05-A Efremov DGLR Manching 081112
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Transcript of 05-A Efremov DGLR Manching 081112
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Prof. A.V. Efremov, Ph. D,Dean of Aeronautical school
Manching, EADS, Germany, 11-13 November, 2008
MOSCOW AVIATION INSTITUTE
MOSCOW AVIATION INSTITUTE EXPERIENCE ON
PILOT-IN-THE LOOP INVESTIGATIONS
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Content
1. MAI fundamental investigation on pilotvehiclesystem
2. MAI applied results in manual control area
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MAI fundamental investigationson pilotvehicle system (PVS)
database of knowledge ;
Goals: 1. Development of reliable basis
technique;
models
for investigation of single loop,multiloop, multimodality ,systems (stationary and
unstationary).2. Use of the basis for solution of applied manual
control tasks:
flight control system design;
FQ prediction
display design;
PVS parameters
Specification
DisplayControlledelementdynamics
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Developed technique for experimental investigations:
(frequency, spectral, integral characteristics of pilot, closedloop,
openloop system )
Unified Fourier coefficient technique
Technique for preliminary definition of CooperHarper
scale metrics in groundbased investigation
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Experience in pilotvehicle systeminvestigations exposed the following problems:
limited potentialities of wellknown mathematical pilotmodels for description of experimental data received withreal input spectrums and aircraft dynamics
considerable influence of different factors and task variables
on ground based evaluation of pilotrating and on PVScharacteristics
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Examples
1. Pilots adaptation in low frequency range
2. Pilots ability to generate complicated actions in crossoverfrequency range
1,00,1 10 , sec-1-20
20
40
0
dB
W ,
LAHOS 1.4LAHOS 2.10
1,00,1 10 , sec-1-20
20
40
0
dB
W ,
=i
1.5 sec-1
=i 0.5 sec-1
( ) ni
ii
KS 22 +
=
1,00,1 10 , sec-1
-20
20
40
0
dB
W ,
= sec 0 = sec 0.3
sekdB
d
Wd
C
p
40lg
lg
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3. Disagreement between groundbased and inflightsimulation
PR
ground
PRflight
averaged results
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10
2-B
2-1
2-5
2-7
2-8
3-D
3-1
3-3
3-6
3-8
3-12
3-13
4-1
4-2
5-1
5-9
5-10
5-11
disagreement between the results in I andIII levels of pilot ratings,
decrease of pilot rating intervalPR = PRworst PRbest in ground-
based simulation,
decrease of sensitivity of flying qualitiesestimation in ground-based simulation toFQ change.
d [sm] 0.5 1.0 2.0
r [dB] 8.15 7.53 2.3
PR 8.5 8.0 3.5
e d
4. Influence of motivations (requirement to the accuracy on PR)
5. Influence of additional channel(s): singleloop taskPR = 2
in multiloop taskPR = 5
PRg
PRf
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Problems and tasks:
determination of optimal aircraft dynamics;
exposition of regularities in pilot evaluation of Flyingqualities;
understanding of complicated behavior and ways for its
simplification; definition of rules for taking into account the different
factors.
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Optimization of aircraft dynamics for each piloting task
Technique for definition of Wc opt Pilots limitations (PL)
),( PLtaskoptcW
task
Application of optimal aircraft dynamic
1. Development of criteria for prediction of flying qualities.
2. Agreement between groundbased and inflight investigations.
3. Flight control system design.
Solution of problems and tasks
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Regularities in FQ evaluation1. Agreement between CooperHarper pilot rating (PR) and WeberFechner
2. Pilot workload and pilot-vehicle system parameters correlated withPR.
Data base:1. Neal Smith2. Have PIO3. LAHOS
1
3
5
7
9
1 2 3 4 5
PR
d
PR=1+5.36 ln( d )
variability PR
),( prfPR
normalized resonance peak of closed loop system
optCW
r
rr
optCCWpWpp
max
p
B
pw
e d
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3.Relationship between CHPR and PIOR
PIOR = 0,5PR + 0,25
PR = 3,5 PIOR = 2
PR = 6,5 PIOR = 3,5
PR = 9,5 PIOR = 5,0
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),max( PRPRPR
4.Evaluation of FQ in multichannel task
PR
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Conclusion: Random valuePR has to be characterized by binomial law
PR
max PR = 3 5
Configuration
10
9
8
7
6
5
4
3
3D
4.1
5.1 3.3
5.11
3.13
2
1
5. Distribution of PRPilot actions variability pilot rating variability
Ex. No 1 PR = 6
Ex. No 2 PR = 9
PR random value
Peculiarities of random valuePR:
PR whole number
PR a number contained
in the limited set ofnumbers
p(PR) = C9PR1pPR1(1 p)10 PR
p =PR 1
9
PR = (PR 1) (10 PR)9
C9PR1 =
9 !
(PR 1) ! (10 PR) !
1cW
1cW
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EXPERIMENTAL TEST ON POSSIBILITY TO USE BINOMIAL LAW FOR
DESCRIPTION OF PILOT RATINGp(PR)
ConfigurationsNumber of experiments
PR
2.122
2.86
4.1 3.8 3.8 3.12 5.10 Total22 24 20 19 17 124
2.75 3.1 3.7 6.4 7.35
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
1 2 3 4 5 6 7 8 9 10
PR
Binomial law
Experiment
PR
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)()()(1)()()(
sWsaWsWsWsWsW
nmf
ad
p
nmvisp
ep +=
Measurements of a set of
characteristics
)();(W);( ,,ad
p, jk
e
pjkjk
vis
p jWjjW
Exposed regularities:
1. Pilot uses additional cues
2. He does it more actively when 1C11 WWwhere, WWWW Cf ==
Understanding of reasons of complicated pilot behavior
nmW
cW+
di
faW
visp
W
adp
W
1W
cW
-
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Mathematical modeling
a. Modified structural approach
complicated form ofFVIS
the different procedure for the choice of parameters: c, FVIS, FPF
New features:
dependence of neuromuscular system on PVS task variables
taking into account pilot remnant
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b. Modified optimal control model
recommendation for the choice of weighting coefficients
modified model of remnant spectral density
Predictor
Human operator model
Disturbance
L*
Display
Time
delay
Kalmanestimator
Vehicledynamics
V (t)u V (t)y
U (t)c
u(t)
x(t) y(t) = C (t) + D (t)x
Y (t)px(t) x(t - )
1
T s + 1N
u
New features: modified cost function
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Composite approach to pilot modeling basedon Neural network
Stages for development of Composite model:
development of pilot neural network models (NNM)
{ } { })()( jWjW ii cp development of composite model based on pilot NNM allowed
to predict PVS characteristics
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1. Selection of technique and definition of parameters for pilot training:
NNP /MATLAB, inverse distribution technique
Stages for development of neural networkpilot model
2. Definition of training set 2400 points3. Definition of model structure:
architecture type of model: Time Delay Neural Network (TDNN) type,
set of inputs for model: for linear Wcei(t), ci(t),yi(t),for nonlinear system e(t), c(t),y(t),
numbers of layers, numbers of neurons, types of neuron
actuation functions:
for linear controlled element dynamicsactuation function
is linear (F= 1),
for nonlinear controlled element dynamicsactuation function
is nonlinear.
G f i
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w1
w2
w3
w4
w5
w6 - b
e t e t ( -0.40)- ( -0.45)
e t e t ( -0.45)- ( -0.50)
y t y t*( - )- *( - - 0.10)y yy
e
y*
y t y t*( - ) - *( - -0.20)
y
-0.10
y
y t y t*( - ) - *( - -0.30)y-0.20 y
e t( -0.25)
c t( )
T sy +1
1
( , ) ( )i cw b f W =
General structure of pilot neural network model
-4
-2
0
2
4
0 5 10 15 20 25 30 35 40 45 50t im e c( )
y
Comparison of mathematical modeling with experiment
15
20
10
5
0
-50
0
-100
-150-200
-25010
-1
10-1
100
100
10+1
10+1
(1/c)
(1/c)
W
experiment
NNPM optimal model structural model
experiment model
Composite approach for prediction
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Composite approach for predictionof pilot dynamics response
1.Selection of the configuration Wck
(j) Wcm
(j) {Wci
(j)} close to Wc(j):
2.Calculation of composite pilot model WP corresponding to WC
3. Development of pilot neural network model
-50
-100
-150
-200
-250
0
50
10-1
100
10+1
(1/c)
20
40
0
-20
-4010
-110
010
+1
(1/c)
W
10075 ( )
24075 ( )
(experiment)
(experiment)
experiment
interpolation
composite model
[ ] [ ]=
+=
n
k
kckickckic AAJ
1
22)()(
180)()(
);()()(
)()()()(
);()()(
)()()()(
ikF
imFikF
imikikip
ikAimAikA
imikikip
III
III
AAAA
=
=
)()()(
)()()(
icixcixF
icixcixA
FFI
AAI
=
=
( )ie tInverseFourier
transform
NeuralNetwork
model
( )A
( ) ( )ic t( )iy t
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MAI investigations on appliedmanual control tasks
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1. Criteria the requirements to pilot workload and pilot-vehicle system characteristics
Potentialities: Prediction of FQ level
2. Criteria the requirements to FQ by calculation of PR
Potentialities: the possibility to define a value of PR for the selection of FQ
FIRST TYPE OF CRITERIACriteria for prediction of FQ and PIO tendency Criteria for prediction of FQ in longitudinal
in longitudinal angular motion path motion (refueling task)
Definition of and W:
Experiment Mathematical modeling (optimal or structural approach to PVS modeling
I. DEVELOPMENT OF CRITERIA FOR PREDICTIONOF FLYING QUALITIES (FQ) AND PIO TENDENCY
r
-2Pilot phase compensation
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ControlledObject
Proprioceptive Feedback
Neuromuscular SystemCentral
ProcessingTimeDelay
Visual Block
se 0
-
+
-
C en
e
S
PFF
NMFVISF ACF
Um
Criteria as a requirements to HQSF
Level 2
Level 1
109876543210
, rad/sec
0
1
2
3
4
5
6
HQSF
15 deg/sec
150 deg/sec
Modified levels of HQSF
Level 2
Level 1
109876543210
, rad/sec
0
1
2
3
4
5
6
HQSF
Original levels of HQSF
L
m
Kj
C
UHQSF
1)( =
SECOND TYPE OF CRITERIA
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1
3
5
7
9
11
-1.2 -1.1 -1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0Ln( e)
P R
PR=11*(1+Ln(e))
.2.1
II
I
SECOND TYPE OF CRITERIA
I group of configurations:
PR= f(e)
II group of configurations:
PR = f(pilot workload)
Criteria
PR = max (PR, PR)
Prediction of PR by mathematical modelingStructural pilot model Wp(j ) Optimal pilot model
2.3
2
2.7
3.5
1
1.5
2
2.5
3
3.5
4
4.5
1 1.5 2 2.5 3 3.5 4 4.5PR
PR
2_1
3d
4_1
5_1
)68.14.0ln1(11e
PR ++= ( )14(11.0PR += p)126.1052.0ln1(11
ePR ++= ( )0.952(11.0PR =
1
1.5
2
2.5
3
3.5
4
4.5
5
1 1.5 2 2.5 3 3.5 4 4.5 5
PR
PR
1b
1c
1d
2d
2c
2f
7c
Criteria for FQ prediction in pitch tracking taskExposed regularities
PR = max (PRa, PRb )
PRa = F (a); PRb = F (b)
DEVELOPMENT OF CRITERIA FOR PREDICTION
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From:
J.R.Wood
AIAA-83-2105
DEVELOPMENT OF CRITERIA FOR PREDICTIONOF FQ IN LATERAL CHANNEL
Problem: Disagreement of FQ requirements developed in ground and in-flight simulation
Reason: Lateral acceleration caused by rotation
:Suggestion [ ]visPRaccPRfPR ,=[ ]
visPRaccPRPR ,max=
)(ln
)(ln
ynvest
vis
fPR
fPR
=
=
CRITERIA FOR PREDICTION OF FQ IN DUAL CHANNEL
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CRITERIA FOR PREDICTION OF FQ IN DUALCHANNELCONTROL TASK
= PRPRPR ,max
PR, PR ratings from dualchannel system investigations
optPR
)(
)(ln36.51,
+=
)( ,opt
)( from pilot optimal control model corresponding to
dualchannel system
exp
PR
mod
PR1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10
ModelingExperiment
II. AGREEMENT BETWEEN GROUNDBASED AND INFLIGHT
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Reasons of disagreement
In the first level of PR) a noise of estimation process due to inaccurate simulation of the different factors of flight,
b) The wrong (absence) instructions about the Cooper-Harper metrics
In the third level of PR
inability to simulate the stress situation typical for 3 level
II. AGREEMENT BETWEEN GROUND BASED AND IN FLIGHTINVESTIGATIONS ON FLYING QUALITIES ESTIMATION
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10
2-B
2-1
2-5
2-7
2-8
3-D
3-1
3-3
3-6
3-8
3-12
3-13
4-1
4-2
5-1
5-9
5-10
5-110
1
2
3
4
5
6
7
8
9
no motion motion LAMARS MS-1 TL-39 In-f light
PR
NASA VMS
W L
Calspan
MAI
PR=PR-PRPR = PRworst PRbest
THE WAYS FOR ACHIEVEMENT OF AGREEMENT
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THE WAYS FOR ACHIEVEMENT OF AGREEMENT
Definition of Cooper-Harper scale metrics on base of developed technique for calibration,
Simultaneous estimation of PR in longitudinal and lateral channels,
Increase of 3D objects on simulated visual scene (for the landing task)
Workstation
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10PR
PR
..
2-1
2-5
2-7
3-D
3-6
3-8
3-13
4-1
4-2
5-1
5-9
5-10
Result : increase of PR interval from PR=2.5 up to PR=8
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10
PR
PR. .
2_1
2_5
2_7
3d
3_6
3_8
3_13
4_1
4_2
5_1
5_9
5_10
With full set of metrics
desd Wd
add dopt
ad
opt
ad
opt
des ddd
ddFromWFL =
35
Without metrics
1
3
5
7
9
1
PR
d, sm
PR=1+5.36 ln( d )
- variability PR
5ddes dad
THE AGREEMENT BETWEEN IN FLIGHT AND GROUND BASED
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INVESTIGATIONS FULFILLED ACCORDING THE DEVELOPED TECHNIQUE
2.5 m/s 78 m 150 mAdequate
1.5 m/s 1.5 m 75 mDesired
Touchdownvelocity
VTD
LateralerrorY
LongitudinalerrorX
0.5 1.8m/s
Less then 60% radius of basketAdequate
0.9 1.4m/s
Less then 40% radius of basketDesired
Contactvelocity
LateralerrorY
LongitudinalerrorX
1.5 mradAdequate
5.0 mradDesired
Angular error
Landing
Refueling
Aimtoaim tracking
III. Means for improvement of pilot actions and FCS system conjunction
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p p y j
Goal: To suppress exposition of flight control system limited potentialities
WAYS FOR SOLUTION OF PROBLEM:
MANIPULATOR WITH VARIABLE STIFFNESS
LOGIC OF SYNCHRONYZED PREFILTER TO SYNCHRONIZE PILOT ACTION AND FLIGHT CONTROL
WITH LIMITED POTENTIALITIES BY LINEARIZATION OF PILOTAIRCRAFT SYSTEM CHARACTERISTICS
SYNCHRONIZED PREFILTER
Kf 1/s
1.
2. Kfo
max
max&
&
law 1:
restoration of initial gain coefficient Kfo
law 2:quick changeof Kf
law 1:
restoration of initial gain coefficient Kfo
law 2:quick changeof Kf
Kf 1/s
1.
2. Kfo
max&max&
&
1)1(
++=
TapTP
XP
X
W1nonlinear standard prefilter
Additional forceregulation law
1 1/pKf
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Effect of manipulator with proposed regulation of force
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Effect of manipulator with proposed regulation of force
constPX =
variable force
After failure
Control surface deflection
(limiter output) Px=const
(limiter output) variable stiffness
Px=const
variable stiffness
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IV. Some aspects of direct lift control use
Direct lift control surfaces flapperrons, canards
Direct lift control allows to:
improve short period dynamics
conserve flying qualities in caseof FCS failure
to suppress the speed instability
INVESTIGATION OF DLC EFFECTIVENESS IN REFUELING
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Improvement of accuracy
Aircraft with DLC
Without DLC
Effectiveness of direct lift control in carrier landingDLC allowes to suppres speed instability in carrier landing
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DLC allowes to suppres speed instability in carrier landing(because =const)
Without DLCWith DLC
Results of experiments
0
2
4
6
8
10
Without DLC
With DLC
Touchdown
0
10
20
30
40
50
3.5
47
22 , X
PR
V Additional information on path angle
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V. Additional information on path angle
Integration of DLC and path angle indication gives an improvement ofperformances up to 20 30%
With Without