In-Flight Wing Deformation Measurement System for Small Unmanned Aerial Vehicles

Pang, Zi Yang; Cesnik, Carlos E. S.; Atkins, Ella M.

doi:10.2514/6.2014-0330

Cited by 9 publications

(12 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The coordinate frame can usually be aligned to the body frame by software calibration in most INS units. The available output measurements are: (17) where INS r represents the offset between the INS mounting location and the body origin ( Figure 2). The superscript cross denotes a cross product matrix (where a cross product between two vectors is expressed as a matrix multiplication): The direction cosine matrix relating inertial and body coordinate frame using Yaw-Pitch-Roll rotation sequence can computed using 18…”

Section: Figure 2 Relationship Between Body Frame Origin and Ins Moumentioning

confidence: 99%

“…The SV setup and processing algorithm has been described in previous work. 17 Images captured are stored in solid state devices (SSD) as raw 8-bit greyscale images at 25Hz. Currently, image processing is done off-line using a desktop PC.…”

Section: Kalman Filter (Kf) Formulationmentioning

confidence: 99%

“…The hardware as well as the post processing software architecture for the stereovision system have been developed in previous work. 17…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Flight Shape Estimation of Very Flexible Unmanned Aerial Vehicle

Pang

Cesnik

2016

57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

Self Cite

View full text Add to dashboard Cite

This paper presents two different methods for estimating wing shape and rigid body attitude using displacement (stereovision reconstruction) and orientation information (inertia measurement units) at discrete points along a very flexible wing. First, theoretical relationship between the system states (strain, strain rate, body velocity, attitude etc.) and the sensor measurements are derived. Using the derived relationship, a nonlinear least squares fit is developed to obtain wing shape snapshots as well as rigid body attitude. The second method employs a Kalman filter to obtain both shape and rate information. The first method is more accurate since it employs nonlinear strain-displacement relationship at the cost of higher computational cost. However, in the presence of noise in the sensor measurement, the Kalman filter is faster and performs better in terms of accuracy.

show abstract

Section: Figure 2 Relationship Between Body Frame Origin and Ins Moumentioning

confidence: 99%

Section: Kalman Filter (Kf) Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Flight Shape Estimation of Very Flexible Unmanned Aerial Vehicle

Pang

Cesnik

2016

57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

Self Cite

View full text Add to dashboard Cite

show abstract

“…X-HALE Risk Reduction Vehicle (RRV) was designed to verify the aeroelastic properties of the aircraft and to understand its flight behavior before a fully instrumented X-HALE could be tested 8 . X-HALE Aeroelastic Test Vehicle (ATV) is the fully instrumented aircraft, equipped with a camera system to measure the wing deformation in flight 9 . Two pairs of cameras were installed on the center pod facing the wing tips, and three pairs of LED markers were placed on top of each section of the wing.…”

Section: X-hale State Of the Artmentioning

confidence: 99%

Linear Control of Highly Flexible Aircraft based on Loop Separation

González

Silvestre

Paglione

et al. 2016

AIAA Atmospheric Flight Mechanics Conference

Self Cite

View full text Add to dashboard Cite

The outcome of highly flexible aircraft requires new approaches in control design. In this research, we apply the loop separation concept, which consists in two control loops. The inner loop is capable of stabilizing the plant of the flexible aircraft, while is holding shape of the trimmed structure. Once the highly flexible aircraft is artificially transformed in a slightly flexible aircraft, the second loop or outer-loop is designed according to conventional, rigid-body-based control. Three control approaches were evaluated in the inner loop: LQG/LTR, LQR with output feedback and a direct integration approach. The direct integration approach with uncoupled gains presented better performance. The outer loops for speed, heading, sideslip angle and altitude were estimated using non-smooth optimization techniques and they are capable of attaining the commanded reference with low control energy and inside the maneuver requirements, while the inner loop is capable of reducing the elastic strains of the wing.

show abstract

“…In addition, it is superior to other non-contact methods, such as those using laser displacement sensors (LDS), because it is capable of a fullfield measurement with the use of only a single set of sensors. Owing to these advantages, its application ranges from the deflection estimation of laboratory test structure model [3,4] to various maneuvering structures such as aircraft wings [5][6][7], rotor blades [8][9][10] and civil infrastructures [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation method of homogeneous stereo camera system for full-field structural deformation estimation

Yun¹,

Kim²,

Han³

et al. 2015

International Journal of Aeronautical and Space Sciences

View full text Add to dashboard Cite

This study presents how we can evaluate stereo camera systems for the structural deformation monitoring. A stereo camera system, consisting of a set of stereo cameras and reflective markers attached on the structure, is introduced for the measurement and the stereo pattern recognition (SPR) method is utilized for the full-field structural deformation estimation. Performance of this measurement system depends on many parameters including types and specifications of the cameras, locations and orientations of them, and sizes and positions of markers; it is difficult to experimentally identify the effects of each parameter on the measurement performance. In this study, a simulation framework for evaluating performance of the stereo camera systems with various parameters has been developed. The maximum normalized root-mean-square (RMS) error is defined as a representative index of stereo camera system performance. A plate structure is chosen for an introductory example. Its several modal harmonic vibrations are generated and estimated in the simulation framework. Two cases of simulations are conducted to see the effects of camera locations and the resolutions of the cameras. An experimental validation is carried out for a few selected cases from the simulations. Using the simultaneous laser displacement sensor (LDS) measurements as the reference, the measurement errors are obtained and compared with the simulations.

show abstract

In-Flight Wing Deformation Measurement System for Small Unmanned Aerial Vehicles

Cited by 9 publications

References 20 publications

Flight Shape Estimation of Very Flexible Unmanned Aerial Vehicle

Flight Shape Estimation of Very Flexible Unmanned Aerial Vehicle

Linear Control of Highly Flexible Aircraft based on Loop Separation

Performance evaluation method of homogeneous stereo camera system for full-field structural deformation estimation

Contact Info

Product

Resources

About