Optimization of an Unmanned Aerial Vehicle Using Fuzzy Logic and Multidisciplinary Design Optimization

This research tries to propose a method to solve problems related to constrained multi-objective optimizations (implementation, computation time, and simplicity). This method, based on fuzzy logic, converts constrained multi-objective optimization problem into unconstrained single-objective optimization problems so many of the mentioned problems are solved. To demonstrate the efficiency of this method, three multidisciplinary design optimizations of an unmanned aerial vehicle have been performed. The aim of the first optimization is to compare the performance of the proposed method with two well-known methods of multi-objective optimizations. The purpose of the second and third optimizations is to show this capability of the proposed method that the designer, according to need, can consciously change the degree of importance on the objective functions or constraints. The results of the optimizations show that the computational time has been reduced, and two different optimal designs have been obtained by changing the degree of importance.