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    Wyświetlanie 1-8 z 8
    Tytuł:
    Integrated fault-tolerant control of a quadcopter UAV with incipient actuator faults
    Autorzy:
    Kantue, Paulin
    Pedro, Jimoh O.
    Powiązania:
    https://bibliotekanauki.pl/articles/2172129.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault tolerant control
    quadrocopter
    incipient actuator fault
    radial basis function
    neural network
    sterowanie tolerujące uszkodzenia
    kwadrokopter
    radialna funkcja bazowa
    sieć neuronowa
    Opis:
    An integrated approach to the fault-tolerant control (FTC) of a quadcopter unmanned aerial vehicle (UAV) with incipient actuator faults is presented. The framework is comprised of a radial basis function neural network (RBFNN) fault detection and diagnosis (FDD) module and a reconfigurable flight controller (RFC) based on the extremum seeking control approach. The dynamics of a quadcopter subject to incipient actuator faults are estimated using a nonlinear identification method comprising a continuous forward algorithm (CFA) and a modified golden section search (GSS) one. A time-difference-of-arrival (TDOA) method and the post-fault system estimates are used within the FDD module to compute the fault location and fault magnitude. The impact of bi-directional uncertainty and FDD detection time on the overall FTC performance and system recovery is assessed by simulating a quadcopter UAV during a trajectory tracking mission and is found to be robust against incipient actuator faults during straight and level flight and tight turns.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 4; 601--617
    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:
    Towards robustness in neural network based fault diagnosis
    Autorzy:
    Patan, K.
    Witczak, M.
    Korbicz, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/929913.pdf
    Data publikacji:
    2008
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    diagnostyka uszkodzeń
    odporność
    sieć neuronowa dynamiczna
    fault diagnosis
    robustness
    dynamic neural networks
    GMDH neural network
    Opis:
    Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 443-454
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault tolerance in networked control systems under intermittent observations
    Autorzy:
    Georges, J. P.
    Theilliol, D.
    Cocquempot, V.
    Ponsart, J. C.
    Aubrun, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/930171.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    przeciążenie sieci
    sterowanie odporne na błędy
    diagnostyka uszkodzeń
    system sieciowy
    model wielokrotny
    network congestion
    fault tolerant control
    fault diagnosis
    networked control system
    interacting multiple model
    Opis:
    This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With wireless transmission, packet losses act as sensor faults. In the presence of such faults, the faulty measurements corrupt directly the behaviour of closed-loop systems. Since the controller aims at cancelling the error between the measurement and its reference input, the real outputs will, in such a networked control system, deviate from the desired value and may drive the system to its physical limitations or even to instability. The proposed method facilitates fault compensation based on an interacting multiple model approach developed in the framework of channel errors or network congestion equivalent to multiple sensors failures. The interacting multiple model method involved in a networked control system provides simultaneously detection and isolation of on-line packet losses, and also performs a suitable state estimation. Based on particular knowledge of packet losses, sensor fault-tolerant controls are obtained by computing a new control law using fault-free estimation of the faulty element to avoid intermittent observations that might develop into failures and to minimize the effects on system performance and safety.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2011, 21, 4; 639-648
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Data-driven techniques for the fault diagnosis of a wind turbine benchmark
    Autorzy:
    Simani, S.
    Farsoni, S.
    Castaldi, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/330715.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault diagnosis
    analytical redundancy
    fuzzy system
    neural network
    residual generator
    fault estimation
    wind turbine benchmark
    diagnostyka uszkodzeń
    redundancja analityczna
    system rozmyty
    sieć neuronowa
    estymacja błędu
    turbina wiatrowa
    Opis:
    This paper deals with the fault diagnosis of wind turbines and investigates viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator, i.e., the fault estimate, involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the proposed data-driven solutions rely on fuzzy systems and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive models with exogenous input, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are also compared with those of other model-based strategies from the related literature. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 2; 247-268
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault diagnosis of networked control systems
    Autorzy:
    Aubrun, C.
    Sauter, D.
    Yamé, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/929885.pdf
    Data publikacji:
    2008
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie siecią
    system sterowania
    diagnostyka uszkodzeń
    sterowanie odporne na błędy
    straty pakietów
    komunikacja ograniczona
    networked control systems
    fault diagnosis
    fault tolerant control
    network-induced time delays
    packet losses
    limited communication
    Opis:
    Networked Control Systems (NCSs) deal with feedback control systems with loops closed via data communication networks. Control over a network has many advantages compared with traditionally controlled systems, such as a lower implementation cost, reduced wiring, simpler installation and maintenance and higher reliability. Nevertheless, the network-induced delay, packet dropout, asynchronous behavior and other specificities of networks will degrade the performance of closed-loop systems. In this context, it is necessary to develop a new theory for systems that operate in a distributed and asynchronous environment. Research on Fault Detection and Isolation (FDI) for NCSs has received increasing attention in recent years. This paper reviews the state of the art in this topic.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 525-537
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Reliability-aware zonotopic tube-based model predictive control of a drinking water network
    Autorzy:
    Khoury, Boutrous
    Nejjari, Fatiha
    Puig, Vicenç
    Powiązania:
    https://bibliotekanauki.pl/articles/2124779.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault tolerant control
    robust MPC
    zonotopes
    Bayesian theory
    drinking water network
    sterowanie tolerujące uszkodzenia
    zonotopy
    teoria bayesowska
    sieć wody pitnej
    Opis:
    A robust economic model predictive control approach that takes into account the reliability of actuators in a network is presented for the control of a drinking water network in the presence of uncertainties in the forecasted demands required for the predictive control design. The uncertain forecasted demand on the nominal MPC may make the optimization process intractable or, to a lesser extent, degrade the controller performance. Thus, the uncertainty on demand is taken into account and considered unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC is formulated to ensure robust constraint satisfaction, performance, stability as well as recursive feasibility through the formulation of an online tube-based MPC and an accompanying appropriate terminal set. Reliability is then modelled based on Bayesian networks, such that the resulting nonlinear function accommodated in the optimization setup is presented in a pseudo-linear form by means of a linear parameter varying representation, mitigating any additional computational expense thanks to the formulation as a quadratic optimization problem. With the inclusion of a reliability index to the economic dominant cost of the MPC, the network users’ requirements are met whilst ensuring improved reliability, therefore decreasing short and long term operational costs for water utility operators. Capabilities of the designed controller are demonstrated with simulated scenarios on the Barcelona drinking water network.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 197--211
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection
    Autorzy:
    Mrugalski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/331364.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    robust fault detection
    nonlinear system identification
    dynamic GMDH neural network
    unscented Kalman filter
    detekcja uszkodzeń
    identyfikacja nieliniowa
    sieć neuronowa dynamiczna
    filtr Kalmana bezśladowy
    Opis:
    This paper presents an identification method of dynamic systems based on a group method of data handling approach. In particular, a new structure of the dynamic multi-input multi-output neuron in a state-space representation is proposed. Moreover, a new training algorithm of the neural network based on the unscented Kalman filter is presented. The final part of the work contains an illustrative example regarding the application of the proposed approach to robust fault detection of a tunnel furnace.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 157-169
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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