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Barron Associates, Inc.
Selected Current Research
SAE International Aerospace Control & Guidance Systems Committee
Proprietary
Niagara Falls, NYOctober 14, 2008
David G. Ward(434) 973-1215
IAG&C for Reusable Launch Vehicles
AFRL Programs / Flight PhasesAFRL Programs / Flight PhasesAFRL Programs / Flight PhasesAFRL Programs / Flight Phases
IAG&C for AscentIAG&C for AscentIAG&C for AscentIAG&C for AscentWorking with:
Program Objectives:• Adaptive ascent guidance• Recover both 1st & 2nd stages under engine and/or actuator failures
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
Prof. Ping Lu
IAG&C for ReIAG&C for ReIAG&C for ReIAG&C for Re----entryentryentryentryWorking with:
Program Objectives:• Adaptive re-entry guidance• Recover vehicle under actuator failures
Proprietary
engine and/or actuator failures
IAG&C for Rapid Mission PlanningIAG&C for Rapid Mission PlanningIAG&C for Rapid Mission PlanningIAG&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
Future Access to Space Technology Future Access to Space Technology Future Access to Space Technology Future Access to Space Technology
(FAST)(FAST)(FAST)(FAST)Working with:
Program Objectives:• Apply adaptive guidance technologies to FAST concept vehicle
Prof. Ping Lu
Prof. Craig Kluever
IAG&C for Reusable Launch Vehicles
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
IAG&C for AscentIAG&C for AscentIAG&C for AscentIAG&C for Ascent
Status:• High fidelity 6-DOF sim dev. (Northrop)(Northrop)(Northrop)(Northrop)
• Reconfig. controller developed (AFRL)(AFRL)(AFRL)(AFRL)
• Adaptive guidance matured (BAI)(BAI)(BAI)(BAI)
• Successfully recovers / reshapes trajectory to engine outs, other failures
• Final Review in November
Re-entry footprint
IAG&C for ReIAG&C for ReIAG&C for ReIAG&C for Re----entryentryentryentry
Status:• Reconfig. controller developed (BAI)(BAI)(BAI)(BAI)
• Re-entry trajectory command generation developed (BAI)(BAI)(BAI)(BAI)
• Successfully recovers / reshapes trajectory to lift & drag variations
• Boeing to test robustness in high fidelity dispersion studies
AFRL Programs / Flight PhasesAFRL Programs / Flight PhasesAFRL Programs / Flight PhasesAFRL Programs / Flight Phases
Proprietary
• Final Review in November fidelity dispersion studies• Final Review in December
IAG&C for Rapid Mission PlanningIAG&C for Rapid Mission PlanningIAG&C for Rapid Mission PlanningIAG&C for Rapid Mission Planning
Status:• Significant tool maturation• Prototype demonstrated• Lockheed to aid infinal demonstration
• Work to continue in follow-on Phase III effort
Java User
Interfaces
Java User
Interfaces
Matlab/Simulink
C/C++Database
Management
Future Access to Space Technology Future Access to Space Technology Future Access to Space Technology Future Access to Space Technology
(FAST)(FAST)(FAST)(FAST)Status:• Configuration continues to be developed (Northrop. Lockheed, Honeywell)(Northrop. Lockheed, Honeywell)(Northrop. Lockheed, Honeywell)(Northrop. Lockheed, Honeywell)
• Aerodynamic model development continues (Northrop, Honeywell, AFRL)(Northrop, Honeywell, AFRL)(Northrop, Honeywell, AFRL)(Northrop, Honeywell, AFRL)
• ICD near completion (Northrop, Honeywell, (Northrop, Honeywell, (Northrop, Honeywell, (Northrop, Honeywell,
BAI)BAI)BAI)BAI)
A Validation Tool for Diagnostic Systems
CCAESARAESAR--DiagnosticDiagnostic
Identification & Significance of Innovation
Diagnostic Systems to Play Safety-Critical
Roles� inform adaptive control laws
� inform condition-based maintenance
Novel V&V Methods Needed for Diagnostic
Systems
� large space of operational conditions
� traditional worst-case analysis does not capture
probabilistic nature of diagnostic systems
NASA Applications
Phase I Accomplishments: gPC Demo on Diagnostic System
Preliminary design of CAESAR extensions
Proprietary
ApproachCombined Probabilistic & Worst-Case Analysis
� identify conditions that are both severe and likely to occur
� test these conditions extensively
Incorporate AURA Probabilistic Modeling Tools� accurately characterize diagnostic system behavior
� fitting from relatively few experimental runs
Design general SW framework � facilitate design, analysis, V&V of diagnostic systems
� open-architecture MATLAB Implementation
NASA ApplicationsAnalyze & Validate Technologies for…
� Aviation Safety Program
� Integrated Resilient Aircraft Control Program
� AirSTAR research testbed
Non-NASA ApplicationsAnalyze, & Validate Technologies for…
� commercial, & GA aircraft safety
� military aircraft survivability & performance
� autonomus air vehicles
� autonomous ground and marine vehicles
ContactsAlec Bateman, [email protected]
Phone: (434) 973-1215Source: NASA LaRC
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 Expand operational envelope of rotorcraft from Expand operational envelope of rotorcraft from Expand operational envelope of rotorcraft from aviation capable shipsaviation capable shipsaviation capable shipsaviation capable ships
• Turbulent environments
• Ship motion
• Rotorcraft/Ship combinations
• Airwake effects
RealRealRealReal----time implementation & evaluationtime implementation & evaluationtime implementation & evaluationtime implementation & evaluation
Estimate disturbances Estimate disturbances Estimate disturbances Estimate disturbances andandandand reduce pilot workloadreduce pilot workloadreduce pilot workloadreduce pilot workloadTrim
Compensation
Pilot Attitude Pseudo-
Trim
Compensation
Pilot Attitude Pseudo-
Feed-forward Trim Compensation
Adaptive and Learning ControlAdaptive and Learning ControlAdaptive and Learning ControlAdaptive and Learning Control
Proprietary
Estimate disturbances Estimate disturbances Estimate disturbances Estimate disturbances andandandand reduce pilot workloadreduce pilot workloadreduce pilot workloadreduce pilot workloadIdeal
Response
Model PID
Comp.
Inverse
Dynamics
Airwake
Feedback
Compensation
Rotorcraft
Flight
Dynamics
Pilot Attitude
Command Sensor
Data
Adaptive
Algorithms
Pseudo-
controls ActuatorsIdeal
Response
Model PID
Comp.
Inverse
Dynamics
Airwake
Feedback
Compensation
Rotorcraft
Flight
Dynamics
Pilot Attitude
Command Sensor
Data
Adaptive
Algorithms
Pseudo-
controls Actuators
Stochastic Disturbance Rejection
10-1
100
101
102
10-6
10-4
10-2
100
102
Frequnecy (rad/sec)
Auto
sp
ectr
a f
or
roll
gust,
pg
Least Squares Fit
FFT of Simulation Data
AR Model
-600
-500
-400
-300
-200
-60
-40
-20
0-0.5
0
0.5
1
1.5
Xpos, ftZpos, ft
Appro
x.
Late
ral W
ind
Norm
aliz
ed
Stochastic Spectral Estimation
Time-varying deterministic approximation
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
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 BAI
path planning algorithms
Trajectory space formulation
dramatically reduces burden
Autonomous Collision Avoidance and
Separation Assurance for
Small UAVs in the NAS
Proprietary
• Demo on representative surrogate platform
On-line adaptive specs
• Quantify processing
& sensing requirements
• ID HW for Ph. II demo
Advanced V&V Technologies
AFRL’s FCSSI Program: AFRL’s FCSSI Program: AFRL’s FCSSI Program: AFRL’s FCSSI Program: CerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRs
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
TASS SBIR Phase IIITASS SBIR Phase IIITASS SBIR Phase IIITASS 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
BackgroundBackgroundBackgroundBackground
Runtime 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)
Proprietary
Challenge Problem Initiative (CPI)Challenge Problem Initiative (CPI)Challenge Problem Initiative (CPI)Challenge Problem Initiative (CPI)Working with:
Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements
(MCAR) (MCAR) (MCAR) (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
Program Objectives:• Apply FCSSI technologies to a particular challenge problem
• Barron Assoc. – focus on RTVV integration into chosen challenge problem
• Return to base/recover vehicle safely
Advanced V&V Technologies
AFRL’s FCSSI Program: AFRL’s FCSSI Program: AFRL’s FCSSI Program: AFRL’s FCSSI Program: CerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRsCerTA FCS, MCAR, CPI & TASS SBIRs
ACGSC Meeting 102 – Grand Island, NYOctober 15, 2008
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Problems Detected
in Modules 1 & 2
Backup 1
Module 1
Backup 2
Module 2
Safety Wrapper 1 Safety Wrapper 2
Backup 3
Module 3
Safety Wrapper 3Problems Detected
in Modules 1 & 2
Example Degraded ModeBackgroundBackgroundBackgroundBackground TASS SBIR Phase IIITASS SBIR Phase IIITASS SBIR Phase IIITASS 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
FLCSoutputselector
3x1
Includes
FDI
input
selector
C C D L
(cross channel data link)
Safety
Performance
Proprietary
Backup 3 Backup 3 begin real-time testing
VMC-OFPVMC-OFP
3x1
3x1
Includes
actuator health
signal used by
input selector,
FDI and FLCS
Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements Mixed Critical Architecture Requirements
(MCAR)(MCAR)(MCAR)(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)Challenge Problem Initiative (CPI)Challenge Problem Initiative (CPI)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?
Polynomial Chaos Uncertainty Tools for Flutter
Polynomial Chaos Fit to Polynomial Chaos Fit to Polynomial Chaos Fit to Polynomial Chaos Fit to
• 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
Polynomial Chaos Fit to Polynomial Chaos Fit to Polynomial Chaos Fit to Polynomial Chaos Fit to
Eigvenvalue in Aeroelastic ModelEigvenvalue in Aeroelastic ModelEigvenvalue in Aeroelastic ModelEigvenvalue in Aeroelastic Model
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 simulationAutomate simulationAutomate simulationAutomate simulation----updates from experimental dataupdates from experimental dataupdates from experimental dataupdates from experimental data• Assist analyst in knowing wherewherewherewhere to update simulation
and whatwhatwhatwhat the update should be
• Structure learning
• System Identification
• Incremental database updates
• Statistically justified and local updates Phase I ResultsPhase I ResultsPhase I ResultsPhase I Results• Data preprocessing (smoothing)
• Frequency domain parameter estimation
• Identify model structure for coupled, nonlinearcoupled, nonlinearcoupled, nonlinearcoupled, nonlineareffects
- Pitch Up with Sideslip
- Heave-Roll (XV-15 ground effect)
Proprietary
SimulationSimulation
Data TablesData Tables
1. automatically determine nonlinear
regression structure at a particular
condition
+−+
+++=
])40[(...
...
2
1
0
α
α
α
α
M
MMM
C
CCC
nonlinear terms
(e.g., splines)
5. automatically update simulation data
based upon analysis
Flight
Data
Experimental
Data4. convert to form
suitable for
simulation data
table
),0(
11
1
αα
ασµMM
M
N
C
±
=
zMachCiiM
=,...),(α
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 ProcessSimulation Update ProcessSimulation Update ProcessSimulation Update Process- Heave-Roll (XV-15 ground effect)
• Overcome correlated actuators
• Rigorous statisticalstatisticalstatisticalstatistical fusionfusionfusionfusion 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 Improved fit using Improved fit using Improved fit using
identified model structureidentified model structureidentified model structureidentified model structure
Unmanned Underwater Riverine Craft
Autonomous Operations in Riverine Environments
Riverine EnvironmentRiverine EnvironmentRiverine EnvironmentRiverine Environment
Tidal wave and river current interactions
Depth variation/stratification
Confined navigation
Low visibility
Traffic
Obstacles
OperationsOperationsOperationsOperations
Specific mission not defined. Capabilities include:
Intelligence, Surveillance, and Reconnaissance (ISR) class of
operations
� Persistence
� Deploy/Retrieve
� Identification
Search, “leave behind”, etc.
Proprietary
Adaptive Control:
6-DOF results
Shape
Control
Flight
Control
Objective
Goal: Stable flight control with limited model knowledge during wing-shape morphing
Adaptive Control of Morphing Aircraft
CFQ
KFQ
KI/s BPL
APL
KPL
CPL-BFQ
AFQ
1/s
xPL θθc xFQ e1/s
δ
xPL=[α θ q]T
CFQ
KFQ
KI/s BPL
APL
KPL
CPL-BFQ
AFQ
1/s
xPL θθc xFQ e1/s
δ
xPL=[α θ q]T
-4
-2
0
2
4
6
Pit
ch
Rate
(d
eg
/s)
Commanded Response
Response (ττττ = ∞∞∞∞ sec.)
Response (ττττ = 1/3 sec.)
Response (ττττ = 3 sec.)
Response (ττττ = 30 sec.)
Morph initiated at 10 sec.
Proprietary
Result: Consistent stable doublet
response during wing morphing
AF SBIR Phase IIAF SBIR Phase IIAF SBIR Phase IIAF SBIR Phase II• With
� NextGen / VA Tech
• Bryan Cannon, COTR
Demonstration GoalDemonstration GoalDemonstration GoalDemonstration Goal• Real-time HIL demonstration of stable
morphing control using MFX-2 aircraft
High-fidelity modeling of
morphing aircraft with two
wing DOF:• Quasi-steady aero analysis• Unsteady perturbation terms
0 5 10 15 20 25-6
Time (s)
Response (ττττ = 30 sec.)
Automated Upset Recovery System
for Unmanned Air Vehicles
OutOutOutOut----ofofofof----Control Arrest System Control Arrest System Control Arrest System Control Arrest System
• robust approach for arresting large angular rates in
nonlinear flight regimes
Automated Recovery System
RL ModuleRL ModuleRL ModuleRL Module
Reference
InnerInnerInnerInner----Loop Loop Loop Loop ControlControlControlControl
Guidance and
RL ModuleRL ModuleRL ModuleRL Module
Unusual Attitude Recovery System
OOC Arrest System ActuatorCommands
Proprietary
nonlinear flight regimes
Unusual Attitude Recovery SystemUnusual Attitude Recovery SystemUnusual Attitude Recovery SystemUnusual Attitude Recovery System
• modify commands/gains to inner-loop control to recover
from early-onset upsets and unusual attitude situations
Reference Guidance and Control Law
Develop upset recovery methodology
Demonstrate approach in simulations
Conduct HWIL/flight test demonstration
Develop tools to automate recovery capability
AAAA BBBB
Phase II objectives:Phase II objectives:Phase II objectives:Phase II objectives:
NASA SBIR/STTR TechnologiesActive Flow Control with Adaptive Design
Techniques for Improved Aircraft SafetyPI: Jason Burkholder / Barron Associates, Inc. – Charlottesville, VA
Significance of OpportunitySignificance of OpportunitySignificance of OpportunitySignificance 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 ResultsPhase I ResultsPhase I ResultsPhase I Results
Proposal Proposal Proposal Proposal T2.02T2.02T2.02T2.02----9831983198319831
Phase II Actuator DesignsPhase II Actuator Designs
Phase I ResultsPhase I ResultsPhase I ResultsPhase 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 TasksPhase II Work TasksPhase II Work TasksPhase 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
ApplicationsApplications•• AirSTAR Testbed for AvSP/SAAPAirSTAR Testbed for AvSP/SAAP
�� Complex damageComplex damage--adaptive FDI & control 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 Commercial and military aircraft –– especially tailless especially tailless
“stealth” aircraft“stealth” aircraft
ContactsContactsburkholderburkholder@[email protected]
(434) 973(434) 973--12151215
Phase II Wind Tunnel Model DesignPhase II Wind Tunnel Model Design
NASA SBIR/STTR TechnologiesReal-Time Adaptive Algorithms for Flight
Control Diagnostics and PrognosticsPI: Jason Burkholder / Barron Associates, Inc. – Charlottesville, VA
Significance of OpportunitySignificance of OpportunitySignificance of OpportunitySignificance of Opportunity• Addresses IVHM challenge: “Adaptive diagnostic and
prognostic algorithms (adapts as systems and
components age, are repaired, or replaced)”
• Research important theoretical issues in adaptive
observers and adaptive Kalman filters
• Research important practical implementation issues to
develop user-friendly tools
Phase I ResultsPhase I ResultsPhase I ResultsPhase I Results• Implemented and successfully demonstrated new
Proposal Proposal Proposal Proposal A1.07A1.07A1.07A1.07----9512951295129512
• Implemented and successfully demonstrated new
adaptive parameter estimation algorithms
• Initiated research effort into theoretical advances required
for adaptive model-based diagnostic techniques suitable
for formal analysis
Phase II Work TasksPhase II Work TasksPhase II Work TasksPhase II Work Tasks• Develop fully functional ADAPT (Adaptive
Diagnostics and Prognostics Toolbox) including:
� New parameter estimation algorithms
� Novel, practical adaptive observer and adaptive Kalman
filter methods
• Use ADAPT to develop an adaptive health
monitoring system for a high-fidelity electro-
hydrostatic control surface actuator simulation
ApplicationsApplications•• AirSTAR Testbed for AvSP/SAAPAirSTAR Testbed for AvSP/SAAP
�� Complex damageComplex damage--adaptive FDI & control 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, landCommercial and military aircraft, land--based based
vehicles, and marine vehiclesvehicles, and marine vehicles
ContactsContactsburkholderburkholder@[email protected]
(434) 973(434) 973--12151215
ADAPT Block DiagramADAPT Block Diagram
ElectroElectro--hydrostatic actuatorhydrostatic actuatorExpected TRL at End of Contract: 6Expected TRL at End of Contract: 6
