1410 Sachem Place ◊ Suite 202 ◊ Charlottesville, VA 22901 www.Barron-Associates.com 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
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Integrated Adaptive Guidance & Control for the X-37 during TAEM & A/L
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 - PowerPoint PPT Presentation
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1410 Sachem Place ◊ Suite 202 ◊ Charlottesville, VA 22901 www.Barron-Associates.com
Integrated Adaptive Guidance & Control for the X-37 during
TAEM & A/L
J. SchiermanBarron Associates, Inc., Charlottesville, Virginia
Paul Kubiatko The Boeing Company, Huntington Beach
Air Force Research Laboratory ProgramDavid Doman, PM
Presented at the Aerospace Control and Guidance Systems Committee (ACGSC) Meeting
Grand Island, NYOct. 15-17
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ACGSC, October, 2008
www.Barron-Associates.com
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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Motivation & Technology Challenges
NASA & Air Force seeking to increase safety & reliability of next generation launch systemsHouse software algorithms onboard to recover the system when physically possible to:
Control effector and other subsystem failuresLarger than expected errors/dispersions
Nominal flying qualities not always recovered w/ inner-loop control reconfiguration aloneGuidance adaptation may be necessary to account for “crippled” vehicleFor 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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Feedback ArchitectureFeedback architecture involves three main loops
Inner-loop control / Outer-loop guidance / Trajectory command generation
Maintain attitude stabilityRecover cmd. following performance to extent possible
Inner-loopCmds.
Meas.Resp.Reusable
Launch Vehicle
Reconfigurable Controller
EffectorCmds.
We have borrowed our reconfigurable flight controls
technologiesWe have borrowed our
parameter ID technologies & developed new algorithms
Re-solve energy management problem – critical for autonomous, unpowered vehicles in gliding flight
Traj. Cmds.Trajectory Command Generation
Our main focus!
Maintain flight path stabilityRecover cmd. following performance to extent possible
GuidanceAdaptationAlgorithm
Guidance Laws
New approaches developed
Required InformationVehicle Health
Monitoring,Filters,
Parameter ID,…
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Background - AFRL Program – ’01 to ‘04Air Force’s Integrated Adaptive Guidance & Control (IAG&C) flight test programDemonstration 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/TIFSEnsure software can run in real timeVerify simulation-based performance analysis
Nominal approach trajectory
Reconfigured trajectory
Nominaltouchdown aim point
TIFS = Total In-Flight Simulator
TIFS simulated
“X-40A”
dynamics
Flight test results presented at SAE ’04 (Colorado)
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AFRL Program ExtensionIAG&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
Bodyflap
Flaperons
Engineering, Operations & Technology | Phantom Works
and control system with on-line trajectory re-targeting and reconfigurable control to compensate for control effector failures using a real-time hardware in-the -loop simulation.
Value/Benefits: • Safety and Reliability:
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.
ID Task Name
1
2 1.0 Program Management3 Pogram Management
4 2.0 Guidance and Control5 2.1 Simulation Development and Integration
6 2.2 IAG&C System Design and Consultation
7 Final IAG&C System (Entry I) Delivered from Barrons
8 Final IAG&C (Entry II) System Delivered from Barrons
9 2.3 IAG&C System V&V (Entry I)
10 2.4 IAG&C System V&V (Entry II)
11 3.0 Software12 3.1 FMC S/W Requirements
13 3.2 IAG&C Integration in FMC
14 4.0 Avionics Lab15 4.1 ASIL S/W Requirements
16 4.2 IAG&C (Entry I) Integration in ASIL
17 4.2.1 IAG&C (Entry II) Integration in ASIL
18 4.3 ASIL Test Entry I
19 4.4 ASIL Test Entry II
20 5.0 Documentation and Final Report
5/169/19
Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar MayQtr 3, 2003 Qtr 1, 2004 Qtr 3, 2004 Qtr 1, 2005 Qtr 3, 2005 Qtr 1, 2006
More technically accurate than flight tests
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
Engineering, Operations & Technology | Phantom Works
Trajectory Reshaping ApproachNeed fast optimization approach - deliver new trajectory solutions in flight
Redefine complete trajectory in terms of a small number of parameters to be optimizedOnce solution is obtained: map parameters back to full trajectory historyTrajectory parameters:
Initial heading angleAltitude to start HAC turnAltitude to start Final Flare guidance lawDynamic pressure at touchdownCL, CD: models trim CL,CD
under failure condition
Optimization problem posed:Minimize lateral maneuvering
Keeps solution from unrealistic sharp turns
Groundtrack
yrwy
xrwy
o
HHAC
Drop
HAC Turn
HFF TDq
} d
Defines shape of last stage of dynamic pressure profile
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Guidance & Control Laws
L _ ruddervator
R _ ruddervator
L _ flaperon
R _ flaperon
speedbrake
bodyflap
Z cmdNLongitudinal
Guidance
Lateral Guidance
cmd Coordinated Flight
Controller
Receding Horizon Optimal (RHO)
Controller- - - - -
Control Allocator
X-37 Vehicle
cmd
cmd
PR
Modified Sequential Least Squares (MSLS)
Parameter ID
refqf
K
cmdcmd+
-
q
V, D, , q, H, , V , D
CommandedTrajectory States toGuidanceLaw
qK f
3-DOF Plant Model
3-DOF Plant Model
+
-qf
H
f K
cmdcmdf
+-
V, , L, DH
o HAC, H
ff TDH , q
Reshaping AlgorithmReshaping Algorithm
Longitudinal Backstepping Loops
Lateral Backstepping Loops
Ref. Cmds.
CL CD, CL, CD
Trajectory Cmd Generation
Measurement Feedback…
Lift, Drag
Series of backstepping/dynamic inversion feedback loops: maps to commanded trajectory histories(V, , X, H, etc.) that drive guidance loops
d
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X-37 Drop Mission Case StudyWorst case low energy (high drag) failure - SB locked @ 65 deg. & BF locked @ 20 deg.
Ablation effects (add more drag); headwind/crosswind; navigation errors; turbulence
Altitude Profile
Ground Track
• 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
• Adaptive system commands much steeper descent – increases kinetic energy at touchdown – allows for greater control authority to execute final flare