Post on 04-Jan-2016
Proprietary
Barron Associates, Inc.Selected Current Research
SAE International Aerospace Control & Guidance Systems Committee
Niagara Falls, NYOctober 14, 2008
David G. Ward(434) 973-1215
ward@barron-associates.com
Proprietary
IAG&C for Reusable Launch Vehicles
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
IAG&C for AscentWorking with:
Program Objectives:• Adaptive ascent guidance• Recover both 1st & 2nd stages
under engine and/or actuator failures
Prof. Ping Lu
IAG&C for Re-entryWorking with:
Program Objectives:• Adaptive re-entry
guidance• Recover vehicle under
actuator failures
IAG&C for Rapid Mission PlanningWorking with:
Program Objectives:• Develop Mission Planning tool
for RLVs• Rapid mission planning
capability• Launch ready within 2 hours,
24/7
Prof. Ping LuProf. Craig Kluever
Future Access to Space Technology (FAST)Working with:
Program Objectives:• Apply adaptive guidance
technologies to FAST concept vehicle
IAG&C for AscentStatus:• High fidelity 6-DOF sim dev.
(Northrop)
• Reconfig. controller developed (AFRL)
• Adaptive guidance matured (BAI)
• Successfully recovers / reshapes trajectory to engine outs, other failures
• Final Review in November
IAG&C for Re-entry
Status:• Reconfig. controller developed
(BAI)
• Re-entry trajectory command generation developed (BAI)
• Successfully recovers / reshapes trajectory to lift & drag variations
• Boeing to test robustness in high fidelity dispersion studies
• Final Review in DecemberIAG&C for Rapid Mission PlanningStatus:• Significant tool maturation• Prototype demonstrated• Lockheed to aid in
final demonstration• Work to continue in
follow-on Phase III effort
Java User Interfaces
Java User Interfaces
Matlab/Simulink
C/C++DatabaseManagement
Future Access to Space Technology (FAST)
Status:• Configuration continues to be
developed (Northrop. Lockheed, Honeywell)
• Aerodynamic model development continues (Northrop, Honeywell, AFRL)
• ICD near completion (Northrop, Honeywell, BAI)
AFRL Programs / Flight Phases
Proprietary
Innovative Rotorcraft Control for Shipboard Operations
Dr. Joseph F. Horn
PSU Vertical Lift Research Center of Excellence
NAVAIR SBIR Phase II TPOC: Mr. Dean CaricoExpand operational envelope of
rotorcraft from aviation capable ships• Turbulent environments• Ship motion• Rotorcraft/Ship combinations• Airwake effects
Real-time implementation & evaluation
Estimate disturbances and reduce pilot workload Ideal
ResponseModel PID
Comp.
InverseDynamics
AirwakeFeedback
Compensation
RotorcraftFlight
Dynamics
TrimCompensation
Pilot Attitude Command Sensor
Data
AdaptiveAlgorithms
Pseudo-controls ActuatorsIdeal
ResponseModel PID
Comp.
InverseDynamics
AirwakeFeedback
Compensation
RotorcraftFlight
Dynamics
TrimCompensation
Pilot Attitude Command Sensor
Data
AdaptiveAlgorithms
Pseudo-controls Actuators
Stochastic Disturbance
Rejection
Feed-forward Trim
Compensation
Adaptive and Learning Control
10-1
100
101
102
10-6
10-4
10-2
100
102
Frequnecy (rad/sec)
Aut
ospe
ctra
for
rol
l gus
t, p
g
Least Squares Fit
FFT of Simulation DataAR Model
-600-500
-400-300
-200
-60
-40
-20
0-0.5
0
0.5
1
1.5
Xpos, ftZpos, ft
App
rox.
Lat
eral
Win
dN
orm
aliz
ed
Stochastic Spectral
Estimation
Time-varying
deterministic
approximation
Proprietary
Damage Adaptation using Integrated Structural, Propulsion,
and Aerodynamic Control
Improved Aviation Safety:
• Compensate catastrophic damage(structure, propulsion, effectors, sensors)
Approach:
• On-line adaptation of subsystem design specs
• Managed through smart, V&V’able middleware
Phase II Objectives:
• Develop design-time tools to facilitate spec integration
• Develop run-time middleware to adapt/manage specs
• Demo on representative surrogate platform
On-line adaptive specs
Novel Collision Avoidance:
• Spenko, Dubowsky (MIT, 2006)
• Very low computational burden
• Strong safety guarantees
• Robust to large uncertainties
• Dynamic model-based
Phase I Objectives:
• Integrate CA with BAIpath planning algorithms
• Quantify processing& sensing requirements
• ID HW for Ph. II demo
Trajectory space formulation dramatically reduces burden
Autonomous Collision Avoidance and Separation Assurance for
Small UAVs in the NAS
Proprietary
Advanced V&V Technologies
AFRL’s FCSSI Program: CerTA FCS, MCAR, CPI & TASS SBIRs
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
TASS SBIR Phase IIIWorking with:
Program Objectives:• Mature RTVV system• Integrate RTVV into triplex system with RM• Certify RTVV system at design time• Mature Flight critical neural network
verification tool • Lockheed to test system in real-time
simulations
Mixed Critical Architecture Requirements (MCAR) Working with:
Program Objectives:• Develop requirements for mixed critical flight
systems• Focus on safety & security• Barron Assoc. – focus on RTVV integration into
mixed critical architectures
Challenge Problem Initiative (CPI)Working with:Program Objectives:• Apply FCSSI technologies to a particular
challenge problem• Barron Assoc. – focus on RTVV integration into
chosen challenge problem
BackgroundRuntime Verification & Validation (RTVV)• Monitor high risk S/W in flight
(algorithm/associated code that cannot be fully certified a priori due to advanced technologies)
• Shut down high risk S/W if anomalous behavior observed
• Revert to simplified (standard/classical) backup mode (can be certified at design time)
• Return to base/recover vehicle safely
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Nominal Operations
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Nominal Operations
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Problems Detectedin Modules 1 & 2
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Problems Detectedin Modules 1 & 2
Example Degraded ModeBackground TASS SBIR Phase IIIStatus:• RTVV approach greatly matured• Integration into high fidelity triplex system –
working w/Lockheed• Design time cert.
techniques for RTVVinvestigated
• Lockheed to soonbegin real-time testing
VMC-OFPVMC-OFP
VMC-OFPVMC-OFP
VMC-OFP
electronics
Actuators SBE
sensors
RM
FLCSoutput
selector
3x13x1
3x1
Includes actuator health
signal used by input selector, FDI and FLCS
FDI
inputselector
C C
D L
(cro
ss c
hann
el d
ata
link
)
Safety
Performance
Mixed Critical Architecture Requirements (MCAR)
Status:• Developed tool to generate/organize
requirements• Prototype list of requirements generated
S3 S2 M M2
S HCRTOS
Middleware Layer
Challenge Problem Initiative (CPI)Status:• Challenge problem selected: QF-16
(unmanned F-16 drones) autoland system certification
• Focus on actual incident: incomplete mode logic resulted in hard landing during flight test
• Developing MoMs, KPPs to measure cost savings of certifying autoland with new methods
• RTVV application: developing safety corridor & trajectory prediction – is A/C currently safe?
Proprietary
Polynomial Chaos Uncertainty Tools for Flutter
Polynomial Chaos Fit to Eigvenvalue in Aeroelastic
Model
• Develop methods for “non-intrusive” use of polynomial chaos
• Fitting polynomial chaos representations to empirical data
• Leverage domain knowledge to reduce complexity of fitting problem
• Address challenges of representing uncertainty in very high order models
Proprietary
Automated Updates of Tiltrotor Simulations using Experimental Data
NAVAIR SBIR Phase I TPOC: Mr. Sean Roark
aeronautics.arc.nasa.gov
halfdome.arc.nasa.gov
Automate simulation-updates from experimental data
• Assist analyst in knowing where to update simulation and what the update should be
• Structure learning• System Identification• Incremental database updates• Statistically justified and local updates
SimulationSimulation
Data TablesData Tables
1. automatically determine nonlinear
regression structure at a particular
condition
])40[(...
...
2
1
0
M
MMM
C
CCC
nonlinear terms(e.g., splines)
5. automatically update simulation databased upon analysis
Flight
Data
Experimental
Data4. convert to form
suitable for
simulation data
table
),0(11
1
MM
M
N
C
zMachCiiM
,...),(
3. compute confidence measures for the
parameters that will be used to update
the database
2. Perform regression on
data
Convert to aero table
format
Convert to aero table
format
Simulation Update Process
Phase I Results• Data preprocessing (smoothing)• Frequency domain parameter estimation• Identify model structure for coupled, nonlinear effects
- Pitch Up with Sideslip - Heave-Roll (XV-15 ground effect)
• Overcome correlated actuators• Rigorous statistical fusion of parameter estimates
0 10 20 30 40 50 60 70 80 90 100-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
Time, sec
L
Truth
Estimated
Improved fit using identified model structure
Proprietary
Unmanned Underwater Riverine CraftAutonomous Operations in Riverine Environments
Riverine EnvironmentTidal wave and river current
interactionsDepth variation/stratificationConfined navigationLow visibilityTrafficObstacles
OperationsSpecific mission not defined. Capabilities include:Intelligence, Surveillance, and Reconnaissance (ISR) class
of operations Persistence Deploy/Retrieve Identification
Search, “leave behind”, etc.
Proprietary
Automated Upset Recovery System for Unmanned Air Vehicles
Out-of-Control Arrest System • robust approach for arresting large angular rates in
nonlinear flight regimes
Unusual Attitude Recovery System• modify commands/gains to inner-loop control to
recover from early-onset upsets and unusual attitude situations
Automated Recovery System
RL ModuleRL Module
Reference
Inner-Loop Control
Inner-Loop Control
Guidance and Control Law
Guidance and Control Law
RL ModuleRL Module
Unusual Attitude Recovery System
OOC Arrest System ActuatorCommands
Develop upset recovery methodology
Demonstrate approach in simulations
Conduct HWIL/flight test demonstration
Develop tools to automate recovery capability
A B
Phase II objectives:
NASA SBIR/STTR TechnologiesActive Flow Control with Adaptive Design Techniques for Improved Aircraft Safety
PI: Jason Burkholder / Barron Associates, Inc. – Charlottesville, VA
Significance of Opportunity• Potential for low-cost safety improvements for
commercial transport aircraft Innovative synthetic jet actuators
strategically-located on airfoil could delay stall and provide “back-up” control power
Adaptive control is required due to complex, nonlinear actuator dynamics
Phase I Results• Designed and implemented adaptive control
laws – verified performance analytically and in simulation
• Designed wind tunnel model, novel actuators, and comprehensive Phase II test plan
Phase II Work Tasks• Develop fully functional AIFAC tool (Adaptive Inverse
For Actuator Compensation)
• Fabricate wind tunnel models and synthetic jet actuators – optimize actuator layout
• Implement real-time adaptive control system and demonstrate in closed-loop wind tunnel tests
• Quantify safety improvements and develop V&V Plan to facilitate future flight tests
Proposal T2.02-9831
ApplicationsApplications• AirSTAR Testbed for AvSP/SAAPAirSTAR Testbed for AvSP/SAAP
Complex damage-adaptive FDI & control Complex damage-adaptive FDI & control Operation near edge of flight envelopeOperation near edge of flight envelope
• NASA Intelligent Flight Control System (IFCS)NASA Intelligent Flight Control System (IFCS)• Commercial and military aircraft – especially Commercial and military aircraft – especially
tailless “stealth” aircrafttailless “stealth” aircraft
ContactsContacts burkholderburkholder@barron-associates.com@barron-associates.com(434) 973-1215(434) 973-1215
Phase II Actuator DesignsPhase II Actuator Designs
Phase II Wind Tunnel Model DesignPhase II Wind Tunnel Model Design