Barron Associates’ Capabilities and Program Overview
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Transcript Barron Associates’ Capabilities and Program Overview
Integrated Adaptive Guidance &
Control for the X-37 during
TAEM & A/L
J. Schierman
Barron Associates, Inc., Charlottesville, Virginia
Paul Kubiatko
The Boeing Company, Huntington Beach
Air Force Research Laboratory Program
David Doman, PM
Presented at the
Aerospace Control and Guidance Systems Committee (ACGSC) Meeting
Grand Island, NY
Oct. 15-17
1410 Sachem Place ◊ Suite 202 ◊ Charlottesville, VA 22901
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ACGSC, October, 2008
Presentation Outline
Motivation/program background
X-37 IAG&C program
Some details on the developed technologies
Sample experimental results
Conclusions
Boeing presentation…
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ACGSC, October, 2008
Motivation & Technology Challenges
NASA & Air Force seeking to increase safety & reliability of
next generation launch systems
House software algorithms onboard to recover the system
when physically possible to:
Control effector and other subsystem failures
Larger than expected errors/dispersions
Nominal flying qualities not always recovered
w/ inner-loop control reconfiguration alone
Guidance adaptation may be necessary to
account for “crippled” vehicle
For unmanned, un-powered vehicles in
descent flight phases - energy management
problem critical for safe landing
If vehicle characteristics have changed, energy
management problem has changed
Energy managed with in-flight trajectory
command reshaping
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ACGSC, October, 2008
Feedback Architecture
Feedback architecture involves three main loops
Inner-loop control / Outer-loop guidance / Trajectory command generation
Trajectory
Command
Generation
Traj. Cmds.
Guidance
Laws
Inner-loop
Cmds.
Reconfigurable
Controller
Guidance
Adaptation
Algorithm
Re-solve energy
management problem –
critical for autonomous,
unpowered vehicles in
gliding flight
Our main
focus!
Effector
Cmds.
Reusable
Launch
Vehicle
Meas.
Resp.
Vehicle Health
Monitoring,
Filters,
Parameter ID,…
Maintain flight path stability
Recover cmd. following
performance to extent
possible
Maintain attitude stability
Recover cmd. following
performance to extent
possible
We have borrowed our
reconfigurable flight controls
technologies
New
approaches
developed
We have borrowed our
parameter ID technologies &
developed new algorithms
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ACGSC, October, 2008
Background - AFRL Program – ’01 to ‘04
Air Force’s Integrated Adaptive Guidance & Control
(IAG&C) flight test program
Demonstration platform: Boeing’s X-40A
Why the X-40A? Boeing accomplished 7 successful drop
tests - hoped to eventually repeat drop tests w/new
reconfigurable G&C algorithms
Risk reduction flight tests w/TIFS
Ensure software can run in real time
Verify simulation-based
performance analysis
Flight test results presented at SAE ’04 (Colorado)
Nominal
approach
trajectory
TIFS = Total In-Flight Simulator
5
Reconfigured trajectory
Nominal
touchdown
aim point
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ACGSC, October, 2008
AFRL Program Extension
IAG&C program extended – ’04-’05
Next logical step: continue work with Boeing to
develop / demonstrate IAG&C technologies for their
X-37 RLV
Ruddervators
Speedbrake
Flaperons
Bodyflap
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Program Summary Chart
Engineering, Operations & Technology | Phantom Works
Description:
• Demonstrate integrated adaptive guidance
and control system with on-line trajectory retargeting and reconfigurable control to
compensate for control effector failures using
a real-time hardware in-the -loop
simulation.
Value/Benefits:
More technically
• Safety and Reliability:
accurate than flight tests
System can compensate for unknown model errors.
• Weight:
Reduce redundancy requirements.
Key Technologies:
• Adaptive / reconfigurable Guidance and
Control algorithms.
Partners/Major Subcontractors
• Barron Associates, Inc.
Copyright © 2008 The Boeing Company. All rights reserved.
Distribution A, Cleared for Public Release, Distribution Unlimited. Case No. 88ABW-2008-0085 WPAFB, OH
Program Objectives
Engineering, Operations & Technology | Phantom Works
• Develop and demonstrate Integrated Adaptive Guidance
and Control (IAG&C) algorithms for reusable launch
vehicles by simulation analysis.
IAG&C algorithms developed under Phase II SBIRs and AFRL 6.2 X-40A
IAG&C program.
• Demonstrate that IAG&C architecture will automatically
compensate for control effector failures and plan new
feasible trajectories in real time when they exist.
Test on-line ID of ablation effects & failures
• Raise technology and integration readiness levels of IAG&C
system by testing algorithms in a real-time relevant
simulation environment.
Utilize existing Boeing X-37 Avionics Simulation Integration Lab
Copyright © 2008 The Boeing Company. All rights reserved.
Distribution A, Cleared for Public Release, Distribution Unlimited. Case No. 88ABW-2008-0085 WPAFB, OH
X-37 Simulation Environments Utilized
Engineering, Operations & Technology | Phantom Works
Matlab/Simulink Environment
IAG&C System Design
Linear Analysis (phase & gain margins)
Limited Worst-on-Worst analysis capability
Shuttle Descent-Approach Program (SDAP) Environment
Simulation validation
Performance Assessment
“Worst-on-Worst” Analysis
Monte Carlo Analysis
}
Avionics Systems Integration Lab (ASIL) Environment
Real-Time Performance Assessment
Copyright © 2008 The Boeing Company. All rights reserved.
Distribution A, Cleared for Public Release, Distribution Unlimited. Case No. 88ABW-2008-0085 WPAFB, OH
ACGSC, October, 2008
Expanded Envelope – TAEM and Approach & Landing
Focus: Boeing’s X-37 drop tests
Separation
& Dive
Alt = 40K ft
Range = 18.8 NM
Subsonic portion of TAEM
Approach & landing
Trajectory reshaping addresses
integrated TAEM/A/L mission
Heading
Alignment Cone
(HAC)
Nominal
initial
heading
= -135
deg.
-90o
heading
Acquisition
w/HAC
Groundtrack
Alt = 22.5K ft
Range = 9.5 NM
Heading
Alignment Cone
(HAC)
180o
heading
Approach/Landing
Touchdown & Rollout
Alt = 10K ft
Range = 4.5 NM
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ACGSC, October, 2008
Trajectory Reshaping Approach
Need fast optimization approach - deliver new trajectory solutions in flight
Redefine complete trajectory in terms of a small number of parameters to be
optimized
Once solution is obtained: map parameters back to full trajectory history
Trajectory parameters:
Initial heading angle
Altitude to start HAC turn
Altitude to start Final Flare guidance law
Dynamic pressure at touchdown
lCL, lCD: models trim CL,CD
under failure condition
}
Optimization problem posed:
d
Drop
co
Groundtrack
HHAC
Minimize lateral maneuvering
HAC Turn
Keeps solution from unrealistic sharp turns
yrwy
xrwy
Defines shape of last
stage of dynamic
pressure profile
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HFF
q TD
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ACGSC, October, 2008
Guidance & Control Laws
Lateral Backstepping Loops
Series of backstepping/dynamic
inversion feedback loops: maps d
to commanded trajectory histories
(V, , X, H, etc.) that drive guidance
loops
V, , L, D
c
H
c o , H HAC
Reshaping
Reshaping Algorithm
Algorithm
-
c cmd
+
fc
fq
q ref
-
f
Kq
+
-
K
cmd
3-DOF
3-DOF Plant
Plant
Model
Model
cmd
+
f
cmd
Commanded
Trajectory
States to
Guidance
Law
q
Ref.
Cmds.
f
CL, CD
l CL , l CD
H ff , q TD
Kc
H
, H , V, D
V, D, , q,
Longitudinal Backstepping Loops
L _ ruddervator
N Z cmd
Trajectory Cmd
Generation
Longitudinal
Guidance
Lateral
Guidance
cmd
Coordinated
Flight
Controller
Pcmd
R cmd
Receding
Horizon
Optimal
(RHO)
Controller
----Control
Allocator
R _ ruddervator
L _ flaperon
R _ flaperon
X-37
Vehicle
speedbrake
bodyflap
Measurement
Feedback…
Lift, Drag
Modified
Sequential Least
Squares (MSLS)
Parameter ID
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ACGSC, October, 2008
X-37 Drop Mission Case Study
Worst case low energy (high drag) failure - SB locked @ 65 deg. & BF locked @ 20 deg.
Ablation effects (add more drag); headwind/crosswind; navigation errors; turbulence
• Simulink and RTHIL results very close
• Adaptive system commands a “HAC turn”
soon into the mission – “cuts the corner” to
reduce downrange distance to runway –
conserves energy
Altitude Profile
Real-Time, HIL results
Ground Track
Real-Time, HIL results
• Adaptive system commands much steeper
descent – increases kinetic energy at
touchdown – allows for greater control
authority to execute final flare
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ACGSC, October, 2008
Real-Time HIL Experiment Results
51 cases run for final set of real-time Hardware-In-the-Loop experiments
Variations included: initial heading (HAC) angle, wind direction, ablation effects,
navigation errors, random turbulence, failure condition, and failure onset time
Failure
Wind
Touchdown Conditions
HAC
Right
Left
Body
Speed
Scale Ablation Sink Rate
Pitch Angle Groundspeed Downrange Crossrange
Input File
Onset
Angle
Rudder Rudder
Flap
Direction
Factor
(fps)
(deg)
(fps)
(ft)
(ft)
Name
Alttitude
Effects
Failure Brake
Wind
Touchdown
Conditions
HAC
Right
Left
Body
Speed
Scale Ablation Sink Rate
Pitch Angle Groundspeed Downrange Crossrange
Input File
Onset
2
135
0.862
4.888
307.616
3146.118
2.089
Angle
Rudder Rudder
Flap
Brake
Direction
Factor
(fps)
(deg)
(fps)
(ft)
(ft)
Name
Alttitude
Effects
4
135
EAFB HW
10%
0.151
7.940
332.815
2107.260
-0.357
28
135
-6
-6
40K
EAFB HW
10%
3.248
8.112
341.929
2151.379
0.168
5
135
EAFB TW
10%
0.886
4.855
305.884
3138.804
2.282
29
135
-6
-6
40K
EAFB TW
10%
0.456
7.372
304.959
3198.168
5.252
EAFB HWCW
6
135
10%
0.263
7.342
310.121
2888.012
1.903
30
135
-6
-6
40K
EAFB HWCW
10%
1.187
7.514
302.618
3293.566
5.557
EAFB TWCW
10%
7
135
1.646
7.433
279.657
4255.383
11.890
31
135
-6
-6
40K
EAFB TWCW
10%
0.638
5.433
302.733
3407.623
6.004
8
90
EAFB HW
10%
0.946
4.948
301.318
3090.743
2.893
EAFB TWCW
10%
32
90
20
65
40K
4.247
12.846
297.295
2222.689
14.536
9
180
EAFB TW
10%
0.785
7.772
339.080
2223.361
-1.217
EAFB TWCW
10%
33
100
20
65
40K
2.941
12.655
296.131
2337.721
-14.367
10
-90
EAFB HWCW
10%
2.741
7.516
362.810
1678.703
0.661
EAFB TWCW
10%
34
110
20
65
40K
2.746
12.792
295.110
2306.181
-18.777
11
-135
EAFB HWCW
10%
1.795
6.308
312.033
2760.766
4.611
EAFB TWCW
10%
35
120
20
65
40K
6.915
13.613
308.312
2145.319
-15.605
10%
12
-180
EAFB TWCW
1.025
4.123
308.488
3317.897
5.073
EAFB TWCW
10%
36
130
20
65
40K
3.050
13.336
303.750
2283.586
-11.120
13
135
20
65
40K
EAFB HW
10%
5.624
13.324
290.315
2223.785
-10.804
EAFB TWCW
10%
37
140
20
65
40K
6.749
13.194
309.011
2179.693
-8.396
14
135
20
65
40K
EAFB TW
10%
3.990
13.133
301.424
2258.649
-7.286
EAFB
TWCW
10%
38
150
20
65
40K
6.151
13.251
308.032
2199.266
-7.053
15
135
20
65
40K
EAFB HWCW
10%
6.440
13.252
291.252
2207.018
-10.619
EAFB TWCW
10%
39
160
20
65
40K
6.963
13.030
311.628
2160.595
-6.790
16
135
20
65
40K
EAFB TWCW
10%
2.578
13.413
300.683
2311.176
-8.793
EAFB
TWCW
10%
40
170
20
65
40K
6.882
13.350
308.939
2159.474
-5.692
17
135
20
65
35K
4.462
13.203
282.470
2316.449
-9.808
EAFB TWCW
10%
41
180
20
65
40K
2.429
13.559
301.803
2292.339
-4.995
18
135
20
65
34K
5.690
13.745
284.886
2286.887
-9.536
42
135
-20
0
40K
EAFB HW
10%
0.351
5.665
292.011
3612.635
2.030
19
135
20
65
33K
3.049
13.081
291.950
2343.315
-10.895
43
135
-20
0
40K
EAFB TW
10%
0.498
8.111
313.568
2884.063
0.658
on
20
135
20
65
40K
EAFB HW
10%
2.719
14.398
272.435
2450.673
-25.214
44
135
-20
0
40K
EAFB HWCW
10%
0.525
8.746
257.944
4589.362
3.733
on
21
135
20
65
40K
EAFB TW
10%
6.571
14.713
296.541
2255.102
-23.289
45
135
-20
0
40K
EAFB TWCW
10%
1.213
7.903
320.847
2831.176
0.806
on
22
135
20
65
40K
EAFB HWCW
10%
2.943
14.296
271.692
2467.679
-25.329
46
135
0
0
40K
EAFB HW
10%
2.642
6.965
312.638
2508.943
3.995
on
23
135
20
65
40K
EAFB TWCW
10%
3.394
14.846
292.592
2315.862
-23.868
47
135
0
0
40K
EAFB TW
10%
3.313
6.561
312.938
2666.653
5.364
24
135
-6
40K
EAFB HW
10%
1.448
8.150
312.263
2694.925
-15.266
48
135
0
0
40K
EAFB HWCW
10%
2.416
6.906
315.066
2516.830
3.881
25
135
-6
40K
EAFB TW
10%
2.730
7.804
316.690
2735.908
-16.530
49
135
0
0
40K
EAFB TWCW
10%
4.497
6.550
317.696
2701.305
4.799
26
135
-6
40K
EAFB HWCW
10%
1.846
8.053
313.906
2606.651
-16.504
50
135
0
30
40K
EAFB HW
10%
0.765
8.665
303.502
2247.709
1.036
27
135
-6
40K
EAFB TWCW
10%
2.871
7.710
319.479
2785.804
-14.749
51
135
0
30
40K
EAFB TW
10%
1.247
8.239
309.674
2349.663
1.709
Page 2
52
135
-
-
0
30
40K
EAFB HWCW
10%
-
0.945
8.609
53
135
-
-
0
30
40K
EAFB TWCW
10%
-
1.894
8.150
14
308.798
2168.552
0.998
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311.511
2365.091
1.613
ACGSC, October, 2008
Conclusions
Barron Associates focus:
Develop integrated TAEM/Approach & Landing trajectory reshaping and innerloop reconfigurable controller
Non-real-time Matlab/Simulink experiments performed during
development
Substantial number of experiments were run with dispersions in trajectory
geometry, winds, failure characteristics, and other errors
Overwhelming majority of these runs resulted in safe landings
Without the advanced algorithms, failures would cause loss of vehicle
Trajectory reshaping coupled with reconfigurable inner-loop control saved
vehicle from significant damage under severe effector impairments
Boeing tested algorithms in real-time simulations…
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