Reliability-based design optimization of control parameters for the optimal lift-to-power ratio of clapping-wing micro air vehicles
Yanwei Zhang (Complex Aviation System Simulation, China Electronics Technology Group Corporation)
Shui Yu (University of Electronic Science and Technology of China)
Zhihua Wang (Chengdu Aircraft Industrial Group Co. Ltd)
Saullo G.P. Castro (TU Delft - Aerospace Engineering)
Zhonglai Wang (University of Electronic Science and Technology of China)
Wensheng Qiao (Complex Aviation System Simulation, China Electronics Technology Group Corporation)
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Abstract
A reliability-based design optimization framework is introduced and applied to optimize control parameters for the optimal lift-to-power ratio of clapping-wing micro air vehicles. Improving this ratio is essential for achieving high load capacity and long endurance in flapping-wing micro air vehicles, especially for clapping-wing types. First, a lift-to-power ratio solver based on smoothed particle hydrodynamics coupled with the finite element method is proposed. To account for the flexible deformation of the wings during high-frequency flapping, an air-solid interaction numerical model is employed to handle quasi-flexible aerodynamics. An experimental platform using particle image velocimetry is established to validate the numerical model and measure power consumption. Then, considering the structural and environmental uncertainties of clapping-wing micro air vehicles measured through experiments, a reliability-based design optimization with an accelerated Kriging model is proposed and solved by particle swarm optimization. Finally, several design cases are examined. Through aerodynamic analysis and reliability-based optimization, optimal control parameters are identified to maximize the lift-to-power ratio of the designed micro air vehicle. The novel method demonstrates rapid convergence, decreasing from 6 to 4 iterations for two control variables and from 9 to 6 iterations for three control variables, thus enabling highly efficient optimization.
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