IMPROVED PREDICTION OF FLAPPING WING AERIAL VEHICLE PERFORMANCE THROUGH COMPONENT INTERACTION MODELING

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2018

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Abstract

Flapping wing aerial vehicles offer the promise of versatile performance, however prediction of flapping wing aerial vehicle performance is a challenging task because of complex interconnectedness in vehicle functionality. To address this challenge, performance is estimated by using component-level modeling as a foundation. Experimental characterization of the drive motors, battery, and wings is performed to identify important functional characteristics and enable selection of appropriate modeling techniques. Component-level models are then generated that capture the performance of each vehicle component. Validation of each component-level model shows where errors are eliminated by capturing important dynamic functionality. System-level modeling is then performed by creating linkages between component-level models that have already been individually validated through experimental testing, leading to real-world functional constraints that are realized and correctly modeled at the system level. The result of this methodology is a system-level performance prediction that offers the ability to explore the effects of changing vehicle components as well as changing functional properties, while maintaining computational tractability. Simulated results are compared to experimental flight test data collected with an instrumented flapping wing aerial vehicle, and are shown to offer good accuracy in estimation of system-level performance properties.

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