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NASA Aeronautics Research Institute
Real-Time Onboard Global Nonlinear Aerodynamic
Modeling from Flight Data
NASA Aeronautics Research Mission Directorate (ARMD) 2014 Seedling Technical Seminar
February 19–27, 2014
Jay Brandon Eugene Morelli
NASA Aeronautics Research Institute
Outline
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 2
• Background • Test Aircraft and Equipment • Flight Test Maneuvers • Aerodynamic Modeling • Example Results - Demo • Dissemination • Next Steps • Closing Remarks
NASA Aeronautics Research Institute
Research Goal
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 3
• Ultimate Goal: Self-Learning and Autonomously-Adapting Vehicles
• Potential for High Impact In Three Primary Areas: – Safety – Reliability – Design/Development Efficiency
Technology Enablers Required: Computer Processing Capabilities System Identification Advances
• Non-linear aerodynamic modeling • Real-time system identification
Flight Control Theory Advances • Adaptive flight control algorithms
Short-circuit the current process…
…with a new paradigm
NASA Aeronautics Research Institute
Phase I Progress
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 4
• Nonlinear Aerodynamic System Identification – No model structure specification
required – Large flight envelope with single model – Post-flight analysis
• Flight Test Techniques for Rich Data Content – Multi-axes inputs over large range of
flight conditions – Piloted adaptation of similar orthogonal
input techniques • Blending of Data from Different Sources
– Ship research data acquisition system – iPad internal sensors for inertial data
and GPS
0 50 100 150-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
Cm
Time, sec
FlightModel, R2 = 0.9649
-10 0 10 20 30 40-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
CN
orm
al
α, deg
FlightModel, R2 = 0.9963
-5 0 5 10 15 20 25 30 35-0.04
-0.02
0
Cmα, p
er d
eg
DF9C4
-5 0 5 10 15 20 25 30 35-0.03
-0.02
-0.01
0
Cmδe
, per
deg
-5 0 5 10 15 20 25 30 350
2
4x 10-3
Cmα-
dot, p
er d
eg/s
ec
-5 0 5 10 15 20 25 30 35-20
-10
0
Cmqh
at
α, deg
FuzzyLESQ
NASA Aeronautics Research Institute
Test Aircraft
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 5
• Large flight envelope, aerobatic capability • Well instrumented:
α /β on nose boom, dynamic pressure, engine rpm, fuel flow accelerations, angular rates, and controls real-time data in aft cockpit and telemetered to the ground
Aermacchi Impala MB-326M
NASA Aeronautics Research Institute
Flight Test Setup
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 6
• Standard Front Cockpit • Onboard Instrumentation • Real-time Analysis Computer
mounted in Aft Cockpit
NASA Aeronautics Research Institute
Flight Test Maneuvers
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 7
NASA Aeronautics Research Institute
Video of Typical Maneuver
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 8
NASA Aeronautics Research Institute
In-Flight Aerodynamic Modeling
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 9
FLIGHT TEST MANEUVER
DATA CONDITIONING
NONLINEAR AERODYNAMIC MODELING ALGORITHMS: FUZZY LOGIC
MULTIVARIATE ORTHOGONAL FUNCTIONS
MODEL VALIDATION DATA FROM OTHER MANEUVERS
MEASURED DATA
FINAL MODEL
Explanatory variables: Response variables: α, β, p, q, r, δe , δa , δr , M, RPM, … CX , CY , CZ , Cl , Cm , Cn
NASA Aeronautics Research Institute
Maneuver Example
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 10
-6 -5 -4 -3 -2 -1 0 1 2 3 46
8
10
12
14
16
18
20
22
24
β (deg)
α (
deg)
-15 -10 -5 0 5 10 15 20-8
-6
-4
-2
0
2
4
6
δa (deg)
δ r (de
g)
-20 -15 -10 -5 0 5 10 15-4
-3
-2
-1
0
1
2
3
p (deg/s)
r (d
eg/s
)
-6 -5 -4 -3 -2 -1 0 1 2 3 4-8
-6
-4
-2
0
2
4
6
β (deg)
δ r (de
g)
NASA Aeronautics Research Institute
Maneuver Guidance Display
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 11
NASA Aeronautics Research Institute
Modeling Display
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 12
NASA Aeronautics Research Institute
Real-Time Demo
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 13
NASA Aeronautics Research Institute
Dissemination of Research
• Publications – NASA TM-2012-217778 – Phase I Results
• Lectures / Presentations – SFTE Meeting September 2013 – NASA Dryden Controls & Dynamics Presentation
September 2013 – ICAST Presentation February 2014
• Upcoming Events – Invited Lecture SETP Symposium March 2014 – Invited Lecture ACGCS Meeting March 2014 – AIAA Paper June 2014
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 14
NASA Aeronautics Research Institute
Next Steps
• Improve Modeling & Prediction Capabilities – Thrust vs aero effects – Full fuzzy model generation inflight
• Automate Data Collection – Real-time monitoring of flight data and
autonomous selection of data suitable for modeling and prediction
• Flight Controls – Use updated models for updated control
algorithms – Real-time checking of model adequacy
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 15
NASA Aeronautics Research Institute
Closing Remarks
• Near Real-time Aero Modeling – Self-learning and monitoring vehicles – Rapid development – Robust flight control
• Demonstrated Successful Modeling Inflight – All axes, large envelope, nonlinear – Complete aero model ready before landing – Two methods giving similar results
• Great Project Model – Small closely-working team – Minimal administrative burdens
February 19–27, 2014
NASA Aeronautics Research Mission Directorate 2014 Seedling Technical Seminar 16