Wind Sensing and Estimation Using Small Fixed-Wing Unmanned Aerial Vehicles: A Survey

Tian, Pengzhi; Huo, Chao; Rhudy, Matthew B.; Gross, Jason N.; Wu, Huixuan

doi:10.2514/1.i010885

Cited by 26 publications

(9 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the airspeed can be measured using a small pitot-static tube, equipment that measures the flow angles α and β is usually not readily available for small UAVs. There exists some available technologies [80], but such equipment can be expensive, too large or too heavy, or just impractical to install on small UAVs that often perform belly landings [81]. Several approaches for flow angle estimation have been proposed in the literature [81][82][83][84], but it remains a challenging problem.…”

Section: Integral Actionmentioning

confidence: 99%

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Coates

Fossen

2021

Applied Sciences

View full text Add to dashboard Cite

This paper presents nonlinear, singularity-free autopilot designs for multivariable reduced-attitude control of fixed-wing aircraft. To control roll and pitch angles, we employ vector coordinates constrained to the unit two-sphere and that are independent of the yaw/heading angle. The angular velocity projected onto this vector is enforced to satisfy the coordinated-turn equation. We exploit model structure in the design and prove almost global asymptotic stability using Lyapunov-based tools. Slowly-varying aerodynamic disturbances are compensated for using adaptive backstepping. To emphasize the practical application of our result, we also establish the ultimate boundedness of the solutions under a simplified controller that only depends on rough estimates of the control-effectiveness matrix. The controller design can be used with state-of-the-art guidance systems for fixed-wing unmanned aerial vehicles (UAVs) and is implemented in the open-source autopilot ArduPilot for validation through realistic software-in-the-loop (SITL) simulations.

show abstract

Section: Integral Actionmentioning

confidence: 99%

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Coates

Fossen

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…If payload limitations prevent integration of an on-board wind sensor, wind estimation techniques can also be explored, such as in [115,116]. For a more thorough understanding of different sensors and estimation techniques, we refer the reader to [117].…”

Section: Sensors and Equipmentmentioning

confidence: 99%

Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

Hollenbeck

Zulevic

Chen

2021

Drones

View full text Add to dashboard Cite

Detecting and quantifying methane emissions is gaining an increasingly vital role in mitigating emissions for the oil and gas industry through early detection and repair and will aide our understanding of how emissions in natural ecosystems are playing a role in the global carbon cycle and its impact on the climate. Traditional methods of measuring and quantifying emissions utilize chamber methods, bagging individual equipment, or require the release of a tracer gas. Advanced leak detection techniques have been developed over the past few years, utilizing technologies, such as optical gas imaging, mobile surveyors equipped with sensitive cavity ring down spectroscopy (CRDS), and manned aircraft and satellite approaches. More recently, sUAS-based approaches have been developed to provide, in some ways, cheaper alternatives that also offer sensing advantages to traditional methods, including not being constrained to roadways and being able to access class G airspace (0–400 ft) where manned aviation cannot travel. This work looks at reviewing methods of quantifying methane emissions that can be, or are, carried out using small unmanned aircraft systems (sUAS) as well as traditional methods to provide a clear comparison for future practitioners. This includes the current limitations, capabilities, assumptions, and survey details. The suggested technique for LDAQ depends on the desired accuracy and is a function of the survey time and survey distance. Based on the complexity and precision, the most promising sUAS methods are the near-field Gaussian plume inversion (NGI) and the vertical flux plane (VFP), which have comparable accuracy to those found in conventional state-of-the-art methods.

show abstract

“…As far as σ 2 β is concerned, using Equation ( 7) and the SLOPOV, it can be shown that: (13) where A = u 2 r + w 2 r , and…”

Section: Error Analysismentioning

confidence: 99%

“…Much work has been published in the field of extrapolation, filtering, and fusion of IMUs and other sensor data (GPS/GNSS, LiDAR, sonar, etc.) for attitude and velocity estimation [7][8][9][10][11], and for meteorology and wind estimation for atmospheric energy harvesting [12][13][14][15][16][17]. For small, low-cost UAVs, minimization of sensing requirements and expansion of flight envelope, endurance, and mission capability are priorities.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Airspeed, Angle of Attack, and Sideslip for Small Unmanned Aerial Vehicles (UAVs) Using a Micro-Pitot Tube

Ariante¹,

Ponte²,

Papa³

et al. 2021

Electronics

View full text Add to dashboard Cite

Fixed and rotary-wing unmanned aircraft systems (UASs), originally developed for military purposes, have widely spread in scientific, civilian, commercial, and recreational applications. Among the most interesting and challenging aspects of small UAS technology are endurance enhancement and autonomous flight; i.e., mission management and control. This paper proposes a practical method for estimation of true and calibrated airspeed, Angle of Attack (AOA), and Angle of Sideslip (AOS) for small unmanned aerial vehicles (UAVs, up to 20 kg mass, 1200 ft altitude above ground level, and airspeed of up to 100 knots) or light aircraft, for which weight, size, cost, and power-consumption requirements do not allow solutions used in large airplanes (typically, arrays of multi-hole Pitot probes). The sensors used in this research were a static and dynamic pressure sensor (“micro-Pitot tube” MPX2010DP differential pressure sensor) and a 10 degrees of freedom (DoF) inertial measurement unit (IMU) for attitude determination. Kalman and complementary filtering were applied for measurement noise removal and data fusion, respectively, achieving global exponential stability of the estimation error. The methodology was tested using experimental data from a prototype of the devised sensor suite, in various indoor-acquisition campaigns and laboratory tests under controlled conditions. AOA and AOS estimates were validated via correlation between the AOA measured by the micro-Pitot and vertical accelerometer measurements, since lift force can be modeled as a linear function of AOA in normal flight. The results confirmed the validity of the proposed approach, which could have interesting applications in energy-harvesting techniques.

show abstract

Wind Sensing and Estimation Using Small Fixed-Wing Unmanned Aerial Vehicles: A Survey

Cited by 26 publications

References 49 publications

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

Estimation of Airspeed, Angle of Attack, and Sideslip for Small Unmanned Aerial Vehicles (UAVs) Using a Micro-Pitot Tube

Contact Info

Product

Resources

About