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    Wyświetlanie 1-4 z 4
    Tytuł:
    System identification and heuristic control of segmented ailerons for enhanced stability of fixed wing UAVS
    Autorzy:
    Sattar, Abdul
    Wang, Liuping
    Mohamed, Abdulghani
    Fisher, Alex
    Powiązania:
    https://bibliotekanauki.pl/articles/2141835.pdf
    Data publikacji:
    2021
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    fixed-wing UAV
    PID control
    segmented control surfaces
    system identification
    Opis:
    Different from a conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed‐wing unmanned aerial vehicle (UAV) with segmented ailerons. The multiple aileron setup is configured as a multi‐input and single‐output system, and each segment is modeled as a control input. Experiments are conducted in the wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multiple aileron segments perform as a single aileron pair in a normal flight condition and adapt to multi‐segment control when encountering severe turbulence or significant angle reference changes. Experimental results reveal that although each control surface can stabilize the aircraft, the proposed control strategy by combining the multiple actuation surfaces reduces the mean squared errors for the roll angle up to 38 percent in the highly turbulent en vironment providing superior disturbance rejection properties.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2021, 15, 3; 3-14
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ensemble Model for Network Intrusion Detection System Based on Bagging Using J48
    Autorzy:
    Otoom, Mohammad Mahmood
    Sattar, Khalid Nazim Abdul
    Al Sadig, Mutasim
    Powiązania:
    https://bibliotekanauki.pl/articles/2201908.pdf
    Data publikacji:
    2023
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    cyber security
    network intrusion
    ensemble learning
    machine learning
    ML
    Opis:
    Technology is rising on daily basis with the advancement in web and artificial intelligence (AI), and big data developed by machines in various industries. All of these provide a gateway for cybercrimes that makes network security a challenging task. There are too many challenges in the development of NID systems. Computer systems are becoming increasingly vulnerable to attack as a result of the rise in cybercrimes, the availability of vast amounts of data on the internet, and increased network connection. This is because creating a system with no vulnerability is not theoretically possible. In the previous studies, various approaches have been developed for the said issue each with its strengths and weaknesses. However, still there is a need for minimal variance and improved accuracy. To this end, this study proposes an ensemble model for the said issue. This model is based on Bagging with J48 Decision Tree. The proposed models outperform other employed models in terms of improving accuracy. The outcomes are assessed via accuracy, recall, precision, and f-measure. The overall average accuracy achieved by the proposed model is 83.73%.
    Źródło:
    Advances in Science and Technology. Research Journal; 2023, 17, 2; 322--329
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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