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

作　　者：Anh Tuan Nguyen Ngoc Doan Tran Thanh Trung Vu Thanh Dong Pham Quoc Tru Vu Jae-Hung Han 

机构地区：[1]Faculty of Aerospace Engineering,Le Quy Don Technical University,236 Hoang Quoc Viet,Vietnam [2]Office of International Cooperation,Le Quy Don Technical University,236 Hoang Quoc Viet,Vietnam [3]Department ofAerospace Engineerings Korea Advanced Institute of Science and Technology,Daejeon 34141,Republic ofKorea

出　　处：《Journal of Bionic Engineering》2019年第5期904-915,共12页仿生工程学报（英文版）

摘　　要：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 sinu soidal wing kinematics problem.When studying the obtained results,it is found that actual hawkmoths do not hover under an energy-optimal 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.

关 键 词：optimal hovering wing kinematics artificial neural network INSECT flight genetic algorithm unsteady VORTEX-LATTICE method BIONICS 

分 类 号：O35[理学—流体力学]