnętrzne
    układ nieliniowy
    szacowanie błędu
    wykrywanie uszkodzenia
    diagnoza uszkodzenia
    Opis:
    A novel fault-tolerant tracking control scheme based on an adaptive robust observer for non-linear systems is proposed. Additionally, it is presumed that the non-linear system may be faulty, i.e., affected by actuator and sensor faults along with the disturbances, simultaneously. Accordingly, the stability of the robust observer as well as the fault-tolerant tracking controller is achieved by using the ℋ∞ approach. Furthermore, unknown actuator and sensor faults and states are bounded by the uncertainty intervals for estimation quality assessment as well as reliable fault diagnosis. This means that narrow intervals accompany better estimation quality. Thus, to cope with the above difficulty, it is assumed that the disturbances are over-bounded by an ellipsoid. Consequently, the performance and correctness of the proposed fault-tolerant tracking control scheme are verified by using a non-linear twin-rotor aerodynamical laboratory system.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 171--183
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault monitoring and fault recovery control for position-moored vessels
    Autorzy:
    Fang, S.
    Blanke, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/907618.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    diagnostyka uszkodzeń
    sterowanie tolerujące uszkodzenia
    usuwanie błędu
    wykrywanie zmian
    fault diagnosis
    fault tolerant control
    fault recovery
    position mooring
    non Gaussian change detection
    Opis:
    This paper addresses fault-tolerant control for position mooring of a shuttle or floating production storage and offloading vessels. A complete framework for fault diagnosis is presented. A loss of a sub-sea mooring line buoyancy element and line breakage are given particular attention, since such failures might cause high-risk abortion of an oil-loading operation. With significant drift forces from waves, non-Gaussian elements dominate forces and the residuals designed for fault diagnosis. Hypothesis testing is designed using dedicated change detection for the type of distribution encountered. A new position recovery algorithm is proposed as a means of fault accommodation in order to keep the mooring system in a safe state, despite faults. The position control is shown to be capable of accommodating serious failures and preventing breakage of a mooring line, or a loss of a buoyancy element, from causing subsequent failures. Properties of the detection and fault-tolerant control algorithms are demonstrated by high fidelity simulations.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2011, 21, 3; 467-478
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Scalable PP-1 block cipher
    Autorzy:
    Bucholc, K.
    Chmiel, K.
    Grocholewska-Czuryło, A.
    Idzikowska, E.
    Janicka-Lipska, I.
    Stokłosa, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/907705.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    resistance against cryptanalysis
    symmetric cipher
    scalable cipher
    S-box construction
    error detection
    szyfrowanie symetryczne
    szyfrowanie skalowalne
    kryptoanaliza
    wykrywanie błędu
    Opis:
    A totally involutional, highly scalable PP-1 cipher is proposed, evaluated and discussed. Having very low memory requirements and using only simple and fast arithmetic operations, the cipher is aimed at platforms with limited resources, e.g., smartcards. At the core of the cipher's processing is a carefully designed S-box. The paper discusses in detail all aspects of PP-1 cipher design including S-box construction, permutation and round key scheduling. The quality of the PP-1 cipher is also evaluated with respect to linear cryptanalysis and other attacks. PP-1's concurrent error detection is also discussed. Some processing speed test results are given and compared with those of other ciphers.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2010, 20, 2; 401-411
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An Expert System Coupled With a Hierarchical Structure of Fuzzy Neural Networks for Fault Diagnosis
    Autorzy:
    Calado, J. M. F.
    Costa, I. S.
    Powiązania:
    https://bibliotekanauki.pl/articles/908283.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    rozpoznanie błędu
    wykrywanie błędu
    system ekspertowy
    sieć neuronowa rozmyta
    fault diagnosis
    fault detection
    fault isolation
    shallow knowledge
    deep knowledge
    expert system
    fuzzy neural network
    abrupt faults
    incipient faults
    Opis:
    An on-line fault diagnosis system, designed to be robust to the normal transient behaviour of the process, is described. The overall system consists of an expert system cascade with a hierarchical structure of fuzzy neural networks, corresponding to a multi-stage fault detection and isolation system. The fault detection is performed through the expert system by means of fault detection heuristic rules, generated from deep and shallow knowledge of the process under consideration. If a fault is detected, the hierarchical structure of fuzzy neural networks starts and it performs the fault isolation task. The structure of this diagnosis system was designed to allow for the diagnosis of single and multiple simultaneous abrupt and incipient faults from only single abrupt fault symptoms. Also, it combines the advantages of both fuzzy reasoning and neural networks learning capacity. A continuous binary distillation column has been used as a test bed of the current approach. Single, double and triple simultaneous abrupt faults, as well as incipient faults, have been considered. The preliminary results obtained show a good accuracy, even in the case of multiple faults.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 667-687
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development of Dynamic Neural Networks With Application to Observer-Based Fault Detection and Izolation
    Autorzy:
    Marcu, T.
    Mirea, L.
    Frank, P. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/908286.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie błędu
    sieć neuronowa dynamiczna
    identyfikacja systemu
    fault diagnosis
    dynamic neural networks
    system identification
    static neural classifiers
    three-tank system
    Opis:
    The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour. The obtained symptoms are then classified by means of static artificial nets. Appropriate decision mechanisms are designed for each type of observer schemes. An application to a laboratory process is included. It refers to component and instrument fault detection and isolation in a three-tank system.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 547-570
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Dynamic Neural Networks for Process Modelling in Fault Detection and Isolation Systems
    Autorzy:
    Korbicz, J.
    Patan, K.
    Obuchowicz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/908291.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie błędu
    sieć neuronowa dynamiczna
    modelowanie nieliniowe
    algorytm inteligentny
    fault detection
    dynamic neural networks
    non-linear modelling
    learning algorithms
    FL-classifier
    two-tank system
    Opis:
    A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our approach, two applications are presented: a neural model of Narendra's system and a fault detection and identification system for the two-tank process.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 519-546
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fuzzy-Logic Fault Diagnosis of Industrial Process Actuators
    Autorzy:
    Kościelny, J. M.
    Syfert, M.
    Bartyś, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/908282.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie błędu
    logika rozmyta
    urządzenie uruchamiające
    system diagnostyczny
    fault diagnosis
    fuzzy logic
    actuators
    decentralised
    diagnostic systems
    Opis:
    The paper presents an idea of decomposition of diagnostic tasks in complex systems. Such decomposition consists in splitting basic diagnostic functions into lower-level units existing in decentralised structures of automatic control and supervision of the process. An example of a unit that realises this concept and includes a positioner that controls and diagnoses an assembly consisting of a servomotor and a pneumatic control valve is also given. An application of fuzzy logic to the actuator diagnosing algorithm is presented and results of the corresponding fault detection tests in an industrial environment are discussed.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 653-666
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Neural Network Evaluation of Model-Based Residuals in Fault Detection of Time Delay Systems
    Autorzy:
    Zitek, P.
    Mankova, R.
    Hlava, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/908288.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie błędu
    model anizochroniczny
    obserwator stanów
    sterowanie wewnętrzne
    sieć neuronowa
    model-based fault detection
    anisochronic model
    state observer
    internal model control
    artificial neural networks
    Opis:
    Model-based fault detection becomes rather questionable if a supervised plant belongs to the class of systems with distributed parameters and significant delays. Two methods of fault detection have been developed for this class of plants, namely a method of functional (anisochronic) state observer and a modified internal model control scheme adopted for that purpose. Both these model schemes are employed to generate residuals, i.e. differences suitable to watch whether a malfunction of the control operation has occurred. Continuous evaluation of residuals is provided by means of a dynamic application of artificial neural networks (ANNs). This evaluation is carried out on the basis of prediction of time series evolution, where the accordance obtained between the prediction and measured outputs is used as a classification criterion. Implementation of both the methods is demonstrated on a laboratory-scale heat transfer set-up, making use of the Real-Time Matlab software.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 599-617
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems
    Autorzy:
    Janczak, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/908281.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie błędu
    wyodrębnienie błędu
    estymacja parametryczna
    sieć neuronowa
    system nieliniowy
    fault detection
    fault isolation
    parameter estimation
    neural networks
    nonlinear system
    Opis:
    Fault detection and isolation in Wiener and Hammerstein systems via generation and processing of residual sequences is considered. We assume that some models of the unfaulty Wiener and Hammerstein systems under consideration are known. For Wiener systems, we also assume that their static nonlinear subsystems are invertible. Then, based on a serial-parallel definition of the residual error, new fault detection and isolation methods are proposed.To detect and identify all the changes in both the Wiener and Hammerstein system parameters, the sequences of residuals are processed by using linear regression methods or a neural network approach.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 711-735
    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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