Neural network based redesign of morphing UAV for simultaneous improvement of roll stability and maximum lift/drag ratioстатья из журнала
Аннотация: Purpose The aim of this paper is to redesign of morphing unmanned aerial vehicle (UAV) using neural network for simultaneous improvement of roll stability coefficient and maximum lift/drag ratio. Design/methodology/approach Redesign of a morphing our UAV manufactured in Faculty of Aeronautics and Astronautics, Erciyes University is performed with using artificial intelligence techniques. For this purpose, an objective function based on artificial neural network (ANN) is obtained to get optimum values of roll stability coefficient ( C l β ) and maximum lift/drag ratio ( E max ). The aim here is to save time and obtain satisfactory errors in the optimization process in which the ANN trained with the selected data is used as the objective function. First, dihedral angle ( φ ) and taper ratio ( λ ) are selected as input parameters, C* l β and E max are selected as output parameters for ANN. Then, ANN is trained with selected input and output data sets. Training of the ANN is possible by adjusting ANN weights. Here, ANN weights are adjusted with artificial bee colony (ABC) algorithm. After adjusting process, the objective function based on ANN is optimized with ABC algorithm to get better C l β and E max , i.e. the ABC algorithm is used for two different purposes. Findings By using artificial intelligence methods for redesigning of morphing UAV, the objective function consisting of C* l β and E max is maximized. Research limitations/implications It takes quite a long time for E max data to be obtained realistically by using the computational fluid dynamics approach. Practical implications Neural network incorporation with the optimization method idea is beneficial for improving C l β and E max . By using this approach, low cost, time saving and practicality in applications are achieved. Social implications This method based on artificial intelligence methods can be useful for better aircraft design and production. Originality/value It is creating a novel method in order to redesign of morphing UAV and improving UAV performance.
Год издания: 2018
Авторы: Tuğrul Oktay, Seda Arık, İlke Türkmen, Metin Uzun, Harun Çelik
Издательство: Emerald Publishing Limited
Источник: Aircraft Engineering and Aerospace Technology
Ключевые слова: Aeroelasticity and Vibration Control, Model Reduction and Neural Networks, Aerospace and Aviation Technology
Открытый доступ: closed
Том: 90
Выпуск: 8
Страницы: 1203–1212