Bioinspired Wing-Surface Pressure Sensing for Attitude Control of Micro Air Vehicles

Abdel‐Rohman, Mohamed; Watkins, Simon; Fisher, Alex; Marino, Matthew; Massey, Kevin; Clothier, Reece

doi:10.2514/1.c032805

Cited by 37 publications

(28 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Once the wing had stalled the flow appeared to be separated near the leading edge, with the pressure becoming unsteady in the region of separated flow. This agrees with previous studies where pressure ports near the leading edge were shown to provide signals that have a strong relationship with AoA [6,8], which then breaks down in stall conditions [10].…”

Section: A Aoa and V Estimationsupporting

confidence: 93%

See 1 more Smart Citation

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

Wood

Araujo-Estrada

Richardson

et al. 2019

Journal of Aircraft

View full text Add to dashboard Cite

Small fixed-wing Unmanned Aerial Systems (UAS) might 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 chord-wise array of pressure sensors was developed. Wind-tunnel testing characterised 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 pre-stall. Flight tests initially manually piloted the vehicle through pitching manoeuvres, then in a series of automated manoeuvres 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.

show abstract

Section: A Aoa and V Estimationsupporting

confidence: 93%

“…A variety of different man-made sensors have also been used to measure the distribution of flow properties on the wings of small UAS. The most common are pressure sensors [6][7][8][9][10][11][12], but more novel sensors such as hotfilms [13,14] and artificial hair sensors [15,16] have also been used to measure flow velocity.…”

Section: Introductionmentioning

confidence: 99%

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

Wood

Araujo-Estrada

Richardson

et al. 2019

Journal of Aircraft

View full text Add to dashboard Cite

show abstract

“…All strategies previously described omit the advance knowledge or prediction of a wind velocity field ahead of the UAV. However, a method for sensing flow disturbances in front of miniature UAVs and using the output signal for further control has been demonstrated by Mohamed et al [13][14][15]. The control strategy has been developed for roll axis as the most sensitive to wind turbulence.…”

Section: Related Researchmentioning

confidence: 99%

Performance Improvement of Small Unmanned Aerial Vehicles Through Gust Energy Harvesting

Gavrilovic

Bénard

Pastor

et al. 2018

Journal of Aircraft

View full text Add to dashboard Cite

“…However, method for sensing flow disturbances in front of mini UAVs and using the output signal for further control has been demonstrated by Mohamed. 8,9 The control strategy has been developed for roll axis as most sensitive to wind turbulence. Recent experiments by Watkins 10 considering measurements of wind components on locations along span-wise confirmed statement about spatial variation of turbulence magnitude which is in correlation with actual needs.…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement of Small UAVs Through Energy-Harvesting Within Atmospheric Gusts

Gavrilovic

Bénard

Pastor

et al. 2017

AIAA Atmospheric Flight Mechanics Conference

View full text Add to dashboard Cite

Fixed-wing mini aerial vehicles usually fly at low altitudes often exposed to turbulent environments. Gust soaring is a flight technique of energy harvesting in such a complex and stochastic domain. Presented work shows the feasibility and benefits of exploiting non-stationary environment for a small UAV. Longitudinal dynamics trajectory is derived showing significant benefits in extended flight with sinusoidal wind profile. Optimization strategy for active control has been performed with the aim of obtaining most effective set of gains for energy retrieval. Moreover, three-dimensional multi-point model confirmed feasibility of energy harvesting in a more complex spatial wind field. Influence of unsteady aerodynamics is determined on overall energy gain along the flight path with active proportional control. Most contributing aerodynamic parameters are identified and suggested as basic objective function of an UAV design for energy harvesting in gusty environment. In addition, passive approach of control related to structural dynamics is investigated, pointing out its potential and possible improvements with aero-elastic tailoring.

show abstract

Bioinspired Wing-Surface Pressure Sensing for Attitude Control of Micro Air Vehicles

Cited by 37 publications

References 15 publications

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

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

Performance Improvement of Small Unmanned Aerial Vehicles Through Gust Energy Harvesting

Performance Improvement of Small UAVs Through Energy-Harvesting Within Atmospheric Gusts

Contact Info

Product

Resources

About