A hybrid approach based on fuzzy BWM and MAIRCA for selection of engine in rotary wing unmanned aerial vehicle design

Abstract

The use of Unmanned Aerial Vehicle (UAV) platforms has been increasing day by day and it has become an important technology. In this study, how the engines should be selected in the design of a rotary wing UAV system is considered a multi-criteria decision-making (MCDM) problem. This MCDM problem has not yet been encountered in the literature. Therefore, a hybrid MCDM approach based on the fuzzy Best Worst Method (BWM) and Multi Attributive Ideal-Real Comparative Analysis (MAIRCA) is proposed to solve this problem. In the proposed approach, the decision makers determine 6 criteria (KV value, thrust, weight, efficiency, battery, electronic speed controller (ESC)) and 6 different engine (A₁, A₂, A₃, A₄, A₅, A₆) alternatives. The fuzzy BWM was used to calculate the weights of criteria, while the MAIRCA was used for the selection of alternatives. According to the results obtained, the three most effective criteria were thrust, KV value, and weight, respectively. The three best engine options were found as A₃, A₁, and A₆. Moreover, sensitivity analysis was performed to observe the change in the ranking of alternatives according to different weights of criteria. MABAC, MARCOS, and COPRAS methods were used to compare the alternative rankings found with the MAIRCA.