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