Application of genetic algorithms to conceptual design of a micro-air vehicle

Abstract

This paper investigates the feasibility of automating the conceptual design of a micro-air vehicle on a personal computer system. The proposed design methodology adopts the use of genetic algorithms as the search engine in the design process. The multidisciplinary optimization problem here is to maximize the lift-to-drag ratio subjected to static longitudinal stability, performance and physical constraints. The six design parameters chosen are angle of attack, main wing twist angle, winglet span, main wing chord length, main wing taper ratio and winglet taper ratio. A case study has been carried out to compare the performance of using genetic algorithms with well-established non-linear optimization method based on sequential quadratic programming.