A Bio-inspired Sensing Approach to in-Gust Flight of Flapping Wing MAVs

Master thesis (2022)

Authors

C. Wang Aerospace Engineering

Contributors

S. Hamaza (supervisor 1)
G.C.H.E. de Croon (supervisor 2)
S. Wang (coach)
Faculty
Aerospace Engineering
Copyright: © 2022 Chenyao Wang
Modeling Adaptive Control DelFly Flapping Wing MAV Bio-inspired Aerial Robotics In-gust Flights Onboard Airflow Sensing
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Published Date

27-09-2022

Language

English

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Faculty

Aerospace Engineering

Abstract

Flapping wing micro aerial vehicles (FWMAVs) are known for their flight agility and maneuverability. However, their in-gust flight performance and stability is still inferior to their biological counterparts. To this end, a simplified in-gust dynamic model, which could capture the main gust effects on FWMAVs, has been identified with real in-gust flights' data of a FWMAV, the Flapper Drone. Based on this model, an adaptive position and velocity controller was proposed with gain scheduling and implemented for in-gust flights under gust speeds up to 2.4 m/s. With this airflow-sensing based adaptive controller, the in-gust hovering stability of the Flapper Drone has been improved when the gust's intensity and frequency changes, comparing with the original fixed-gain cascaded PID controller case.