NASA/TM-97-206229

In-Flight Transport Performance

Optimization: An Experimental Flight

Research Program and an Operational

Scenario

Glenn Gilyard

Dryden Flight Research Center

Edwards, California

National Aeronautics and

Space Administration

Dryden Flight Research Center

Edwards, California 93523-0273

October 1997
NOTICE

Use of trade names or names of manufacturers in this document does not constitute an official

endorsement of such products or manufacturers, either expressed or implied, by the National

Aeronautics and Space Administration.

Available from:

NASA Center for AeroSpace Information

800 Elkridge Landing Road

Linthicum Heights, MD 21090-2934

Price Code: A16

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

Price Code: A16
IN-FLIGHT TRANSPORT PERFORMANCE OPTIMIZATION:

AN EXPERIMENTAL FLIGHT RESEARCH PROGRAM

AND AN OPERATIONAL SCENARIO*

Glenn Gilyard

NASA Dryden Flight Research Center

P.O. Box 273

Edwards, California 93523-0273

USA

ABSTRACT C D

0

CL

A flight research program exploring the practical

application of real-time performance optimization CL@minCD

based on aircraft measurements and calculation of CDU

incremental drag from forced-response maneuvers is

presented. The outboard ailerons of the L-1011 test bed EGI

aircraft were modified to provide for symmetric FMS

deflections to permit a recambering of the wing in that

localized area, which in turn modifies the entire wing g

load distribution. The National Aeronautics and Space GLA

Administration developed an onboard research GPS

engineering test station from which the flight H

experiments are conducted and all analyses, both

qualitative and quantitative, are performed in a real- i

time or near real-time manner. Initial flight test results INS

are presented that indicate real-time drag minimization

is attainable. An approach to an operational KI'K2

implementation of adaptive performance optimization L/D

on current and future commercial and military M

transports is discussed with the goal of keeping the

required modifications simple and the pilot interface MADC

minimal and user friendly. MAW

MLA

NASA

NOMENCLATURE

AFTI

APO

A

xfp

A

zfp

CD

CD M

*Patent pending.

Advanced Fighter Technology

Integration PCM

adaptive performance optimization

q

acceleration along the flightpath, g

(positive forward) RETS

S

acceleration normal to the flightpath, g

(positive up) t

coefficient of drag T

coefficient of drag caused by Mach TE

N1, N3

coefficient of parasite drag

coefficient of lift

CL at minimum CD

control display unit

embedded GPS/INS

flight management system

acceleration caused by gravity, ft/sec 2

gust load alleviation

global positioning system

altitude, ft

number of redundant control effectors

inertial navigation system

drag equation coefficients

lift-to-drag ratio

Mach number

micro airdata computer

Mission Adaptive Wing

maneuver load alleviation

National Aeronautics and Space

Administration

engine rotation speeds of the first and

third spools, rpm

pulse code modulation

dynamic pressure, lbf/ft 2

research engineering test station

aircraft reference area, f12

time, sec

thrust, Ibf

trailing edge
VME

W

6

a

S

a

opt

A

rl

versa module eurocard

aircraft gross weight, Ibm

angle of attack, rad

symmetric aileron position (positive =

trailing-edge down), deg

optimal (minimum drag) symmetric

aileron position, deg

change

inclination of engine thrust relative to

the fuselage, rad

angular frequency, rad/sec

INTRODUCTION

Application of variable-geometry wing camber control

to transport aircraft can reduce aircraft drag, a

significant factor for improving airline profitability. A

1-percent drag reduction reduces fuel flow 1 percent

which, for the U.S. fleet of wide-body transports,

results in savings of approximately $140 million each

year.* [1-3].

A significant amount of transport efficiency technology

was developed in the late 1970's and 1980's and has

continued into the 1990's. The Advanced Fighter

Technology Integration (AFTI)/F-111 Mission

Adaptive Wing (MAW) program developed and

demonstrated the potential of using variable-camber

control to optimize cruise and maneuver flight

conditions for fighter configurations [4, 5]. The

program did not develop an operationally

implementable algorithm for optimization of

aerodynamic efficiency (maximizing the lift-to-drag

ratio, L/D) but instead relied heavily on

predetermined camber control scheduling. Recently,

preliminary design work has been performed for

implementing variable camber into transport aircraft

[6-8]. The proposed variable-camber design did not

include development of an L/D optimization

methodology.

Numerous reports exist documenting trajectory

optimization algorithms and their benefits relative to

the economics of commercial transports [9-12]. In

fact, all large transports currently being produced have

an on-board flight management system (FMS) that

"optimizes" the aircraft trajectory to minimize cost as a

function of flight time and fuel price. However, the

common theme or basis of all these algorithms is that a

model of all the performance-related aspects of the

aircraft is required. The "optimal" trajectory, therefore,

is only as good as the on-board models. In addition to

the baseline model having less-than-perfect accuracy,

airframe and propulsion system degradation are

additional factors that affect model accuracy.

Many issues enter into performance optimization for

subsonic transport aircraft. Foremost, the potential for

optimization must exist, which implies redundant

control effector capability (for example, more than one

means of trimming out the forces and moments to

obtain a steady-state flight condition). Most transport

aircraft have significant capability in this area. Controls

or variables that can potentially play a role in

performance optimization for current and future

generation transport aircraft include elevators,

horizontal stabilizers, outboard ailerons, inboard

ailerons, flaps, rudders, center of gravity, thrust

modulation, and differential thrust.

NASA has a flight research program, adaptive

performance optimization (APO), that is currently

addressing the key technological challenge of in-flight

performance optimization for transport aircraft;

namely, identification of very low levels of incremental

drag. To provide an effective optimization algorithm,

identification of incremental drag levels of 1 percent or

less will be required.

Adaptive performance optimization is a new approach

for improving aircraft performance without requiring

extensive hardware modifications. This approach

exploits existing redundant control-effector capability

by automatically reconfiguring control-surface

deflections to achieve a minimum drag trim

condition [13-15]. Although this paper emphasizes

drag minimization in the longitudinal axis, the

methodology is equally and readily applicable to the

lateral-directional axes. Currently, no commercial

transport aircraft features an automated drag

minimization system. The development and

implementation of a system (using symmetric ailerons)

is used to provide a practical example and is within the

scope of current flight research activities at the NASA

Dryden Flight Research Center. For fly-by-wire

transports, the modification can be as simple as a new

FMS and control display unit (CDU) software load.

Transports with mechanical systems additionally

require a simple control hardware modification.

*Fuel cost of $0.70/gal.
Thispaperaddressesthepracticalapplicationof arealtimeperformanceoptimizationmethodologyusingonboardmeasurementsandcalculationof incremental

dragfrom forced-responsemaneuversat cruiseflight

conditions.Theexperimental testaircraftisanL-1011

(LockheedCorporation,Burbank,California)widebodyaircraft.Theexperimentalsystemis described,

including hardware and software features,test

maneuvers, andanalysistechniques.Preliminaryflight

testresultsarepresented, andapplicationtooperational

aircraftis discussed.Notethatuseof tradenamesor

namesof manufacturersin this documentdoesnot

constituteanofficialendorsement of suchproductsor

manufacturers,either expressedor implied,by the

NationalAeronauticsandSpaceAdministration.

BACKGROUND: TRANSPORT

PERFORMANCE OPTIMIZATION

At cruise flight conditions, two control effectors are

typically required for longitudinal flightpath control:

the throttle and the horizontal stabilator (assuming a

symmetric aircraft, with identical engines and a

coupled elevator/horizontal stabilizer). Thus, in order

to maintain a given flight condition, only one unique

combination of the two control effectors exists.

Inclusion of symmetric outboard aileron as a

longitudinal control effector adds redundancy to the set

of longitudinal control effectors. (The three control

effectors each produce pitching moment and

drag/thrust changes to varying degrees.) With this one

additional control effector, the set of three control

effectors is redundant in that there no longer exists one

unique set of control settings that will maintain a given

flight condition. Instead, an infinite number of

combinations of throttle, horizontal stabilator, and

symmetric aileron deflections exists that can maintain

the given flight condition. However, each of these

combinations is not equally "good" in the sense of

providing minimum aircraft drag; and over the range of

small perturbations, only one pronounced minima is

likely to exist that produces a minimum drag

configuration. Adaptive performance optimization

addresses this one unique combination of control

effectors.

Adaptive performance optimization empirically

determines the minimum drag configuration for the net

aircraft and not just the wing. In this case, APO

determines optimal settings for throttle, horizontal

stabilator, and symmetric aileron deflection (a unique

angle of attack is also determined implicitly). The APO

methodology can be used to handle as many redundant

control effectors as are available.

Most aircraft have significant capability in this area but

are not currently taking advantage of it. Performance

optimization from a condition that is already fine-tuned

(based on wind-tunnel and flight testing) places

increased demands on high-quality instrumentation to

sense small differences in an unsteady environment.

A wide range of controls or variables can potentially

play a role in performance optimization for current and

future generation aircraft. These controls or variables

include elevators, horizontal stabilizers, outboard and

inboard ailerons, outboard and inboard flaps, rudder,

center of gravity, thrust modulation, and differential

thrust (fig. 1).

Preliminary design work, including wind-tunnel testing

and some flight experiments, has been performed for

implementation of variable camber on a transport

aircraft. The benefits of full-span variable camber

include the following [8]:

• Improved aerodynamic efficiency

L/D)

• Increased Mach number capability

• Improved buffet boundary

• Increased operational flexibility

• Reduced structural weight

• Reduced fuel burn

(improved

• Increased aircraft development potential

Figure 2 shows that, even at the design point of a

state-of-the-art conventional wing, the variablecamber feature provides increased L/D ratios. This

research involved using the entire trailing edge

of the wing for variable-camber control with the

variable-camber deflections being a function of span

location. This system produced L/D increases of

between 3 and 9percent and a buffet boundary

increase of 12 percent. The proposed full-span

variable-camber design did not include development

of a real-time adaptive optimization methodology.

TEST BED AIRCRAFT DESCRIPTION

An L-1011 aircraft was selected as the test bed for the

APO flight experiment. This aircraft is representative of

the general class of wide-body transports capable of
aileron

Center of gravity

_-- Horizontal

stabilizer

Inboard flap

Inboard aileron

Thrust modulation

differential thrust

Figure 1. Potential redundant control effectors.

970717

M= O.eO i ]

:- 3 percent r

9 percent

Variable _amber _ \

! \ _ v-Buffet

............................................. i ............................................... 3.3 percel_t__ ._ ................................. T"i ............. _ I,oundary

i z-- Fixed wing variable camber

' :i =,,xedwing _/_ l

: _ _! . --_

, _ ,_ t-,xeo-wing _, I

,,' '-- cruise range _'1

' ! Variable-camber

,' ;_ i cruise range

Lift coefficient 970718

Figure 2. Benefits of variable camber for a transport configuration using a simple trailing-edge control surface

system [8].
long-rangecruiseflight.Aircraftavailabilityandcost

dictateditsselectionoverotherwide-bodytransports.

General Information "

The test bed aircraft selected is owned and operated by

Orbital Sciences Corporation (Dulles, Virginia) and

was previously modified to launch satellites using

various models of the Pegasus ® rocket (Orbital

Sciences Corporation, Dulles, Virginia). The

modifications consisted of stripping the main cabin of

seating and related passenger amenities, modifying the

aircraft to carry and launch a rocket from the belly of

the aircraft with support systems installed primarily in

the lower galleys, and installing a launch panel control

station in the forward cabin along with seating for

approximately 10 engineers or observers. These rocket

launch modifications do not affect the incremental drag

measurements upon which APO is based.

The test aircraft is an L-1011-100 model and is

powered by three RB-211-22B (Rolls Royce, Inc.,

Derby, England) high-bypass turbofan engines. The

empty weight (without the Pegasus ®) and maximum

gross weight of the modified aircraft are 280,000 and

467,0001bm, respectively. The empty weight of

the Pegasus®-modified aircraft is approximately

20,000Ibm lighter than the production L-1011-100

model. The aircraft has a cruise range of approximately

4000 miles at Mach 0.84 and a maximum operating

speed of Mach 0.90.

Adaptive Performance Optimization Test Bed

Modifications

Aircraft modifications necessary to support the APO

experiment consisted of the following:

• Adding a research engineering test station

(RETS), which is the central feature of the APO

modification

• Adding an actuator (one on each wing)to drive

the outboard ailerons symmetrically

• Adding a trailing-cone system to obtain true static

pressure

• Connecting into the basic aircraft system to

obtain engine, control surface, and other

measurements

• Adding an embedded global positioning system

(GPS) and inertial navigation system (INS)

• Adding a state-of-the-art airdata computer

• Adding a pulse code modulation (PCM) data

recording system

Figure 3 shows the APO system. The APO system does

not rely on any uplink or downlink other than receiving

normal GPS satellite signals.

Research Engineering Test Station--All aspects of the

APO experiments are conducted from the RETS. At the

top level, the RETS consists of four vertical racks that

contain a SPARC 20 (Sun Microsystems, Inc.,

Mountain View, California) work station and three

additional displays for presentation of time histories

and related analysis results. The RETS is staffed by a

flight test conductor and an analysis/systems engineer.

The RETS also contains a computer based on versa

module eurocard (VME) architecture to support realtime input and output requirements and related realtime calculations. The RETS was designed to be a

flexible research tool and has many capabilities, which

include the following:

• Generating excitation signals to drive the

outboard ailerons: steps, ramps, sine waves, and

raised-cosine waves

• Providing position control for the outboard

aileron actuators

• Performing data collection, calibration, and

storage on hard disk

• Performing real-time analysis

• Displaying data and analysis results

• Displaying variable or error signal to the cockpit

to aid pilot control during test maneuvers

• Providing automatic feedback control and

optimization of the outboard ailerons

• Monitoring system health

• Providing communications with the pilot station

Figure 4 shows the RETS console.

Symmetric Aileron Actuation--In order to achieve

longitudinal-axis drag reduction, redundant control

variables must be available. Although the wing has a

number of control surfaces (inboard and outboard

ailerons and flaps), symmetric control is not normally

available in cruise flight with the exception of outboard

ailerons for load control on a few transport aircraft

types or models. A system modification was required to

provide for symmetric deflections, but first a selection

of the control surface to be used was required. Either or
i

_ Cockpit AM

I Symmetric aileron actuators outboard

- Experiment control (r

- Data files

-

-

Real-time

Postmaneuver

analysis

analysis L

GPS/INS

Computer

(VME)

SPARC 20

I Aircraft trailingdataconeand

PCM

_I O.t...rv.r I

970719

Figure 3. APO/L-1011 research system architecture.

EC 97 44012-2

Figure 4. Research engineering test station.
boththeinboardandoutboardflapsmightappearmost

desirable.However,becausetheflapsweredesigned

solelyfor low-speed,high-lift operation,significant

Fowlermotion(translation)existspriortoandwithflap

rotation.In addition,the lowersurfacesof theflaps

normallydevelopsignificantgapsastheflapdeflection

increases,thusproducinga significantdragincrease.

Theinboardaileronhasa shortspanrelativeto chord

andthereforehassignificantedgeeffects,whichleaves

useof theoutboardaileronsformodification.

The L-1011-100aileron control systemis fully

mechanical.Althoughuseof aservocontroller(to sum

bothelectricalandmechanical inputs)at theoutboard

actuatorwouldbeideal,theservounitaswell asthe

analysisandtestingrequiredto flight-qualifytheunit

would have beenprohibitivelyexpensive.Normal

outboardaileronoperationis commandedfrom the

inboard aileron using pushrodsand cables.The

approachtakento providesymmetriccontrolof the

outboardaileronswasto modifytherodcomingfrom

the inboard aileron,which in turn positionsthe

outboardaileronactuator.Themodificationconsisted

of replacingthe rod with a low-bandwidth,linear,

electricactuatorwith endfittingsidenticalto therod

being replaced.This modificationprovidesfor an

adjustablerod length that permits independent

commandstobesummedforeachoutboardaileron.

Figure5 showsa diagramof the outboardaileron

controlsystemanda photographof themodifiedrods

with actuators.This modificationallows for both

normal(asymmetric)andsymmetriccommandsto be

sento theoutboardaileronsimultaneously.

Theapproachdescribedwastakentominimizeaircraft

changesandmaintaintheaircraftsafetycharacteristics.

In additiontothemechanical rateandpositionlimitsof

theinlineactuator,additionallimitsonrateandposition

canbeplacedinthepositioncontrollersoftware.

Trailing-Cone System--Precise, absolute drag measurements require the use of a trailing-cone system to

obtain accurate, absolute static-pressure measurements

for research purposes. The trailing-cone system

consists of 250 ft of tubing running from the main

cabin through a pressure fitting in the aft bulkhead, up

the conduit in the leading edge of the vertical fin, and

out the top of the vertical fin.

Figure 6 shows a diagram of the trailing-cone system.

The trailing cone is only for research purposes; an

operational aircraft will not need one. A selector valve

is used to switch between static pressure of the aircraft

and trailing-cone static pressure to compare results

between aircraft and research sensors.

Standard Aircraft Data--Because the APO research is

directed toward operational implementation in

transport aircraft, the basic aircraft instrumentation was

used to the maximum degree possible. Access to the

aircraft data was obtained through tee connectors with a

large impedance on the instrumentation output side of

the tee to preclude research instrumentation electronic

problems from affecting aircraft systems.

The following aircraft data were recorded:

• Airdata: total and static pressure and angle of

attack

• Engine parameters: engine pressure ratio, fuel

flow, and first and third spool speeds (NI and N3)

• Surface positions: inboard and outboard ailerons,

inboard and outboard flaps, horizontal stabilator,

and rudder

In addition, sideslip sensor and throttle position

transducers were installed, and fuel burn counters were

added to the instrumentation system.

Embedded GPSflNS System--An embedded GPSflNS

(EGI) system typical of current production aircraft was

added to the instrumentation data base to provide

highly accurate measurements of very small changes in

flightpath axis accelerations and velocities. These

measurements are critical to the determination of very

small changes (less than 1 percent) in incremental drag.

The EGI system data, along with airdata, are also used

to compute wind estimates and angle-of-attack and

sideslip estimates.

Airdata Computer--A state-of-the-art micro airdata

computer (MADC) was added to the instrumentation

data base to provide accurate measurements and

calculation of very small changes in Mach number, true

airspeed, and altitude. The unique construction of the

MADC provides for more accurate airdata calculations

than independent measures of total and static pressures.

Other Modifications--An independent PCM data pallet

was installed to collect and record on tape all of the

standard aircraft data that is required for the flight

experiment parameters previously discussed. This

PCM data stream is also sent to the RETS for use in

displays and algorithm analysis. In addition, a unit was

added to the cockpit to display one variable and an error
Outboard

aileron servo

/--- Cable

_'__tuatorlnserted In _

(a) Original outboard aileron control linkage.

Pushrod

Inboard aileron

970720

(b) Control rod and linear actuator assemblies.

Figure 5. Outboard aileron control system.

EC 97 44012-9

8
To pressure

sensor

Brake

pallet

m_ m Flexible 3/8 in.

inside-diameter tubing

Pulley

pallet

/ tto Static-pressure

// of vertical sensing tube

/ tail /

/

/

/

/

/

/

/

/

//_-- Enter main

t/ cabin

/

Figure 6. Static-pressure trailing-cone system.

970721

signal to aid the pilot in performing precise control.

The symmetric aileron actuator power switch was

added to the cockpit.

REAL-TIME TEST OPERATIONS

Forced excitation of redundant control effectors is

required to identify incremental drag effects. The

requirement for forced excitation must be tempered by

the additional requirement that neither handling nor

ride qualities are noticeably impacted, which in turn

dictates the range of excitation frequencies and

amplitudes. These trade studies were conducted using a

high fidelity simulation of the test aircraft.

The APO flight experiment modifications discussed

previously only allow for direct control of the outboard

ailerons; throttle, stabilator, and angle-of-attack

changes are controlled indirectly. When the pilot

applies power to the APO actuators, the test conductor

has control over the actual surface position of the

outboard ailerons. The experimental APO system has

the following capabilities:

An independent bias can be added to either or

both outboard ailerons.

Normal (asymmetric) aileron commands from the

pilot and autopilot can be removed from the

outboard aileron command, thus providing for

only symmetric outboard aileron deflections. (In

the situation where roll control is required.

inboard aileron deflections are increased so as to

account for the "loss" of asymmetric outboard

aileron control.)

Step, ramp, sine, or raised-cosine excitation

commands are available. The magnitude.

frequency, and maneuver duration is selectable as

required.

Maximum commandable position and rate sent to

the outboard aileron is selectable and controlled

in software.

Relay characteristics that control commands sent

to the actuator for position feedback control of

the actuator are selectable in software.

Real-Time Flight Experiment Operation at

Stabilized Cruise Conditions

The test conductor selects the excitation parameters

and variables described in the previous section. The

desired flight condition is stabilized by the pilot and/or

autopilot. When the test conductor determines flight

conditions have stabilized, the excitation function is

commanded. The APO algorithm (described in the next

section) requires the pilot and/or autopilot to control

Mach number and altitude as accurately as possible
throughuse of the throttles and stabilator. The

excitation causes small drag and pitching-moment

changes in the aircraft configuration. The net aircraft

drag changes are anticipated to be both positive and

negative over the range of the excitation.

As previously noted, APO determines the control

effector positions to yield a net aircraft minimum drag

condition. Although only symmetric ailerons are

excited explicitly, maintaining approximate flight

conditions during the maneuver requires throttle and

horizontal stabilator changes (by the pilot or autopilot),

thus providing information relative to their pitchingmoment and thrust or drag effects. Flight conditions are

not required to be maintained exactly because small

deviations can be compensated for in the analysis.

Data are collected throughout the maneuver, and upon

maneuver completion, a drag-minimization analysis is

performed. The outboard ailerons are then commanded

to that optimal position. Probably the most obvious

way to take advantage of the drag reduction is to

continue flying at the same desired flight conditions but

at reduced fuel flows. An alternate use of the reduced

drag is to increase the cruise speed at the same fuel flow

setting; other variations on reduced drag benefits are

also possible. The operation of APO at other than

stabilized cruise is possible and is the subject of followon research. Long-range cruise flight is where most of

the drag reduction (fuel saving) benefits will be

accrued.

Drag-Minimization Algorithm

To provide an effective optimization algorithm,

estimation of incremental drag to levels of 1 percent or

less will be required. Although absolute drag

measurements of this accuracy are only obtainable with

very detailed analysis and precise engine modeling,

incremental drag values in this range are more readily

achievable [16, 17].

Previously discussed APO feasibility studies [13, 14]

(using a first-generation jet transport) have practical

difficulties in an operational flight scenario because of

measurement bias and resolution characteristics. The

optimization approach presented in this paper is

directed at identifying unknown drag characteristics

(including the minimum-drag symmetric aileron

position) from a forced-response, smooth, lowfrequency maneuver and then setting the symmetric

aileron to the estimated minimum-drag position.

The analysis procedure follows the general

methodology used for standard postflight performance

analysis with simplifications for the determination of

incremental drag. The process is based on the

availability of accurate linear and angular

displacement, velocity, and acceleration measurements,

such as from an INS, along with accurate airdata

information. These data can be used to calculate winds

and then angle of attack. Transformations are then

performed to produce flightpath-axes accelerations.

Thrust, T, is estimated from a representative steadystate engine model as a function of measured variables.

The lift and drag equations are then used to calculate

the coefficient of lift, CL, and the coefficient of drag.

CD.

Lift = qSC L = WAzfp-T sin(ot-'q) (I)

Drag = qSC D = T cos(_-rl)-WA (2)

xfp

where ct is angle of attack and 1] is the inclination of the

engine thrust relative to the fuselage. Aircraft gross

weight, W, is calculated based on takeoff weight and

fuel flow. Thrust-related ram effects are assumed

aligned with the gross-thrust axis and are included in

the other terms.

The following is an expression for CD that is a function

of parasite drag, induced drag, Mach-induced drag, and

symmetric aileron drag.

CD = CDo+K 1

[CL-CL@minC D]2

(3)

2

+ CDM AM+K2(6a- 6a opt )

Equation (3) is then solved from forced-response

excitation data. Algorithm solutions can range from

continuous to batch operation (the variables K 1 and

C L can be selected from previous baseline

@minCr_

aircraft flight data). Estimates of the parasite drag

coefficient (C D ), curvature of the aileron drag

O

variation (K2), and the optimal symmetric aileron

position (6 ) are produced. The optimal settings of

opt

10
throttleandhorizontalstabilatorarenot determined

explicitlybutratheraredeterminedfromthefactthat

when one of the threeredundantcontrol-effector

positionsis fixed, no redundancyis left for the

remainingtwoeffectorsandthustheywill seektheir

uniquepositionbasedon the flight conditionbeing

constrained.Thealgorithmcanbeconsidereda slow,

limited-authoritytrimmer.

The formulationof equation(3) is not unique;the

importantconceptis that the primary effectsof

symmetricaileron-induceddragberepresentedin the

CD equation in a plausible manner. Care should be

taken not to over-parameterize the problem;

independence of the various estimates must be

maintained to provide meaningful results.

Simulation results confirm that the analysis procedure

is insensitive to a wide range of algorithm variables

such as a priori estimates of K 1 and CL

@minCD

measurement bias effects, measurement resolution

effects, and thrust model accuracy [15]. Other

performance-related calculations such as changes in

specific fuel consumption and range can be calculated.

PRELIMINARY FLIGHT RESULTS

A functional flight of the research-modified aircraft

was flown, and the research systems operation was

evaluated at Mach 0.84 and an altitude of 35,000 ft.

With the altitude-hold autopilot on, the pilot trimmed

the aircraft throttles before maneuver initiation

(throttles were not used during the excitation portion of

the maneuver). The maneuver consisted of a 5 °

amplitude raised-cosine ( 1.0-cos(c0t)) forced excitation

of the symmetric outboard ailerons with a 300-sec

duration.

Figure 7(a) shows altitude, Mach number, and

stabilizer response variables to the forced excitation.

Altitude is held within 10 ft over the maneuver

duration, and Mach number apparently increases

during the initial portion of trailing-edge-down

outboard aileron deflection and begins decreasing as

the deflection reaches its peak value. Mach numberhold through the throttles was not used during this

maneuver. Although in an operational scenario, Mach

number would be constrained by an autothrottle mode.

It is clear from the maneuver response characteristics

that neither handling qualities nor ride qualities are

affected.

Figure 7(b) shows the variation of AC D with _a" The

AC D parameter is estimated from equations (1), (2),

and (3) using flight data measurements. The smooth,

solid line is the "best fit" of the flight data using

estimates of the unknown parameters of equation (3).

Although the variation is "noisy," a minimum clearly

exists (=4°,trailing-edge-down, symmetric aileron

deflection) that indicates a more optimal flight

configuration than the baseline aircraft (0 ° symmetric

aileron deflection). From this one example, it is clear

that small incremental drag changes can be estimated

and that the aircraft can be reconfigured to reduce drag.

OPERATIONAL IMPLEMENTATION

Application of APO to fly-by-wire aircraft is straightforward and theoretically only requires software

additions that could be placed in the FMS. The pilot

would interface with the APO software through the

CDU. For aircraft with mechanical control systems,

application of APO would require the additional

modification of the installation of electrically

commanded actuators (or equivalent) somewhere

within the system controlling the particular control

surface of interest.

Redundancy is not required because the APO system is

not a safety-of-flight item. This aspect can be assured

by having APO in a discretionary mode with very

limited rate and position authority. In a situation where

the aircraft has an active control mode using the

outboard ailerons (for example, maneuver load

alleviation, MLA, or gust load alleviation, GLA), the

APO optimal position would be summed with the

active signals. In the GLA situation, APO provides a

new reference condition about which the GLA

commands operate. The MLA command is similar to

the APO command and obviously has priority; the APO

command needs to be "washed out" as the total

outboard aileron deflection exceeds predetermined

levels.

11
35.20 x 103

Altitude,

ft

35.15

35.10

35.05

35.00

........... _ ............ r ............ , ............ r ........... _ ............

, i

i

........... _ ............ r ...................................

, i

i i

b i

p 4 i

Mach

number

Horizontal

stabilizer,

deg

.87

.86

.85

.84

.83

1.0

.5

-.5

- 1.0

i i i ,

........... _ ............ r ............

............ t ............ r ........... _ ............ r ............

t i

i

i

i

....................... r _ ............

r i

b

........................ r ............ r ........................

b

•-_ ..... :_ _"__

Symmetric

outboard

aileron,

deg

6

1

........... i.............. %Lii_ L_..........................

............ :.............

............ :................... _' _ ....................

i I I I

2 3 4 5

Time, min

(a) Aircraft response to forced-excitation maneuver.

Figure 7. Preliminary APO flight test results.

I

6 7

970722

12
Hoavy line: arlalysis fit

AC D

I

i

....... r- ....... ._ .......

5.0 k 31 i .... 4.5 4.0 5 3 0 2.5 2.0 1.5 1.0

Symmetric aileron, deg

(b) Variation of incremental drag with symmetric aileron deflection.

Figure 7. Concluded.

'5• 0

970725

13
Operational Algorithm Operation

Figure 8 shows an approach to an operational

implementation of the APO algorithm. (A proposed

pilot interface with the APO system will be discussed

later.) After APO is engaged, storage arrays are

searched for previous APO results. If applicable results

are located, the control surfaces will be positioned

beforehand to this value based on the assumption that

the previous optimal position is, in all likelihood, better

than the baseline aircraft configuration. The forcedexcitation signal is then applied. A raised-cosine

excitation with a period of approximately 300 sec is

preferred because of its smooth characteristics and long

duration during which the autopilot maintains steady

flight conditions. (Autopilot modes are assumed to

exist for all practical operational implementations to

maintain constant flight conditions.)

Data are collected during the course of the maneuver.

When the maneuver is complete, the optimization

analysis is performed. These results are available

essentially instantaneously. The control surface is then

smoothly commanded to the newly determined optimal

position by using the first one-half of the raised-cosine

command shape. If it is determined that the excitation

signal range did not encompass the optimal position,

the algorithm is assumed not to have converged, and the

process is repeated with the range of the excitation

signal changed. (This issue should not exist when a set

of APO optimal conditions have been determined for a

particular aircraft.) In the situation where more than

one redundant controller is available, repetition of the

excitation for a different control surface may be

required. When the optimal APO conditions have been

determined, the results update the storage arrays.

Because aircraft-specific variations play a significant

role in the actual amount of performance improvement

accruable, using previous optimality results as initial

conditions can speed up optimality convergence for

subsequent flights.

When an optimal set of control positions have been

determined, the APO system goes into a standby mode

because continuing the excitation process will only

serve to introduce drag increases at the optimal

condition. A new excitation cycle is required when

aircraft or flight conditions have changed sufficiently

such that a new optimization cycle could provide a new

optimal result. Although the criteria for starting a new

APO cycle are somewhat aircraft-dependent, a

reasonable set of criteria could be the exceedence of

any one of the following: 30 min since the last APO

cycle, an altitude change of 2000 ft, or a Mach number

change of 0.02. Of course, the flight crew would always

have the option of initiating a new APO cycle.

Flight Crew Operation

Figure 9 shows one possible APO system interface

display from the flight crew's perspective.

The required software would be implemented

in an FMS revision. As a first-generation

implementation, the proposed interface has

some limited interactive features. The proposed operations relative to the panel illustrated are as

follows:

ON

ENTER

EXCITE

ON window lights; EXCITE and ENTER

remain dark

OLD Optimal Value control position is displayed if a valid set of interpolation points

are available; if not, display reads 0.0

ENTER window lights

Sends displayed value to the surface; light

stays on to indicate optimal value is on the

control surface

Optimal value is entered in the data table

Succeeding excitations and analyses place

a new value in the window and turn the

ENTER window light off

EXCITE window lights and stays on

during forced excitation

Commanding EXCITE initiates a new

excitation signal (must be dark/off to

initiate)

When an optimal value is determined, the

excitation function goes into a standby

mode

After a fixed period of time or upon

exceedence of predetermined flight

parameters (for example, AM, AH), the

excitation repeats automatically

Upon completion of forced excitation,

analysis is performed and result displayed

(for example, NEW -1.8)

Excitation will be referenced to previous

ENTER position

14
I

]OptJmJzatJon analysis }

I

J Position effector(,)I

Figure 8. APO algorithm flow chart.

ION/OFF I

APO PANEL

ENTER I IEXCITE

Optimal value

NEW -1.8

Figure 9. Crew interface display.

J

970724

15
Optimal

Value Window flashes until the optimal value is

entered (surface is then commanded to the

optimal position)

The described APO system keeps the flight crew

apprised of optimal positions as the positions become

available; the crew then has the option of accepting

those optimal positions. It is presumed that when

experience has been gained with the system described,

even this minimal interactive capability will not be

required. The elements of the display (described above)

presumably would be integrated into one or more CDU

display pages so that no hardware changes to either the

FMS or the flight station are required.

CONCLUDING REMARKS

The NASA Adaptive Performance Optimization (APO)

flight research program, which is directed at exploring

the practical application of real-time performance

optimization based on aircraft measurements, has been

described. The experiment has been implemented on an

L-1011 wide-body transport. The outboard ailerons of

the test bed aircraft were modified to provide for

symmetric deflections, and an onboard research

engineering test station was developed by NASA.

Incremental drag variations are calculated in response

to a forced excitation of the redundant control surface

being optimized. An example flight maneuver has been

presented that illustrates the real-time character of the

maneuver and its minimal effect on flying or ride

qualities.

An approach to an operational implementation of APO

on current and future commercial and military

transports is proposed with the goal of keeping the

required modifications minimal. Application of APO to

fly-by-wire aircraft theoretically requires only software

additions that could be placed in the flight management

system. Aircraft with mechanical control systems

would additionally require the installation of

electrically commanded actuators (or equivalent)

somewhere within the system controlling the particular

control effector of interest. In both cases, the pilot

would interface with the APO software through the

control display unit. Sensors and instrumentation

installed on current state-of-the-art aircraft appear

adequate for performing APO.

REFERENCES

[1] "Long Live the Leviathan," Flight International,

Sept. 15-21, 1993, pp. 30-31.

[2] "P&W Plans PW4000 Improvement Tests,"

Flight International, June 30-July 6, 1993, p. 11.

[3] Szodruch, J., "Viscous Drag Reduction On

Transport Aircraft," AIAA 91-0685, 1991.

[4] Advanced Fighter Technology Integration F-Ill

Mission Adaptive Wing, NASA CP-3055, 1990 (ITAR

restricted document).

[5] Phillips, Paul W. and Stephen B. Smith,

AFTI/F-111 Mission Adaptive Wing (MAW) Automatic

Flight Control System Modes Lift and Drag

Characteristics, AFFTC-TR-89-03, May 1989.

(Distribution limited to U.S. Government agencies

only (Test and Evaluation), Apr. 1989. Other requests

for this document shall be referred to the AFTI/F-111

(MAW) Program Office (WRDC/FIMF), WrightPaterson AFB, OH, 45433-6503.)

[6] Szodruch, J. and R. Hilbig, "Variable Wing

Camber For Transport Aircraft," Progress In Aerospace

Sciences, vol. 25, no. 3, 1988,pp. 297-328.

[7] Renken, J. H., "Mission-Adaptive Wing Camber

Control Systems for Transport Aircraft," AIAA 85-

5006, Oct. 1985.

[8] Renken, Jiirgen, Variable Wing Camber Control

Systems for the Future Airbus Program,

Messerschmitt-Brlkow-Blohm GmbH UT-104-88,

Feb. 1988 (in German; English summary).

[9] Sorensen, John A., S. A. Morello, and H.

Erzberger, "Application of Trajectory Optimization

Principles to Minimize Aircraft Operating Costs,"

IEEE TA3-9:00, 1979.

[10] Lee, Homer Q. and Heinz Erzberger, Algorithm

for Fixed-Range Optimal Trajectories, NASA

TP-1565, July 1980.

[11] Erzberger, Heinz, Automation of On-Board

Flightpath Management, NASA TM- 84212,

Dec. 1981.

16
[12] Visser, H. G., An Approach to On-Board

Optimization of Cruise at Constant Altitude, Delft

Technische University, The Netherlands, report no.

LR-581, 1989.

[13] Gilyard, Glenn B. and Martfn D. Espafia, On the

Use of Controls for Subsonic Transport Performance

Improvement: Overview and Future Directions, NASA

TM-4605, Aug. 1994.

[14] Espafia, Martfn and Glenn Gilyard, Direct

Adaptive Performance Optimization of Subsonic

Transports: A Periodic Perturbation Technique, NASA

TM-4676, Mar. 1995.

[15] Gilyard, Glenn, Development of a RealTime Transport Performance Optimization

Methodology, NASA TM-4730, Jan. 1996.

[16] Rhodes, J. A., K. Ravindra, and D. M. Freidman,

"CFD Drag Predictions for a Wide Body Transport

Fuselage With Flight Test Verification," AIAA 93-3418,

1993.

[17] Weisenseel, Charles W. and Chester Gong, C-17A

Cruise Configuration Performance Evaluation,

AFFTC-TR-93-23, Dec. 1993. (Distribution limited to

U.S. Government agencies and their contractors

(Critical Technology), Sept. 1993. Other requests for

this document shall be referred to ASC/YC, 2600

Paramount Place, Fairborn, Ohio 45324-6766.)

17
REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and

maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information,

including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington,

VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORTTYPE AND DATES COVERED

October 1997 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

In-Flight Transport Performance Optimization: An Experimental Flight

Research Program and an Operational Scenario.

6. AUTHOR(S)

Glenn Gilyard

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

NASA Dryden Flight Research Center

P.O. Box 273

Edwards, California 93523-0273

9.SPONSORING/MONITORING AGENCYNAME(S)ANDADDRESS(ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

522-15-34-00-39-00-210

8. PERFORMING ORGANIZATION

REPORT NUMBER

H-2192

10. SPONSORING/MONITORING

AGENCY REPORT NUMBER

NASA/TM-97-206229

11.SUPPLEMENTARY NOTES

Presented at the 16th Digital Avionics Systems Conference, Irvine, California October 26-30, 1997

12a. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified--Unlimited

Subject Category 02-01, 02-03, and 03-01

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

A flight research program exploring the practical application of real-time performance optimization based on

aircraft measurements and calculation of incremental drag from forced-response maneuvers is presented. The

outboard ailerons of the L-1011 test bed aircraft were modified to provide for symmetric deflections to permit

a recambering of the wing in that localized area, which in turn modifies the entire wing load distribution. The

National Aeronautics and Space Administration developed an onboard research engineering test station from

which the flight experiments are conducted and all analyses, both qualitative and quantitative, are performed in

a real-time or near real-time manner. Initial flight test results are presented that indicate real-time drag

minimization is attainable. An approach to an operational implementation of adaptive performance

optimization on current and future commercial and military transports is discussed with the goal of keeping the

required modifications simple and the pilot interface minimal and user friendly.

14. SUBJECTTERMS

Aircraft Performance, Drag Reduction, Fuel Consumption, Wing Camber, Flight

Optimization, and Optimization

17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION

OF REPORT OFTHIS PAGE OF ABSTRACT

Unclassified Unclassified Unclassified

NSN 7540-01-280-5500 Available from the NASA Center for AeroSpace Information, 800 Elkridge Landing Road,

Linthicum Heights, MD 21090; (30 I)621-0390

15. NUMBER OF PAGES

22

i16. PRICE CODE

A03

20.LIMITATIONOFABSTRACT

Unlimited

Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. Z39-18

298-102