Simultaneous determination of maximum acceleration and endurance of morphing UAV with ABC algorithm-based model

Purpose The purpose of this paper is to present a novel approach based on the artificial bee colony (ABC) algorithm aiming to achieve maximum acceleration and maximum endurance for morphing unmanned aerial vehicle (UAV) design. Design/methodology/approach Some of the most important issues in the design of UAV are the design of thrust system and determination of the endurance of the UAV. Although propeller selection is very important for the thrust system design, battery selection has the utmost importance for the determination of UAV endurance. In this study, the calculations of maximum acceleration and endurance required by ZANKA-II during the flight are considered simultaneously. For this purpose, a model based on the ABC algorithm is proposed for the morphing UAV design, aiming to achieve the maximum acceleration and endurance. In the proposed model, the propeller diameter, propeller pitch and battery values used in morphing UAV's power system design are selected as the input parameters; maximum acceleration and endurance are selected as the output parameters. To obtain the maximum acceleration and endurance, the optimum input parameters are determined through the ABC algorithm-based model. Findings Considerable improvements on maximum acceleration and endurance of morphing UAV with ABC algorithm-based model are obtained. Research limitations/implications The endurance and acceleration due to the thrust are two separate parameters that are not normally proportional to each other. In this study, optimization of UAV’s endurance and acceleration is considered with equal importance. Practical implications Using artificial intelligence techniques causes fast and simple optimization for determination of UAV’s endurance and acceleration with equal importance. In the simulation studies with ABC algorithm, satisfactory results are obtained. Social implications The results of the study have showed that the proposed approach could be an alternative method for UAV designers. Originality/value Providing a new and efficient method saves time and reduces cost in calculations of maximum acceleration and endurance of the UAV.

Neural network based redesign of morphing UAV for simultaneous improvement of roll stability and maximum lift/drag ratio

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 (Clβ) and maximum lift/drag ratio (Emax). 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*lβ and Emax 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 Clβ and Emax, 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*lβ and Emax is maximized. Research limitations/implications It takes quite a long time for Emax 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 Clβ and Emax. 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.