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Improvement of UAV thrust using the BSO algorithm-based ANFIS model

Published online by Cambridge University Press:  02 April 2024

M. Konar Open the ORCID record for M. Konar [Opens in a new window] ,
S. Arık Hatipoğlu Open the ORCID record for S. Arık Hatipoğlu [Opens in a new window]  and
M. Akpınar Open the ORCID record for M. Akpınar [Opens in a new window]
M. Konar
Affiliation:
Faculty of Aeronautics and Astronautics, Erciyes University, Kayseri, Türkiye
S. Arık Hatipoğlu*
Affiliation:
Faculty of Aeronautics and Astronautics, Erciyes University, Kayseri, Türkiye
M. Akpınar
Affiliation:
Graduate School of Natural and Applied Science, Erciyes University, Kayseri, Türkiye
*
Corresponding author: S. Arık Hatipoğlu; Email: arikseda@erciyes.edu.tr
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Abstract

Unmanned aerial vehicles (UAVs), which are available in our lives in many areas today, bring with them new expectations and needs along with developing technology. In order to meet these expectations and needs, main subjects such as reducing energy consumption, increasing thrust and endurance, must be taken into account in UAV designs. In this study, Backtracking search optimisation (BSO) algorithm-based adaptive neuro-fuzzy inference system (ANFIS) model is proposed for the first time to improve UAV thrust. For this purpose, first, different batteries and propellers were tested on the thrust measuring device and a data set was obtained. Propeller diameter and pitch, current, voltage and the electronic speed controller (ESC) signal were selected as input, and UAV thrust was selected as output. ANFIS was used to relate input and output parameters that do not have a direct relationship between them. In order to determine the ANFIS parameters at the optimum value, ANFIS was trained with the obtained data set by using BSO algorithm. Then, the objective function based on the optimum ANFIS structure was integrated into BSO algorithm, and the input values that gave the optimum thrust were calculated using BSO algorithm. Simulation results, in which parameters such as engine, battery and propeller affecting the thrust are taken into account equally, emphasise that the proposed method can be used effectively in improving the UAV thrust. This hybrid method, consisting of ANFIS and BSO algorithm, can reduce the cost and time loss in UAV designs and allows many possibilities to be tested.

Keywords

ANFISbacktracking search optimisationthrustUAVoptimisation
Type
Research Article
Information
The Aeronautical Journal , First View , pp. 1 - 10
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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