Flying insects could perform robust flapping-wing dynamics under various environments while minimizing the high energetic cost by using elastic flight muscles and motors. Here we propose a fluid-structure interaction model that couples unsteady flapping aerodynamics and three-torsional-spring-based elastic wing-hinge dynamics to determine passive and active mechanisms (PAM) in bumblebee hovering. The results show that a strategy of active-controlled stroke, passive-controlled wing pitch and deviation enables an optimal elastic storage. The flapping-wing dynamics is robust, which is characterized by dynamics-based passive elevation-rotation and aerodynamics-based passive feathering-rotation, capable of producing aerodynamic force while achieving high power efficiency over a broad range of wing-hinge stiffness. A force-impulse model further confirms the capability of external perturbation robustness under the PAM-based strategy.
Flying insects exhibit outperforming stability and control via continuous wing flapping even under severe disturbances in various conditions of wind gust and turbulence. While conventional linear proportional derivative (PD)-based controllers are widely employed in insect-inspired flight systems, they usually fail to deal with large perturbation conditions in terms of the 6-DoF nonlinear control strategy. Here we propose a novel wing kinematics-based controller, which is optimized based on deep reinforcement learning (DRL) to stabilize bumblebee hovering under large perturbations. A high-fidelity Open AI Gym environment is established through coupling a CFD data-driven aerodynamic model and a 6-DoF flight dynamic model. The control policy with an action space of 4 is optimized using the off-policy Soft Actor–Critic (SAC) algorithm with automating entropy adjustment, which is verified to be of feasibility and robustness to achieve fast stabilization of the bumblebee hovering flight under full 6-DoF large disturbances. The 6-DoF wing kinematics-based DRL control strategy may provide an efficient autonomous controller design for bioinspired flapping-wing micro air vehicles.
Although the aerodynamics and energetics associated with single or paired flapping wings of insects have attracted significant attention, the aerodynamic interaction between the flapping wings and the flying body as a function of flight velocity remains an open question. Here we present a computational fluid dynamic (CFD) study of hawkmoth aerodynamics and energetics for hovering and for forward flights of five different velocities. We build up a high-fidelity CFD wing-body (WB) model based on the realistic morphology and the WB kinematics of hawkmoth Manduca Sexta, which enables trimmed flapping flights based on a genetic algorithm embedded within a CFD-driven model. The effects of WB interactions on velocity-dependent aerodynamic performance are examined with WB, wing-wing, and body-only models in terms of leading-edge-vortex- and body-vortex-based mechanisms and their correlations with the production of aerodynamic forces and with power consumption. While leading-edge-vortices are a convergent mechanism responsible for creating most of the aerodynamic force, the body-vortices created by WB interactions can augment the vertical force at all flight velocities, producing a 10% increase in fast flights. The time-averaged body-mass-specific mechanical power produces a J-shaped curve, which lowers power costs in intermediate- and high-velocity flights and saves energy from the WB interaction. An extensive investigation into aerodynamics and power consumption shows that high aspect-ratio wings increase wing- and body-based vertical forces, realistic wing-to-body mass ratios lead to low power costs, and slightly lower reduced frequency optimizes the aerodynamic performance. These results may help to guide the design of future biomimetic flapping micro aerial vehicles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.