Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function

作     者：Ali Reza BABAEI Mohammad Reza SETAYANDEH Hamid FARROKHFAL 

作者机构：Department of Mechanical and Aerospace Engineering Malek-Ashtar University of Technology 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2018年第31卷第12期

页      码：2248-2259页

摘      要：This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization(FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle(UAV):(A) deterministic optimization and(B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm(NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation(MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively.

主 题 词：Fuzzy logic Multidisciplinary design optimization Preference function Robust design Unmanned Aerial Vehicle(UAV) 

学科分类：08[工学] 0825[工学-环境科学与工程类] 

核心收录：

D　O　I：10.1016/J.CJA.2018.04.018

馆 藏 号：203299478...