Aerodynamic Modeling and System Identification from Flight Data ...
Aerodynamic Modeling and System Identification from Flight Data ...
Aerodynamic Modeling and System Identification from Flight Data ...
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<strong>Aerodynamic</strong> <strong>Modeling</strong> <strong>and</strong> <strong>System</strong> <strong>Identification</strong><br />
<strong>from</strong> <strong>Flight</strong> <strong>Data</strong> – Recent Applications at DLR<br />
?<br />
by<br />
Dr. Ravindra Jategaonkar<br />
Senior Scientist<br />
Institute of <strong>Flight</strong> <strong>System</strong>s<br />
DLR - German Aerospace Center<br />
Lilienthalplatz 7, 38108 Braunschweig, Germany<br />
Email: jategaonkar@dlr.de Phone: 0049 531 295-2684<br />
TÜBITAK-SAGE / METU, Ankara, Turkey, 29 May 2008<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 1
Contents<br />
Introduction<br />
Overview: Why <strong>and</strong> what is system identification<br />
Unified approach<br />
Quad-M basics (Maneuvers, Measurements, Methods, Models)<br />
Estimation methods<br />
Examples of <strong>Aerodynamic</strong> <strong>Modeling</strong><br />
- C-160 <strong>Aerodynamic</strong> <strong>Data</strong> Base:<br />
<strong>Data</strong> consistency checking<br />
Nonlinear control surface effectiveness<br />
Separation of pitch damping derivatives<br />
Stall hysteresis<br />
<strong>Modeling</strong> of l<strong>and</strong>ing gear effects<br />
- <strong>Data</strong>base validation<br />
- Wake Vortex Aircraft Encounter Model<br />
- EC-135 Helicopter<br />
6 DOF <strong>and</strong> extended models <strong>and</strong> Rotor wake modeling<br />
- Phoenix: Reusable orbiter glider,<br />
- UAV: Automatic Envelope Expansion through Adaptive <strong>Flight</strong> Control<br />
Concluding remarks<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 2
Aircraft mass<br />
characteristics<br />
What is <strong>System</strong> <strong>Identification</strong>? (1)<br />
u z<br />
Dynamic <strong>System</strong><br />
Process noise<br />
(turbulence)<br />
State Equations x<br />
Measurement Eq.<br />
Inputs x &(<br />
t)<br />
= f ( x(<br />
t),<br />
u(<br />
t),<br />
ϕ)<br />
States y(<br />
t)<br />
= g(<br />
x(<br />
t),<br />
u(<br />
t),<br />
Θ)<br />
<strong>Aerodynamic</strong>s<br />
(unknown<br />
parameters)<br />
Sensor<br />
locations<br />
Measurement<br />
noise<br />
Outputs<br />
Sensor model<br />
(calibration factors,<br />
bias errors)<br />
AIM: To determine unknown model parameters Θ such that the model<br />
response y matches well with the measured system response z.<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 3<br />
y
What is <strong>System</strong> <strong>Identification</strong>? (2)<br />
Inputs Outputs<br />
State<br />
.<br />
Equations<br />
u x = f (x, u, θ) x<br />
Simulation: given u <strong>and</strong> f, find x<br />
Control: given x <strong>and</strong> f, find u<br />
<strong>Identification</strong>: given u <strong>and</strong> x, find f<br />
?<br />
SysID: an Inverse Problem<br />
Given the answer, what are the questions,<br />
i.e., look at the results <strong>and</strong> try to figure<br />
out what situation caused those results.<br />
Classification<br />
Parameter<br />
estimation <strong>System</strong><br />
identification<br />
Simulation<br />
(1) <strong>System</strong> <strong>Identification</strong><br />
Concerned with the mathematical<br />
structure of a flight vehicle model<br />
(2) Parameter Estimation<br />
Quantifying of parameters for a<br />
selected flight vehicle model<br />
Is the commonly used terminology<br />
PID appropriate?<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 4
Why <strong>System</strong> <strong>Identification</strong>?<br />
Need <strong>and</strong> quest to better underst<strong>and</strong> the system<br />
- Cause-effect relationship purported to underlie the physical phenomenon<br />
Mathematical models required for:<br />
- Investigation of system performance <strong>and</strong> characteristics<br />
- <strong>Aerodynamic</strong> databases valid over operational envelope for flight simulators<br />
- High-fidelity / high-b<strong>and</strong>width models for in-flight simulators<br />
- <strong>Flight</strong> control law design<br />
- Analysis of h<strong>and</strong>ling qualities compliance<br />
<strong>Aerodynamic</strong> databases <strong>from</strong> flight data<br />
- Analytical estimates: validity <strong>and</strong> inadequate theory !<br />
- Wind-tunnel predictions: model scaling, Reynold's number,<br />
dynamic derivatives, cross coupling, aero-servo-elastic effects !!<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 5
Classical Approach<br />
1919 - mid 1960's<br />
Classical<br />
Methods<br />
- Deterministic<br />
-Graphical<br />
(Paper & Pencil)<br />
- Frequency domain<br />
- Analog computation<br />
Transition Phase<br />
Late 1960's<br />
Dinosauric<br />
Digital<br />
Computation<br />
Modern Era<br />
1966 - 2008<br />
Advanced<br />
Methods<br />
- Statistical analysis<br />
- Time domain<br />
- Frequency domain<br />
- Digital computation<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 6
Unified Approach to<br />
<strong>Flight</strong> Vehicle <strong>System</strong> <strong>Identification</strong><br />
Maneuver<br />
Optimized<br />
Input<br />
A Priori Values,<br />
lower/upper<br />
bounds<br />
Model<br />
Structure<br />
Input<br />
Complementary<br />
<strong>Flight</strong> <strong>Data</strong><br />
Quad-M Basics<br />
<strong>Flight</strong> Vehicle<br />
M<br />
Estimation<br />
Algorithm /<br />
Optimization<br />
Actual<br />
Response<br />
Parameter<br />
odels Adjustments<br />
Mathematical<br />
Model /<br />
Simulation<br />
M<br />
ethods<br />
Model<br />
Validation<br />
Measurements<br />
<strong>Data</strong> Collection<br />
& Compatibility<br />
Parameter Estimation<br />
<strong>Identification</strong><br />
Criteria<br />
Response<br />
Error<br />
Model Response<br />
<strong>Identification</strong> Phase<br />
Validation Phase<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 7<br />
+<br />
-
Aircraft Parameter Estimation Methods<br />
Types <strong>and</strong> Classification<br />
Stable <strong>System</strong>s<br />
Regression Analysis<br />
- Linear modeling<br />
- <strong>Data</strong> compatibility required<br />
- <strong>Data</strong> partitioning<br />
Output Error Method<br />
- Accounts for measurement noise<br />
- Time <strong>and</strong> frequency domain<br />
Filter Error Method<br />
Accounts for both process noise<br />
(turbulence) <strong>and</strong> measurement noise<br />
Most general <strong>and</strong> most complex<br />
Neural Networks<br />
- Recurrent neural network<br />
- Feed forward neural network<br />
- Local model network<br />
Pilot<br />
inputs<br />
<strong>Flight</strong><br />
Control<br />
Unstable <strong>System</strong>s<br />
Surface<br />
Deflections<br />
Methods:<br />
- Regression Analysis<br />
- Filter Error Method<br />
- Extended Kalman Filter<br />
- Output Error Method with<br />
artificial stabilization<br />
Unstable<br />
Aircraft<br />
Motion<br />
Difficulties:<br />
- Open loop plant identification: basic aircraft<br />
is unstable (due to the aerodynamic design)<br />
- States <strong>and</strong> controls are highly correlated<br />
(due to the design of flight control laws)<br />
- Aircraft may be excited by process noise<br />
(e.g., induced by forebody vortices)<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 8
C nβ<br />
C nβ<br />
0.22<br />
0.20<br />
0.18<br />
0.16<br />
0.22<br />
0.20<br />
0.18<br />
Parameter Estimation Accounting for<br />
Atmospheric Turbulence<br />
Weathercock stability (yaw stiffness) Rudder effectiveness<br />
<strong>Flight</strong><br />
No.<br />
209<br />
112<br />
214<br />
219<br />
221<br />
216<br />
222<br />
223<br />
Output Error Method<br />
Filter Error Method<br />
0.16 -3 3 9<br />
Angle of Attack, deg<br />
flight in in<br />
turbulence<br />
15<br />
Output Error Method<br />
-0.36<br />
0.15 0.25 0.35<br />
Mach Number<br />
0.45 0.55<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 9<br />
C nζ<br />
C nζ<br />
-0.18<br />
-0.24<br />
-0.30<br />
-0.36<br />
-0.18<br />
-0.24<br />
-0.30<br />
Filter Error Method
A340-600, 2001<br />
EC-135, 2001<br />
N250-PA1, 1999<br />
A318-121, 2002<br />
Dornier 328, 1995-96<br />
X-31A, 1992-94<br />
A Retrospective<br />
Application Spectrum:<br />
<strong>Flight</strong> Vehicles<br />
Software Tools:<br />
ESTIMA<br />
FITLAB<br />
Dyn. Simulation in WT,1982<br />
Beaver DHC-2, 1983<br />
XV-15, 1990-91<br />
Transall C-160, 1992-93<br />
HFB-320, 1985<br />
ATTAS, 1989-90<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 10
High speed<br />
regime<br />
Stall approach<br />
<strong>and</strong> stall<br />
Single<br />
engine<br />
Take-off<br />
l<strong>and</strong>ing<br />
General Concept of <strong>Aerodynamic</strong><br />
Model <strong>Identification</strong><br />
Ground<br />
h<strong>and</strong>ling<br />
Normal <strong>Flight</strong><br />
regime<br />
Engine<br />
L<strong>and</strong>ing<br />
gear<br />
Ramp door<br />
Airdrop<br />
Ground<br />
effect<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 11
Altitude<br />
FL 300<br />
FL 260<br />
FL 160<br />
FL 80<br />
FL 20<br />
Elevator 3-2-1-1<br />
Short Period<br />
Typical <strong>Flight</strong> Test Program for<br />
<strong>System</strong> <strong>Identification</strong><br />
Test Case: C-160 Transall<br />
0.2 0.3 0.4 0.5 Mach No.<br />
80 KCAS<br />
100 KCAS<br />
120 KCAS<br />
160 KCAS<br />
100 150 200 250 300 True Airspeed (Kts)<br />
Elevator pulse<br />
Phugoid<br />
140 KCAS<br />
Bank angle<br />
Level Turn Maneuver<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 12<br />
195 KCAS<br />
Aileron/Spoiler<br />
Bank to Bank<br />
Maneuver<br />
230 KCAS<br />
Rudder Doublet<br />
Dutch Roll<br />
277 KCAS<br />
Thrust Doublet
Kinematic Consistency Checking of<br />
Recorded <strong>Data</strong><br />
General Approach, sensor model <strong>and</strong> estimation algorithm<br />
-To ensure that the measurements are<br />
consistent <strong>and</strong> error free.<br />
- Inertial measurements (accelerations <strong>and</strong><br />
angular rates are highly accurate.<br />
- Kinematic equations with no uncertainties;<br />
Accurate information about aircraft state;<br />
- Means to calibrate parameters with lower<br />
accuracy (angle of attack & sideslip).<br />
Kinematic Equations<br />
Linear Accelerations<br />
Velocity components<br />
Rotational rates<br />
∫<br />
(u, v, w)<br />
ax, ay, az, p, q, r Attitude angles<br />
Initial conditions: u 0, v 0, w 0, p 0, q 0, r 0<br />
Scale factors: K p, K q, K r<br />
Bias: Δa x, Δa y, Δa z, Δp, Δq, Δr<br />
Sensor calibration model<br />
Scale factor <strong>and</strong> bias<br />
Time delay<br />
p<br />
dα<br />
m<br />
= Kα<br />
p<br />
dyn<br />
α<br />
nb<br />
+ Δ p<br />
dα<br />
p<br />
dβ<br />
m<br />
= K<br />
β<br />
p<br />
dyn<br />
β<br />
nb<br />
+ Δ p<br />
dβ<br />
α α τ α τα<br />
Δ<br />
dα<br />
p ) t (<br />
p<br />
d m<br />
( t ) = K p<br />
dyn<br />
( t − q )<br />
nb<br />
− +<br />
Parameter estimation<br />
- Output error method for nonlinear systems<br />
- Bounded-Variable Gauss-Newton algorithm<br />
- Multiple experiment evaluation<br />
Kα , Δ p<br />
dα<br />
, Kβ<br />
, Δ p<br />
dβ<br />
, τα<br />
, τ<br />
β , τ<br />
q<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 13
Noseboom Mounted 5 Hole Probe<br />
<strong>Flight</strong> Validation ATTAS VFW-614<br />
K<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0 0.4 0.6 1.0 2.0<br />
Mach number<br />
<strong>Flight</strong> estimates Kα<br />
Calibration factors independent of configuration<br />
0.063<br />
0<br />
<strong>Flight</strong> Validation C-160<br />
20 40<br />
Flap<br />
deg 60<br />
Calibration factors configuration dependent<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 14<br />
Scale<br />
factor<br />
0.084<br />
0.077<br />
0.070<br />
ATTAS<br />
Kα<br />
K β
C-160: High-Fidelity Simulator <strong>Data</strong> Base<br />
<strong>Aerodynamic</strong> data base valid over<br />
the entire operational envelope<br />
- Nonlinear aerodynamics<br />
- Interference <strong>and</strong> coupling effects<br />
<strong>Identification</strong> of C-160 specific<br />
operational characteristics<br />
- Ramp door interference,<br />
- air drop, etc.<br />
<strong>Identification</strong> of dynamic stall<br />
- Unsteady flow separation<br />
<strong>Identification</strong> of<br />
- Ground effect<br />
- L<strong>and</strong>ing <strong>and</strong> Take-off<br />
- Failure states<br />
Validation of flight estimated database<br />
- FAA Level-D<br />
<strong>Flight</strong> estimate of dihedral effect<br />
Point ID: Single trim points<br />
Multi-Point ID: Several trim conditions<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 15<br />
-0.12<br />
C lβ<br />
-0.18<br />
η = 40°<br />
K<br />
η = 30°<br />
K<br />
L<strong>and</strong>ing<br />
Flap<br />
Point <strong>Identification</strong><br />
Multi-point <strong>Identification</strong><br />
-0.24<br />
η = 20°<br />
K η = 0° K<br />
-6 0 6 deg 12<br />
Angle of Attack
elevator<br />
deflection<br />
<strong>Identification</strong> of Elevator Control Effectiveness<br />
Test Case: Transall C-160<br />
2<br />
deg<br />
-18<br />
0 10 20 s 30<br />
time<br />
-6<br />
m/s2<br />
Vertical<br />
acceleration<br />
pitchrate<br />
angle of<br />
attack<br />
-12<br />
8<br />
deg/s<br />
0<br />
-8<br />
18<br />
deg<br />
6<br />
Linear model<br />
Accounting for nonlinearity<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 16<br />
-6<br />
m/s2<br />
Vertical<br />
acceleration<br />
pitch rate<br />
angle of<br />
attack<br />
-12<br />
8<br />
deg/s<br />
0<br />
18<br />
deg<br />
6<br />
Effectiveness<br />
Deflection
<strong>Aerodynamic</strong> <strong>Modeling</strong>: Complex Models<br />
Linear models (e.g. Rolling moment coefficient)<br />
C<br />
l<br />
= C + C<br />
l0<br />
l<br />
β<br />
β + C<br />
l<br />
p<br />
+ C r + C<br />
l r l<br />
Nonlinear models (e.g. Tail lift coefficient)<br />
Unsteady aerodynamics (e.g. Stall hysteresis)<br />
p<br />
ξ<br />
ξ + C ζ<br />
lζ<br />
Lη 2 α 2 α T CLη 3 η 2<br />
T L Lη α C = C α + C η + C T + C + η<br />
L T<br />
L T α<br />
α<br />
Unsteady <strong>Aerodynamic</strong> Model<br />
Lift coefficient<br />
C L (α, x) = C Lα<br />
Flow Separation Point<br />
x<br />
1 + x<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 17<br />
α<br />
x = 0<br />
CL( α,<br />
x)<br />
x = 1<br />
2<br />
2<br />
α
α<br />
a Z<br />
θ<br />
V<br />
δ e<br />
25<br />
deg<br />
-10<br />
0.0<br />
g<br />
-1.2<br />
20<br />
deg<br />
-40<br />
140<br />
kt<br />
80<br />
20<br />
deg<br />
Time Responses<br />
-30<br />
0 20 40<br />
Time, sec<br />
Unsteady <strong>Aerodynamic</strong>s<br />
60<br />
Lift Coefficient<br />
0.0<br />
-8 0 8 16 24<br />
Angle of Attack α , deg<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 18<br />
C L<br />
3.0<br />
2.0<br />
1.0<br />
DO 328<br />
<strong>Flight</strong> measured<br />
Model identified
<strong>Modeling</strong> of L<strong>and</strong>ing Gear Effects (1)<br />
<strong>Modeling</strong> <strong>and</strong> Experimental Aspects<br />
Important for simulation of<br />
take-offs <strong>and</strong> l<strong>and</strong>ings<br />
Longitudinal <strong>and</strong> lateral-directional<br />
maneuvers with gear down<br />
8000 ft <strong>and</strong> 16000 ft<br />
120, 140 <strong>and</strong> 160 kts<br />
Test Case: Transall C-160<br />
Basic aerodynamic model:<br />
Discernible deviations in<br />
- longitudinal motion<br />
- lateral-directional motion variables<br />
Neglecting L<strong>and</strong>ing Gear Effects<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 19<br />
a<br />
r<br />
θ<br />
α<br />
β<br />
x<br />
m/s 2<br />
1.2<br />
.0<br />
10<br />
deg/s<br />
0<br />
-8<br />
13<br />
deg<br />
0<br />
-7<br />
5<br />
deg<br />
0<br />
8<br />
deg<br />
0<br />
-8<br />
0 20 40 s<br />
60<br />
Time<br />
<strong>Flight</strong> measurement (C-160 Transall)<br />
Model identification
<strong>Modeling</strong> of L<strong>and</strong>ing Gear Effects (2)<br />
<strong>Modeling</strong> of <strong>Aerodynamic</strong> Effects due to LG<br />
Incremental aerodynamic modeling<br />
Longitudinal motion:<br />
Lift, drag <strong>and</strong> pitching moment coeff.<br />
ΔC LLG , ΔC DLG , ΔC mLG<br />
Lateral-Directional motion:<br />
- Increased weathercock stability ΔC nβLG<br />
- Sideforce due to sideslip ΔC YβLG<br />
Test Case: Transall C-160<br />
Accounting for L<strong>and</strong>ing Gear Effects<br />
-8<br />
0 20 Time 40 s 60<br />
<strong>Flight</strong> measurement (C-160 Transall)<br />
Model identification<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 20<br />
a<br />
r<br />
θ<br />
α<br />
β<br />
x<br />
1.2<br />
m/s 2<br />
.0<br />
10<br />
deg/s<br />
0<br />
-8<br />
13<br />
deg<br />
0<br />
-7<br />
5<br />
deg<br />
0<br />
8<br />
deg<br />
0
Verticalacceleration<br />
Pitch<br />
rate<br />
Pitch<br />
attitude<br />
Pitch<br />
acceleration<br />
CGlocation<br />
-8<br />
m/s 2<br />
-13<br />
-13<br />
5<br />
5<br />
deg/s deg/s<br />
-5<br />
8<br />
deg<br />
2<br />
deg/s<br />
-2<br />
8<br />
20<br />
Measurement<br />
Simulation<br />
C-160: Load Drop (4.6 t)<br />
Neglecing Variations in Aircraft Mass<br />
Characteristics<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 21<br />
-8<br />
m/s 2<br />
-5<br />
6<br />
deg<br />
2<br />
deg/s<br />
-16<br />
-16<br />
50<br />
50<br />
% %<br />
0 5 10 15<br />
Time (sec)<br />
2<br />
8<br />
20<br />
Accounting for Variations in the<br />
Aircraft Mass Characteristics<br />
0 5 10<br />
Time (sec)<br />
15
How do you know that you got the<br />
right answer?<br />
1.<br />
2.<br />
3.<br />
4.<br />
5.<br />
St<strong>and</strong>ard derivations<br />
Correlation among the estimates<br />
Goodness of fit<br />
Plausibility of estimates<br />
(WT data base)<br />
Model predictive capability<br />
"ACID TEST"<br />
Simulation <strong>and</strong> comparison with<br />
flight data not used in identification<br />
<strong>Data</strong> Base Validation (1)<br />
-12<br />
10<br />
deg/sec<br />
-7<br />
0 2 Time, sec 4 6<br />
10<br />
dB<br />
0<br />
Magn.<br />
-10<br />
q model<br />
qmeasured<br />
model<br />
90<br />
deg<br />
0<br />
Phase<br />
q model<br />
qmeasured<br />
-90<br />
0.1 1.0<br />
10 100<br />
Frequency, rad/sec<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 22<br />
q<br />
9<br />
deg<br />
δ e<br />
C-160 Pitch Response<br />
q model
C nβ<br />
0.3<br />
1/rad<br />
0.2<br />
Weathercock stability<br />
WT/analytical<br />
prediction<br />
flight estimates<br />
δ f = 30°<br />
δ f = 0°<br />
0.1<br />
-10 0<br />
angle of attack<br />
deg 15<br />
Tolerances:<br />
Frequency: +- 0.5 s or 10%<br />
Damping: +- 0.02<br />
<strong>Data</strong> Base Validation (2)<br />
yaw<br />
rate<br />
-8<br />
0 5 time 10 15 s 20<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 23<br />
10<br />
deg/s<br />
0<br />
-10<br />
8<br />
deg<br />
angle<br />
0<br />
of<br />
sideslip<br />
-8<br />
8<br />
deg<br />
rudder<br />
0<br />
<strong>Flight</strong> measured<br />
Dutch roll dynamics<br />
WT database prediction<br />
SysID database prediction<br />
WT-Predictions: 4.18 s 0.207<br />
<strong>Flight</strong> estimated <strong>Data</strong>base: 5.04 s 0.202<br />
<strong>Flight</strong> recorded responses: 5.12 s 0.198
Do-328: St<strong>and</strong>-alone versus Integrated Models<br />
Aircraft<br />
Motion<br />
Variables<br />
Pilot Input<br />
Forces<br />
Pilot<br />
Input<br />
Forces<br />
<strong>Data</strong> Base Validation (3)<br />
Reversible<br />
<strong>Flight</strong> Control<br />
Dynamics<br />
Control<br />
Surface<br />
Deflect.<br />
<strong>Flight</strong> controls st<strong>and</strong>-alone<br />
Reversible<br />
<strong>Flight</strong> Control<br />
Dynamics<br />
Control<br />
Surface<br />
Deflect.<br />
Control<br />
Surface<br />
Deflect.<br />
Integrated model<br />
measured data simulated data<br />
Rigid Body<br />
Dynamics<br />
Rigid Body<br />
Dynamics<br />
Aircraft<br />
Motion<br />
Variables<br />
Rigid-body st<strong>and</strong>-alone<br />
Aircraft<br />
Motion<br />
Variables<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 24
V<br />
h<br />
θ<br />
φ<br />
δ e<br />
<strong>Data</strong> Base Validation (4)<br />
DO-328:Normal L<strong>and</strong>ing<br />
130<br />
kt<br />
90<br />
250<br />
ft<br />
0<br />
10<br />
deg<br />
-5<br />
5<br />
deg<br />
-10<br />
20<br />
deg<br />
-10<br />
10<br />
deg<br />
δr Complete L<strong>and</strong>ing Phase<br />
3 kt<br />
10 ft<br />
1.5 deg<br />
2 deg<br />
-5<br />
0 10 Time (sec)<br />
20<br />
0<br />
8<br />
deg<br />
θ<br />
2<br />
5<br />
deg<br />
φ<br />
<strong>Flight</strong> measured (DO 328)<br />
Model identified<br />
FAA AC 120-40C tolerances<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 25<br />
h<br />
δ e<br />
60<br />
ft<br />
-5<br />
0<br />
deg<br />
-10<br />
Exp<strong>and</strong>ed View (Touch down)<br />
10 ft<br />
1.5 deg<br />
2 deg<br />
14 16<br />
Time (sec)<br />
18
Validation Example 3:<br />
Critical Engine Failure (DO 328)<br />
Engine failure during the critical<br />
phase of takeoff<br />
Response to rudder <strong>and</strong><br />
aileron important<br />
Complete sequence as a single time<br />
segment (st<strong>and</strong>-still, acceleration,<br />
Rotation, <strong>and</strong> climb to 200 ft)<br />
No closed-loop controller<br />
Tolerances: 3 kt on airspeed<br />
20 ft on altitude<br />
1.5 deg on pitch attitude<br />
2.0 deg on bank<br />
<strong>Data</strong> Base Validation (5)<br />
<strong>Flight</strong> measured<br />
Model identified<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 26<br />
V<br />
h<br />
θ<br />
φ<br />
δ e<br />
δ r<br />
150<br />
kt<br />
0<br />
-50<br />
300<br />
ft<br />
0<br />
-100<br />
15<br />
deg<br />
0<br />
-5<br />
10<br />
deg<br />
0<br />
-5<br />
30<br />
deg<br />
0<br />
-15<br />
10<br />
deg<br />
0<br />
-20<br />
4000<br />
daN<br />
FL , FR 0<br />
-2000<br />
left engine shut off<br />
0 10 20 30 s<br />
time
Wake Vortex Aircraft Encounter Model (1)<br />
Full Scale <strong>Flight</strong> tests: <strong>Data</strong> Gathering<br />
Wake vortex encounters:<br />
- Aircraft reaction dominantly affected<br />
- Critical situation during<br />
safety-critical flight phases<br />
(l<strong>and</strong>ing, vicinity of airport)<br />
Full scale flight tests with ATTAS<br />
followed by Do-128 or Cessna Citation<br />
Separation class medium<br />
wake<br />
generation<br />
100 encounters under steady atmospheric conditions.<br />
smoke trace<br />
0.5 nm<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 27<br />
1 nm<br />
1.5 nm<br />
Reaction of follower Aircraft:<br />
- Up to 80° bank angle; typical 30-40°; Bump; Uncomfortable; usually does not<br />
lead to loss of control (banking motion is averaged out)<br />
- More important: lateral acceleration; may lead to injury to crew or Passenger
Wake Vortex Aircraft Encounter Model (2)<br />
Schematic of Two Step Procedure for Vortex Model <strong>Identification</strong><br />
measured<br />
flight test test<br />
data<br />
data<br />
pilot’s<br />
control<br />
inputs<br />
flow measurements<br />
accel.,<br />
rates, flight flight<br />
attitude, path path<br />
altitude, reconstruction<br />
reconstruction<br />
velocity (FPR) (FPR)<br />
basic basic<br />
A/C A/C aero aero<br />
model model<br />
aerodynamic<br />
interaction<br />
model model<br />
Vortex model<br />
forces,<br />
moments<br />
+ 6-DOF 6-DOF<br />
A/C<br />
+ A/C<br />
simulation<br />
Δ forces,<br />
Δ moments<br />
wake vortex<br />
characteristics<br />
accelerations, rates,<br />
attitude, altitude, velocity<br />
-<br />
outputs<br />
step 1:<br />
“Flow field<br />
characterization”<br />
step 2:<br />
“Encounter model<br />
validation”<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 28<br />
+<br />
model<br />
accuracy
Wake Vortex Aircraft Encounter Model (3)<br />
Analytical Model<br />
The model consists of two idealized,<br />
superimposed counter-rotating single<br />
Vortices. Model parameters:<br />
- vortex circulation Γ,<br />
- core radius r C,<br />
- lateral vortex separation b V,<br />
- vortex location in space.<br />
The tangential velocity of one vortex<br />
as a function of the distance <strong>from</strong> the<br />
core, V t(r), is described in terms of the<br />
circulation Γ <strong>and</strong> the core radius r C:<br />
Lamb − Oseen :<br />
V<br />
t<br />
( r)<br />
=<br />
Γ<br />
2π<br />
r<br />
⎜<br />
⎛1− e<br />
⎝<br />
−1.<br />
2544r<br />
2 /<br />
r<br />
2<br />
c<br />
⎟<br />
⎞<br />
⎠<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 29<br />
V t,max<br />
r C<br />
left<br />
vortex<br />
V<br />
t<br />
b v<br />
V t<br />
Burnham<br />
( r)<br />
=<br />
−<br />
r C<br />
right<br />
vortex<br />
Hallock<br />
Γ r<br />
2π<br />
r<br />
2<br />
r<br />
2<br />
c<br />
+<br />
:<br />
y
Wake Vortex Aircraft Encounter Model (4)<br />
Wake velocity components during lateral encounter<br />
horizontal velocity vertical velocity<br />
Noseboom<br />
Right wing<br />
Left wing<br />
15<br />
m/s<br />
-20<br />
10<br />
m/s<br />
-15<br />
10<br />
m/s<br />
-15<br />
0 2<br />
time<br />
4 S 6<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 30<br />
10<br />
m/s<br />
-15<br />
6<br />
m/s<br />
-8<br />
6<br />
m/s<br />
-8<br />
0 2 4 S<br />
time<br />
6
Wake Vortex Aircraft Encounter Model (5)<br />
<strong>Flight</strong> estimated vortex model parameters<br />
Identified core radius r C<br />
<strong>and</strong> circulation Γ of the<br />
Burham-Hallock model<br />
for do-128 encounters<br />
<strong>from</strong> three flights.<br />
Conformance with Theory:<br />
- Expected decay of circulation<br />
- Increase of core radius<br />
- Initial core radius ~ 0.75 m,<br />
(roughly 3.5% of the wake<br />
Generating wing span which<br />
Is somewhat smaller than<br />
Commonly stated value of 5%)<br />
circulation, m 2 /s<br />
core radius, m<br />
200<br />
160<br />
80<br />
0<br />
3.0<br />
2.0<br />
1.0<br />
0.0<br />
<strong>Flight</strong> 1, 14.08.2001<br />
<strong>Flight</strong> 2, 15.08.2001<br />
<strong>Flight</strong> 3, 22.03.2002<br />
0 1 2 3 4 5<br />
normalized time t*=t/t 0<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 31
EC-135 Flying Helicopter Simulator (1)<br />
Model Predictive Capability<br />
Forward speed 60 kts:<br />
Two flight maneuvers (Lateral <strong>and</strong><br />
pedal inputs)<br />
6-DOF Rigid-Body model:<br />
- Angle of attack dependent lateraldirectional<br />
derivatives<br />
- Nonlinear aerodynamics; Weathercock<br />
stability for +ve <strong>and</strong> -ve sideslip angles<br />
0 10 20<br />
time<br />
30 s 40<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 32<br />
p<br />
q<br />
r<br />
0.3<br />
rad/s<br />
0<br />
-0.5<br />
0.3<br />
rad/s<br />
0<br />
-0.3<br />
0.3<br />
rad/s<br />
α<br />
β<br />
0<br />
-0.3<br />
0.2<br />
rad<br />
0<br />
-0.2<br />
0.3<br />
rad<br />
0<br />
-0.3<br />
75<br />
%<br />
δ lat,<br />
δ ped<br />
35
EC-135 Flying Helicopter Simulator (2)<br />
Rotor Wake <strong>Modeling</strong><br />
Roll <strong>and</strong> pitch in hover <strong>and</strong> at low speeds:<br />
unsymmetrical vortex compression <strong>and</strong><br />
dilatation act on the induced velocity field<br />
in the proximity of the main rotor.<br />
Effective AoA at the blade sections changed.<br />
<strong>Aerodynamic</strong> rotor loads directly affected.<br />
Rotor gyroscopic behavior due to the blade<br />
flapping dynamics forced by these loads<br />
leads to strong cross coupling effects of the<br />
helicopter due to the wake distortion.<br />
Current research topic:<br />
Suitable flight dynamic models describing<br />
this phenomenon to obtain improved<br />
simulation fidelity in off-axis response<br />
Pure Hover<br />
Pitching motion in Hover<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 33
EC-135 Flying Helicopter Simulator (3)<br />
Dynamic Wake Model: Parametric extension of Pitt <strong>and</strong> Peters:<br />
⎡ ⎤<br />
⎢<br />
0<br />
−<br />
−1<br />
⎥<br />
λ + λ = + L ⎢K<br />
−β<br />
⎥<br />
Ω ⎢<br />
p<br />
( p<br />
s<br />
)<br />
⎥<br />
⎢K<br />
( q −β<br />
) ⎥<br />
⎣ q c ⎦<br />
ˆ<br />
1 1<br />
L c ˆ M &<br />
&<br />
&<br />
M: Apparent mass matrix associated with the<br />
acceleration terms <strong>from</strong> momentum theory<br />
L: gain matrix, λ (= [λ 0 , λ s , λ c ] T ) the inflow ratio<br />
describing the first harmonic terms<br />
c (= [c T , c 1 , c m ] T ): rotor load coefficients wrt rotor<br />
thrust <strong>and</strong> aerodynamic pitch <strong>and</strong> roll moment,<br />
Ω: main rotor rotation speed<br />
K p <strong>and</strong> K q: Wake distortion parameters for<br />
longitudinal <strong>and</strong> lateral distribution of the<br />
induced velocity.<br />
Last term on RHS: Parametric term that feeds<br />
back the roll <strong>and</strong> pitch rates of the rotor tip<br />
path plane wrt to the surrounding air to the<br />
induced velocity distribution over the rotor disk<br />
Estimate Kp <strong>and</strong> Kq Theoretical estimates of<br />
Wake distortion parameters<br />
From flight tests applying<br />
SysId methods:<br />
Kq = 1.6; Kp = 2.5 (μ = 0)<br />
μ= V H /ΩR; V H : forward speed<br />
m/s; Ω: main rotor rotation<br />
speed rad/s; R: rotor radius in m.<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 34
Dynamic Wake Model: Parametric extension of Pitt <strong>and</strong> Peters:<br />
Simulation fidelity at Hover<br />
20<br />
Inflow Dynamics<br />
Roll Rate Pitch Rate deg/s<br />
Lateral Input Longitudinal<br />
Input<br />
20<br />
0<br />
-20<br />
-30<br />
30<br />
20<br />
deg/s<br />
0<br />
-20<br />
2<br />
deg<br />
0<br />
-3<br />
4<br />
deg<br />
2<br />
0<br />
EC-135 Flying Helicopter Simulator (4)<br />
<strong>Flight</strong> case #1 <strong>Flight</strong> case #2<br />
with theoretical<br />
WD-parameters<br />
with flight<br />
identified WD<br />
parameters<br />
-1<br />
20 25<br />
time<br />
30 s 35<br />
Pitch<br />
Rate<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 35<br />
deg/s<br />
10<br />
0<br />
-10<br />
-20<br />
20<br />
60 64 Distortion s 68<br />
deg/s<br />
10<br />
0<br />
-10<br />
-20<br />
Inflow <strong>and</strong> Wake<br />
time<br />
<strong>Flight</strong> <strong>Data</strong><br />
Simulation<br />
60 64 s 68<br />
time
EC-135 Flying Helicopter Simulator (5)<br />
Dynamic Wake Model: Parametric extension of Pitt <strong>and</strong> Peters:<br />
Forward speed 40 m/s<br />
μ= V H /ΩR = 0.18<br />
Theoretical estimate = 0<br />
From flight tests applying<br />
SysId methods:<br />
Kq = 1.6; Kp = 1.1 Good match<br />
But, estimates do not conform to<br />
The wake distortion theory.<br />
Anomaly: Parameters do not<br />
Represent wake distortion which<br />
occurs at hover. They account for<br />
Other unmodeled effects (rigid /<br />
elastic blade formulation).<br />
without PWD<br />
with PWD<br />
0<br />
0 2 4 6 8 s 10<br />
time<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 36<br />
Roll Rate Pitch Rate<br />
Lateral Input Longitudinal<br />
Input<br />
15<br />
deg/s<br />
0<br />
-10<br />
20<br />
deg/s<br />
0<br />
-20<br />
-40<br />
-1<br />
deg<br />
-3<br />
-5<br />
4<br />
deg<br />
2<br />
<strong>Flight</strong> case #1 <strong>Flight</strong> case #2
Phoenix: Reusable orbital glider (1)<br />
Wind-tunnel testing in August 2003<br />
Pre-flight checks: April 2004<br />
calibration of flow angles:<br />
p p<br />
d<br />
d<br />
α = α<br />
β<br />
+ korrβ<br />
+ α<br />
K q q<br />
α<br />
c<br />
offset<br />
α-error nonlinear:<br />
quadratic or piecewise linear<br />
Accuracy:<br />
AoA <strong>and</strong> AoS: < 0.5°<br />
Horizontal velocity: 0.5 m/s<br />
c<br />
-0.6<br />
-10 -5 0 5 10 15 20 deg 25<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 37<br />
Alpha-error<br />
after linear calibration<br />
0.8<br />
deg<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
-0.2<br />
-0.4<br />
40 m/s<br />
70 m/s<br />
100 m/s<br />
alpha
<strong>Flight</strong> phases<br />
upon release:<br />
1) Acquisition<br />
2) Approach<br />
3) Flare<br />
4) Alignment<br />
5) Derotation<br />
6) Rollout<br />
Phoenix: Reusable orbital glider (2)<br />
Reference Mission:<br />
Towed to establish<br />
initial conditions<br />
touch<br />
down<br />
lift-off<br />
altitude<br />
510m<br />
Launch at<br />
40m/s EAS<br />
RLV<br />
approach<br />
path -23o RLV<br />
approach<br />
path -23o acquisition<br />
dive<br />
6.6km<br />
118m/s<br />
release Phoenix<br />
<strong>from</strong> helicopter<br />
ground track<br />
flare<br />
2.65km<br />
Phoenix free<br />
flight profile<br />
touch down<br />
71m/s<br />
runway<br />
45m x 2100m<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 38
Free flights:<br />
Maiden flight on 8-May-2004<br />
Repeat flight on 13-May-2004<br />
3rd flight with Offset on 16-May-2004<br />
Configuration:<br />
Delta Wing, relatively low wing span<br />
3 controls (flaperons <strong>and</strong> rudder)<br />
Body flap <strong>and</strong> speed brake<br />
1200 Kg<br />
7m long<br />
3,48 m span<br />
Highly dynamic behavior<br />
High b<strong>and</strong>width control loops<br />
Video<br />
<strong>Flight</strong> 1 <strong>and</strong> <strong>Flight</strong> 3<br />
Phoenix: Reusable orbital glider (3)<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 39
<strong>Aerodynamic</strong> <strong>Data</strong>base:<br />
Verification <strong>and</strong> Update -- Principle<br />
Measured<br />
AX, AY, AZ,<br />
p, q, r,<br />
pdyn<br />
Measured<br />
dero, delo,<br />
dari, deli,<br />
dr, dbf, dsb,<br />
p, q, r,<br />
al, be<br />
Phoenix: Reusable orbital glider (4)<br />
p_dot, q_dot, r_dot<br />
AX_cg, AY_cg, AZ_cg<br />
X, Y, Z, L_cg, M_cg, N_cg<br />
X, Y, Z, L_ac, M_ac, N_ac<br />
Windtunnel <strong>Data</strong>base<br />
(aerodataV31)<br />
SysID<br />
Corrections<br />
<strong>Flight</strong> derived<br />
CX, CY, CZ<br />
CLX, CMY, CNZ<br />
WT-Predictions<br />
CX, CY, CZ<br />
CLX, CMY, CNZ<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 40<br />
Δs
Total CZ<br />
0<br />
-0.05<br />
-0.1<br />
-0.15<br />
-0.2<br />
-0.25<br />
-0.3<br />
-0.35<br />
-0.4<br />
-0.45<br />
Phoenix: Reusable orbital glider (5)<br />
<strong>Flight</strong> derived <strong>and</strong> WT predicted vertical force coefficient<br />
<strong>Flight</strong>-derived<br />
ff-n1 flight measurements<br />
ff-n2 flight measurements<br />
ff-n3 flight measurements<br />
ff-n1 wind-tunnel<br />
ff-n2 wind-tunnel<br />
ff-n3 wind-tunnel<br />
Pre-flight ADB<br />
-0.5<br />
0 0.05 0.1 0.15 0.2 0.25<br />
Angle of attack (rad)<br />
Rough order of<br />
discrepancies:<br />
CZ: 9-10%<br />
Cm: < 3%<br />
CD: ~10% Nonlinear<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 41
Phoenix: Reusable orbital glider (6)<br />
Aero model update (In-Air)<br />
q<br />
CZ = CZ + CZ<br />
δ<br />
Δ 0<br />
q<br />
CX = CX + CX<br />
δ<br />
Δ 0<br />
Δ 0<br />
α α + CZ q + CZδ<br />
bf<br />
Lref<br />
V<br />
α α + CX q + CX δ sb<br />
Lref<br />
V<br />
CMY = CM + CM<br />
δ<br />
α α + CM δ e δ e + CM δ sb<br />
12 Parameters CZ (), CX () <strong>and</strong> Cm () are estimated to<br />
reduce the deviations between flight measurements <strong>and</strong><br />
WT-predictions.<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 42<br />
bf<br />
sb<br />
sb
Delta CZ<br />
0.03<br />
0.02<br />
0.01<br />
0<br />
-0.01<br />
-0.02<br />
-0.03<br />
-0.04<br />
-0.05<br />
Phoenix: Reusable orbital glider (7)<br />
<strong>Flight</strong> derived <strong>and</strong> Updated database<br />
-0.06<br />
0 0.05 0.1 0.15 0.2 0.25<br />
Angle of attack (rad)<br />
Important Inferences:<br />
- lift generated in flight is higher<br />
ff-n1<br />
ff-n2<br />
ff-n3<br />
- component due to pitch rate in lift <strong>and</strong><br />
drag is not adequately accounted for.<br />
- basic longitudinal force coefficient for<br />
clean configuration underestimated,<br />
- impact of speedbrakes overestimated.<br />
Delta CZ versus AoA<br />
without <strong>and</strong> with update<br />
-0.06<br />
0 0.05 0.1 0.15 0.2 0.25<br />
Angle of attack (rad)<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 43<br />
Delta CZ<br />
0.03<br />
0.02<br />
0.01<br />
0<br />
-0.01<br />
-0.02<br />
-0.03<br />
-0.04<br />
-0.05<br />
ff-n1<br />
ff-n2<br />
ff-n3
Automatic Envelope Expansion through<br />
Adaptive <strong>Flight</strong> Control (1)<br />
Expansion to flight<br />
regimes not<br />
accounted for during<br />
the controller design<br />
(Design based on<br />
linear Hover model)<br />
<strong>Flight</strong> demonstration<br />
of adaptive flight<br />
control<br />
Reference Model<br />
Limitations<br />
Reference Dynamics<br />
Reference States<br />
Déjà-vu: Modules of adaptive control system<br />
Nonlinear Compensator<br />
Input<br />
Feed Forward<br />
Coupling<br />
Known Disturbances<br />
Nonlinear Effects<br />
Feedback<br />
Hidden<br />
Stability<br />
Output<br />
layer<br />
Error Compensation<br />
Error Response Dynamics<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 44<br />
Σ
| Velocity Control Error | in m/s<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0<br />
Automatic Envelope Expansion through<br />
Adaptive <strong>Flight</strong> Control (2)<br />
<strong>Flight</strong> test results: Forward flight (>10m/s) with midiARTIS<br />
without adaptive Element<br />
mean error<br />
with adaptive Element<br />
mean error<br />
Significant reduction in<br />
error coom<strong>and</strong>ed speed<br />
Reduction in the mean<br />
error by factor of 10<br />
50 100 150 200 250<br />
Time in s<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 45
The Future<br />
Prime areas of applications:<br />
<strong>Aerodynamic</strong> database generations<br />
<strong>Modeling</strong> of nonlinear aerodynamics<br />
Unstable aircraft<br />
New measuring techniques for air data<br />
Flush air data sensors<br />
optical sensors<br />
Real-Time parameter estimation is re-emerging (after seventies)<br />
Full flexible aircraft models (integration of flight mechanics <strong>and</strong> structural<br />
models) -- distributed mass models<br />
<strong>Modeling</strong> <strong>and</strong> identification of UAVs, mAVs<br />
Integrating <strong>System</strong> <strong>Identification</strong> <strong>and</strong> Computational Fluid Dynamics<br />
methodologies<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 46
Concluding Remarks<br />
Unified approach based on Quad-M basics <strong>and</strong> various aircraft parameter<br />
estimation methods<br />
Various examples covering global aerodynamic database, nonlinear effects,<br />
stall hysteresis, l<strong>and</strong>ing gear effects, load drop<br />
<strong>Modeling</strong> of wake vortex encounter<br />
<strong>Modeling</strong> of rigid-body <strong>and</strong> extended models for EC-135 helicopter<br />
<strong>Modeling</strong> of Reusable orbital glider<br />
Different aspects <strong>and</strong> examples of validation of identified models<br />
Summary:<br />
SysID methods provide a well proven <strong>and</strong> highly sophisticated tool<br />
for aerodynamic modeling <strong>from</strong> flight data.<br />
Experience, engineering judgement <strong>and</strong> skill to interpret the modeling<br />
discrepancies <strong>and</strong> formulate them mathematically mainly limits the scope<br />
of applications.<br />
Dr. Ravindra Jategaonkar RTO Mission at Tübitak-SAGE, Ankara, Turkey, 26-29 May 2008 pp. 47