Design of low altitude long endurance solar-powered UAV using genetic algorithm

Abu Bakar, Li Ke, Haobo Liu, Ziqi Xu, Dongsheng Wen

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This paper presents a novel framework for the design of a low altitude long endurance solar-powered UAV for multiple-day flight. The genetic algorithm is used to optimize wing airfoil using CST parameterization, along with wing, horizontal and vertical tail geometry. The mass estimation model presented in this paper is based on structural layout, design and available materials used in the fabrication of similar UAVs. This model also caters for additional weight due to the change in wing airfoil. The configuration is optimized for a user-defined static margin, thereby incorporating static stability in the optimization. Longitudinal and lateral control systems are developed for the optimized configuration using the inner–outer loop strategy with an LQR and PID controller, respectively. A six degree-of-freedom nonlinear simulation is performed for the validation of the proposed control scheme. The results of nonlinear simulations are in good agreement with static analysis, validating the complete design process.

Original languageEnglish
Article number228
JournalAerospace
Volume8
Issue number8
DOIs
StatePublished - Aug 2021
Externally publishedYes

Keywords

  • Genetic algorithm
  • LQR (linear quadratic regulator)
  • Optimization
  • PID (proportional integral derivative)
  • Solar-powered UAV (unmanned aerial vehicle)

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