Soaring Maneuvers for a Morphing Capable UAV 1 Presentation for Dr Haitham Taha amp Colligues Aug2017 Presentation Outline 2 Introduction UAS Problem of energy d eficiency in ID: 638144
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Slide1
Dynamics, Optimization & Control of Biologically Inspired Dynamic Soaring Maneuvers for a Morphing Capable UAV
1
Presentation for
Dr
Haitham
Taha
&
Colligues
Aug-2017Slide2
Presentation Outline
2
Introduction
UAS
Problem of energy
d
eficiency in
s
UAS
Dynamic soaring a potential solution
Biological
Inspiration: Dynamic
s
oaring under morphing conditions
Area of research : Integration of two concepts
Research results
Task
a
ccomplished till date
Future work to be carried out in next six months at UCISlide3
Introduction
3Slide4
Introduction :
sUAS
sUAS
Utility
s
urveillance, communication relay & loitering dominated missions
low
radar cross section area, ability to perform agile maneuvers close to the proximity of ground, reduced vulnerability, low fuel consumption, low cost
4Slide5
Introduction :
sUAS
Diverse set of mission
r
equirement necessitates
sUAS
to improve the time aloft
Speed, range and endurance
Much larger platform
Possible Solution
Upgrade battery/fuel system
Elevated cost and space requirementTapping energy from atmosphere though Soaring (Biological inspiration)
5Slide6
Dynamic Soaring The extraction of energy from atmospheric wind shear
6
Has
four
characteristic
phasesSlide7
Dynamic Soaring7
Dynamic Soaring
Initial Orientation
Yaw movement
Pitch
movement
Roll movementSlide8
USEFUL STUDIES8Slide9
Some Useful studies :
Gottfried Sachs
Gottfried Sachs
:
1
2
relevant publications from 1991 to 2017
[1] G. Sachs and B. Grüter, "Dynamic Soaring− Kinetic Energy and Inertial Speed," in AIAA Atmospheric Flight Mechanics Conference, 2017, p. 1862.Kinetic energy plays an important role in the energy management of dynamic soaring important to use an appropriate kinetic energy conceptUtilized kinetic energy based on inertial speed
9Slide10
Some Useful studies :
Gottfried Sachs
[
2] G. Sachs, "In-flight measurement of upwind dynamic soaring in albatrosses,"
Progress in Oceanography,
vol. 142, pp. 47-57, 2016.
[3] G. Sachs, J.
Traugott
, A.
Nesterova, and F. Bonadonna, "Experimental verification of dynamic soaring in albatrosses," The Journal of experimental biology, vol. 216, pp. 4222-4232, 2013.[4] G. Sachs, J. Traugott, A. P. Nesterova, G. Dell'Omo, F. Kuemmeth, W. Heidrich, et al., "Flying at No Mechanical Energy Cost: Disclosing the Secret of Wandering Albatrosses," Plos One, vol. 7, Sep 5 2012.[5] G. Sachs, J. Traugott
, and F.
Holzapfel
, "Progress against the Wind with Dynamic Soaring-Results from In-Flight Measurements of Albatrosses," in AIAA Guidance Navigation and Control Conference, AIAA, 2011, p. 2011.[6] G. Sachs, J. Traugott, and F. Holzapfel, "In-flight measurement of dynamic soaring in albatrosses," in AIAA Guidance, Navigation, and Control Conference, Toronto, Ontario Canada, 2010, pp. 2-5.10Slide11
Some Useful studies :
Gottfried Sachs
D
ynamic
soaring is a small-scale flight
maneuver which
is the basis for the extreme flight performance of albatrosses and
other large
seabirds to travel huge distances in sustained non-flapping flight.
Experimental data with sufficient resolution of these small-scale movements are not availableIn-house developments of GPS logging units for recording raw phase observations and of a dedicated mathematical method for post processing these measurements11Slide12
Some Useful studies :
Gottfried Sachs
Experimental
results from tracking 16 wandering albatrosses show the characteristic pattern of dynamic
soaring throughout their flight
12Slide13
Some Useful studies :
Gottfried Sachs
[7] G. Sachs, "Minimum shear wind strength required for dynamic soaring of albatrosses,"
Ibis,
vol. 147, pp. 1-10, 2005.
[8] G. Sachs and O. da Costa, "Optimization of dynamic soaring at ridges," in
AIAA
Atmospheric Flight Mechanics Conference and Exhibit, Austin, Texas
, 2003, pp. 11-14.
[9] G. Sachs and M. Mayrhofer, "Shear wind strength required for dynamic soaring at ridges," Technical Soaring, vol. 25, pp. 209-215, 2001.[10] G. Sachs, "Optimal Wind Energy Extraction for Dynamic Soaring," in Applied Mathematics in Aerospace Science and Engineering, ed: Springer, 1994, pp. 221-237.[11] G. Sachs, A. Knoll, and K. Lesch, "Optimal utilization of wind energy for dynamic soaring," Technical Soaring, vol. 15, pp. 48-55, 1991.
[12] G. Sachs, "MINIMUM CONDITIONS FOR DYNAMIC SOARING,"
Zeitschrift
Fur Flugwissenschaften Und Weltraumforschung, vol. 13, pp. 188-198, May-Jun 1989.13Slide14
Some Useful studies:
Gottfried Sachs
A
mathematical optimization
method
(
GESOP
and ALTOS) is
used for computing minimum shear wind
energy-neutral trajectoriesThe minimum shear wind strength is of a magnitude that often exists or is exceeded in areas in which albatrosses are found5m/s close to sea level (0.79m height)The mechanism of energy transfer from the shear flow to the bird is considered, and it is shown that there is a significant energy gain in the upper curve and a loss in the lower curve.
14Slide15
Some Useful studies
Evaluation of dynamic
soaring flight characteristics
Dynamic
soaring flight characteristics have been investigated actively by various researchers to determine the fundamentals of soaring flight.
Parameters
such as the peak altitude/speeds attained during the soaring maneuvers, cycle time, minimum wind shear required
for birds /UAVs
were subsequently
determined15Slide16
Some Useful studiesZhao investigated Optimal dynamic soaring patterns
(loiter, travel and basic modes) of a glider in wind gradients [1]Minimum fuel powered dynamic soaring of UAV utilizing wind gradients
[2]
16
Y
. J. Zhao, "Optimal patterns of glider dynamic soaring,"
Optimal control applications and methods,
vol. 25, pp. 67-89, 2004
.1. Y. Y. J. Zhao and Y. C. Qi, "Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing wind gradients," Optimal Control Applications & Methods, vol. 25, pp. 211-233, Sep-Oct 2004.Slide17
Some Useful studies: Optimal dynamic soaring patterns
Min cycle time Max altitude gain
17Slide18
Some Useful studies: Minimum fuel
Minimum fuel (min thrust for jet and min power for prop) powered
dynamic soaring
trajectories
When the wind gradient is sufficiently
steep,
a UAV can perform dynamic soaring without using any thrust.
If
the wind
gradient is not sufficient to maintain powerless dynamic soaring, on the other hand, a UAV can still take advantage of the wind gradient to reduce fuel consumptions by performing powered dynamic soaring flights. In this case, the largest wind condition parameter at which powerless dynamic soaring is still possible sets a bound on the range of wind conditions 181. Y. Y. J. Zhao and Y. C. Qi, "Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing wind gradients," Optimal Control Applications & Methods,
vol. 25, pp. 211-233, Sep-Oct 2004.Slide19
Some Useful studiesSachs investigated dynamic soaring at ridges
and determined that significant shear wind conditions exists behind ridges to successfully perform dynamic soaring
Zhao &
Lissaman
evaluated that
shear layers over the
ocean
contain sufficient energy to provide continuous or assisted flight for small (< 10 kg) UAVs
191. Zhao "Minimum fuel powered dynamic soaring of UAVs utilizing wind gradients,“ 2004.P. Lissaman, "Wind energy extraction by birds and flight vehicles," AIAA paper, vol. 241, 2005G. Sachs and O. da Costa, "Optimization of dynamic soaring at ridges," in AIAA Atmospheric Flight Mechanics Conference and Exhibit, Austin, Texas, 2003, pp. 11-14.Slide20
Some Useful studies For full-scale aircraft
Sachs and da Costa showed that dynamic soaring by full-size sailplanes is possible with values of wind shear found near mountain
ridges
Gordan
showed full
size sailplanes could extract energy from horizontal wind shears, although the utility of the energy extraction could be marginal depending on the flight conditions and type of sailplane used
20
R
. J. Gordon, "Optimal dynamic soaring for full size sailplanes," DTIC Document2006.G. Sachs and O. da Costa, "Optimization of dynamic soaring at ridges,“2003Slide21
Some Useful studiesGao [1] , Lawrence [2] implemented DS trajectories utilizing piece wise controllers for each of the four phases of DS for a fixed-wing
gliding UAV Computationally simpleNot accurate
21
1.
X. Z.
Gao
, Z. X.
Hou
, Z.
Guo, R. F. Fan, and X. Q. Chen, "Analysis and design of guidance-strategy for dynamic soaring with UAVs," Control Engineering Practice, vol. 32, pp. 218-226, Nov 2014.2. Lawrance and Sukkarieh, "A guidance and control strategy for dynamic soaring in a gliding UAV,“2009Slide22
Some Useful studiesZhu (2015) performed trajectory optimization for Long
Endurance (loiter mode) and Long Distance (forward flight) for Engineless UAV by Dynamic Soaring
22
B. Zhu, Z.
Hou
, X. Wang, and Q. Chen, "Long Endurance and Long Distance Trajectory Optimization for Engineless UAV by Dynamic Soaring,"
CMES
: Computer Modeling in Engineering & Sciences,
vol. 106, pp. 357-377, 2015.Slide23
Some Useful studiesAkhtar [1,2] developed dynamic soaring trajectories employing non-linear
constrained optimization method where some reference polynomials The trajectories are defined by the coefficients
of the
polynomials. The coefficients are
determined analytically
from the boundary conditions and
the final
time.
23
[1] N. Akhtar, J. F. Whidborne, and A. K. Cooke, "Wind shear energy extraction using dynamic soaring techniques," 2009[2] N. Akhtar, J. F. Whidborne, and A. K. Cooke, "Real-time optimal techniques for unmanned air vehicles fuel saving," 2012Slide24
Critical Observation Dynamic soaring maneuver has never been attempted for a morphing platform Soaring birds rests on its wings with a shoulder lock, skillfully
vary wing planform and twist, during dynamic soaring [1,2,3]
Biologically
inspired UAV will be able to acquire maximum energy from the atmosphere
24
J
. P. Barnes, "How Flies the Albatross–the Flight Mechanics of Dynamic Soaring," SAE Technical
Paper2004
.
X.-Z. Gao, Z.-X. Hou, Z. Guo, and X.-Q. Chen, "Energy extraction from wind shear: Reviews of dynamic soaring," Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 229, pp. 2336-2348, 2015.
3. D
.
Lentink, U. Müller, E. Stamhuis, R. De Kat, W. Van Gestel, L. Veldhuis, et al., "How swifts control their glide performance with morphing wings," Nature, vol. 446, pp. 1082-1085, 2007.Slide25
Research Neech
For UAV
Majority
of the
studies utilize
off-line numerical optimization techniques
Confined
to fixed
planform configurations
Requirement existed
to
compute optimal trajectories in near real time environment for on board utilization to perform analysis for dynamic soaring under morphing conditions Morphing has significant
impact on aircraft performance & flight
dynamics characteristics
25
Y
. J. Zhao, "Optimal patterns of glider dynamic soaring,"
Optimal control applications and methods,
vol. 25, pp. 67-89, 2004
.
N
.
Akhtar
, J. F.
Whidborne
, and A. K. Cooke, "Real-time optimal techniques for unmanned air vehicles fuel saving,"
Proceedings of the Institution of Mechanical Engineers
1.
Zhao, Y.Y.J. and Y.C. Qi,
Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing
wind
gradients.
Optimal Control Applications & Methods, 2004.
25
(5): p. 211-233.
1. Sachs, G.,
Minimum shear wind strength required for dynamic soaring of albatrosses.
Ibis, 2005.
147
(1): p. 1-10.
2. Sachs, G. and O. da Costa.
Optimization of dynamic soaring at ridges
. in
AIAA
Atmospheric Flight Mechanics Conference and Exhibit, Austin, Texas
. 2003.
3. Sachs, G. and M.
Mayrhofer
,
Shear wind strength required for dynamic soaring at ridges.
Technical Soaring, 2001.
25
(4): p. 209-215.
2
Y. J.
Zhao, "Optimal patterns of glider dynamic soaring,"
Optimal control applications and methods,
vol. 25, pp. 67-89, 2004.Slide26
Area of Research
Dynamics
, Optimization & Control of Biologically Inspired Dynamic Soaring Maneuvers for a Morphing
Capable
UAV
26Slide27
Area of Research
Optimal Dynamic
soaring maneuvers will be
implemented for
a morphing capable platform which can alter its planform configuration
(span and sweep variations)
27
Slide28
Problem Formulation28Slide29
Description of Platform
Modal Specifications
Geometric Attribute
Dimensions
Geometric Attribute
Dimensions
Mass
1.25 kg
Aerodynamic coefficient (k)
0.08
Fuselage Length
1 m
Zero Lift Drag
coefficient
(
CDo
)
0.004
Span Variation
1.25m
±
50%
velocity
range
3- 30m/s
MAC
0.48m
Azimuth
(
ψ)
range
-540° to 90°
Area
0.6 m2
Flight
path angle (
γ)
range
-60° to 60°
Aspect Ratio
4.31
Bank Angle range
-70° to 70°
Sweep variation
0-25°
Cycle
time
1-30 s
Wing Airfoil
NACA 0012
Max Load factor
5
29Slide30
Mathematical Modeling
Non Linear UAV Dynamics model
30Slide31
Mathematical Modeling
State vector
Control vector
31Slide32
Mathematical Modeling
Boundary Constraints
Wind Model
32Slide33
Mathematical Modeling
Path Constraints
33Slide34
Software Utilized
Trajectory Optimization
DynOpt
GPOPS
II
Utilization
of direct collocation methods, the optimal control problem is transcribed to a nonlinear programming problem (NLP) by parameterizing the state and control using global polynomials
IPOPT
(NLP Solver)
Matlab34Slide35
Comparative Analysis: Morphing Vs
Fixed Wing
Trajectory
optimization for dynamic soaring
is formulated
for UAV with fixed planform
and than
morphing configurations.
Evaluation of various aspects of dynamic soaring parameters cycle timemaximum achievable velocityminimum required wind shearmaximum altitude gainenergy (total, potential and kinetic) gaindistances covered in the east / north
direction
35Slide36
General Aspects36Slide37
Max velocity in the DS loop is constrained by load factor constraintMax velocity occurs max permissible load factormin CL, min span, max sweep
37
Load Factor constraint affects Velocity and Span Slide38
Shear layer is being considered as a limited
height structure (that is, the horizontal wind speed increases
linearly to
some altitude and is constant for higher altitudes
)
38
Dynamic Soaring Heuristics:
Zho
ho
is the surface correctness factorSlide39
At higher speeds, high sweep/ low span improves aerodynamic wing performance by reducing drag whereas low sweep/ high span wings contributes in better performance at low velocities by providing more lift
At lower speeds, low sweep/ high span
wings deliver superior glide ratios and at higher speeds glide ratio is higher for high sweep/low span wings
39
Morphing Impact
[1] D
.
Lentink
, U. Müller, E.
Stamhuis, R. De Kat, W. Van Gestel, L. Veldhuis
, et al.
, "How swifts control their glide performance with morphing wings,"
Nature, vol. 446, pp. 1082-1085, 2007.Slide40
During the climb phaseThe K.E is traded for P.E and velocity starts decreasing
40
Dynamic Soaring CycleSlide41
Span Morphing Results41Slide42
Comparative Analysis: Morphing Vs
Fixed Wing
Optimized Trajectory
42Slide43
43
Altitude GainSlide44
44
East Distance CoverageSlide45
45
North Distance CoverageSlide46
Max velocity in the DS loop is constrained by load factor constraintMax velocity occurs max permissible load factormin CL, min span, max sweep
46
Load Factor constraint affects Velocity and Span Slide47
Velocity Vs
Altitude
47Slide48
48
Control Effort : Span morphingSlide49
49
Normalized energiesSlide50
Shear layer is being considered as a limited
height structure (that is, the horizontal wind speed increases
linearly to
some altitude and is constant for higher altitudes
)
50
Dynamic Soaring Heuristics:
Zho
ho
is the surface correctness factorSlide51
51
Minimum wind shear requirement
Minimum
wind speeds required for dynamic soaring at sea level conditions are
6.6m
/s (for
1.25m
span),
6.8m
/s (for
1.75m
span) and
5.6m
/s (for morphing platform).
Fixed
1.25m
span
Fixed
1.75m
span
Morphing configurationSlide52
52
Control
Effort : Angle of attack
Slide53
53
Lift CoefficientSlide54
54
Drag Coefficient variation
wrt
spanSlide55
55
Drag Coefficient variation
wrt
velocity and altitudeSlide56
56
Heading,
FPA
, and bank angle Slide57
S No
Nom
Worst case fixed span configuration value
Span Morphing Configuration
%
Improvement
(Morphing value-fixed value)/Fixed value
1
Maximum altitude gain
150ft
210ft
40% enhancement
2
Distance covered in east direction
210ft
300ft
42% enhancement
3
Distance covered in north direction
70ft
100ft
42% enhancement
4
Normalized energy
5200
7200
38% higher energy
5
Maximum speed
100ft
/sec
120
ft
/sec
20% higher max velocity
57
Comparative Analysis:
Span Morphing
Vs
Fixed
ConfigurationsSlide58
S No
Nom
Worst case fixed span configuration value
Span Morphing Configuration
%
Improvement
(Morphing value-fixed value)/Fixed value
6
Minimum wind shear at sear level (1m)
6.8m
/s
5.6m
/s
18% lesser minimum wind shear requirement
7
Maximum required Aoa
5.2
3.7
29% lesser maximum
AoA
required
8
Maximum Cl
requirement
0.45
0.4
11% lesser
AOA
requirement
9
Max Drag reduction
0.0334
0.023
34% decrease in maximum drag
58
Comparative Analysis:
Span Morphing
Vs
Fixed ConfigurationsSlide59
Sweep Morphing Results59Slide60
Optimized Trajectory
60Slide61
61
Control Effort : Sweep morphing Slide62
62
Lift CoefficientSlide63
Drag Coefficient63
Comparative Analysis: Morphing
Vs
Fixed
WingSlide64
Control Effort : Angle of attack
64
Comparative Analysis: Morphing
Vs
Fixed
WingSlide65
Control Effort : Bank a
ngle
65
Comparative Analysis: Morphing
Vs
Fixed
WingSlide66
66
Comparative Analysis:
Sweep Morphing
Vs
Fixed
Wing
S No
Nomen
Fixed 0° sweep configuration
Morphing configuration
(0-20° sweep)
1
Maximum altitude gain
210
ft
230
ft
10% improvement
2
Energy gain
7600
8200
6.5
%
improvement
3
Maximum velocity
118ft
/sec
125ft
/sec
6
%
improvement
4
Maximum Angle
of attack requirement
2.2 °
2°
10
%
reduction
5
Minimum wind
shear required
Wind velocity of
5m
/s
(close to se level)
4.2m
/s
15 % reduction
6
Drag
coefficient
15% lesser Slide67
Work
Task Accomplished till Date
Optimal
dynamic soaring trajectories implemented for a fixed configuration UAV suitable for near real time implementations (computation time of under
4sec
)
Optimal
dynamic soaring trajectories formulated for a morphing capable platform capable of
Span morphing (50% span variation
) Sweep morphing (0-20
°)
Hybrid morphing (span + sweep variations)
67Slide68
Publications
Conference Papers
Optimization of Dynamic Soaring Maneuvers for a Morphing Capable
UAV.
AIAA
Scitech
2017, Grapevine,
USA (Published) Dynamic Modeling & Stability Analysis of a generic UAV in Glide
Phase.
International conference on Mechanical, Material and Aerospace Engineering (
2MAE), 2017 (Published) Optimization of Dynamic Soaring Maneuvers to Enhance Endurance of a fixed configuration UAV. International conference on Aerospace, Mechanical and Mechatronic Engineering (
CAMME
), 2017
Thailand
(Published)
Autonomous Dynamic Soaring Maneuvers for a UAV Capable of Span Morphing.
AIAA
Scitech
2018, Florida,
USA
(submitted)
68Slide69
Publications
Journal Papers (Under Review)
Real Time Trajectory Optimization of Dynamic Soaring Maneuvers Using Orthogonal Collocation Techniques.
Submitted
to Journal of Theoretical And Applied Mechanics (
JTAM
) , April
2017
(Under Review) Dynamic
Soaring Maneuvers for an unmanned aircraft capable of sweep
morphing. IEEE Access , June 2017
(Under Review) Dynamics, optimization and control of autonomous Aerial vehicles. IEEE Access , June 2017 (Under Review)
Autonomous dynamic soaring for a morphing capable UAV
(under finalization stages at UCI)
69Slide70
Tasks for Next Six Months at UCI
To
get familiarize with the ongoing research activities and the tools
used at
Flight Dynamics and Control
Lab, UCI
To
learn
about various non-linear
control techniques (such as Sliding Mode Control, Back stepping controller, Feed back linearization, Control lypnov function, Geometric control and so on). In specific those already employed to solve engineering problems by the research group Synthesis of control law for implementing optimized dynamic soaring trajectories utilizing most relevant control techniquePublication of at least 02 Impact factor journal for the developed control architecture
70Slide71
THANK YOU71