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Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Research output: Contribution to journalArticle

Original languageEnglish
Number of pages10
JournalJournal of Aircraft
Early online date3 Jul 2019
DOIs
DateAccepted/In press - 4 May 2019
DateE-pub ahead of print (current) - 3 Jul 2019

Abstract

Small fixed-wing unmanned aerial systems (UAS) may require increased agility when operating in turbulent wind fields. In these conditions, conventional sensor suites could be augmented with additional flow-sensing to extend the aircraft’s usable flight envelope. Inspired by distributed sensor arrays in biological systems, a UAS with a chordwise array of pressure sensors was developed. Wind-tunnel testing characterized these sensors alongside a conventional airspeed sensor and an angle-of-attack (AoA) vane, and showed a single pressure measurement gave a linear response to AoA prestall. Flight tests initially manually piloted the vehicle through pitching maneuvers, then in a series of automated maneuvers based on closed-loop feedback using an estimate of AoA from the single pressure port. The AoA estimate was successfully used to control the attitude of the aircraft. An artificial neural network (ANN) was trained to estimate the AoA and airspeed using all pressure ports in the array, and validated using flight-trial data. The ANN more accurately estimated the AoA over a single-port method with good robustness to stall and unsteady flow. Distributed flow sensors could be used to supplement conventional flight control systems, providing enhanced information about wing flow conditions with application to systems with highly flexible or morphing wings.

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  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via AIAA at https://arc.aiaa.org/doi/10.2514/1.C035416 . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 17 MB, PDF document

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