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Journal of Bionic Engineering

, Volume 16, Issue 5, pp 904–915 | Cite as

A Neural-network-based Approach to Study the Energy-optimal Hovering Wing Kinematics of a Bionic Hawkmoth Model

  • Anh Tuan NguyenEmail author
  • Ngoc Doan Tran
  • Thanh Trung Vu
  • Thanh Dong Pham
  • Quoc Tru Vu
  • Jae-Hung Han
Article
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Abstract

This paper presents the application of an artificial neural network to develop an approach to determine and study the energy-optimal wing kinematics of a hovering bionic hawkmoth model. A three-layered artificial neural network is used for the rapid prediction of the unsteady aerodynamic force acting on the wings and the required power. When this artificial network is integrated into genetic and simplex algorithms, the running time of the optimization process is reduced considerably. The validity of this new approach is confirmed in a comparison with a conventional method using an aerodynamic model based on an extended unsteady vortex-lattice method for a sinusoidal wing kinematics problem. When studying the obtained results, it is found that actual hawkmoths do not hover under an energyoptimal condition. Instead, by tilting the stroke plane and lowering the wing positions, they can compromise and expend some energy to enhance their maneuverability and the stability of their flight.

Keywords

optimal hovering wing kinematics artificial neural network insect flight genetic algorithm unsteady vortex-lattice method bionics 

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Notes

Acknowledgement

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 107.01-2018.05.

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Copyright information

© Jilin University 2019

Authors and Affiliations

  • Anh Tuan Nguyen
    • 1
    Email author
  • Ngoc Doan Tran
    • 1
  • Thanh Trung Vu
    • 2
  • Thanh Dong Pham
    • 1
  • Quoc Tru Vu
    • 1
  • Jae-Hung Han
    • 3
  1. 1.Faculty of Aerospace EngineeringLe Quy Don Technical UniversityHanoiVietnam
  2. 2.Office of International CooperationLe Quy Don Technical UniversityHanoiVietnam
  3. 3.Department of Aerospace EngineeringKorea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea

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