PENNSTATE
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Project PS 5.2
Simulation and Control of Shipboard Launch and
Recovery Operations
PI: Asst. Prof. Joseph F. Horn
Tel: (814) 865 6434 Email: joehorn@psu.edu
Graduate Student: Dooyong Lee, PhD Candidate
2002 RCOE Program Review
April 3, 2003
PENNSTATE
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Background / Problem Statement
• The shipboard launch and recovery task is one of the
most challenging, training intensive, and dangerous of all
rotorcraft operations
• The helicopter / ship dynamic interface (DI) is difficult to
accurately model
• Industry and government could use better tools for
analyzing shipboard operations to reduce the flight test
time and cost to establish safe operating envelopes
• Workload requirements could be reduced using tasktailored control systems for shipboard operations
Technical Barriers
Starboard side winds
Tailwinds from astern Port side winds
Main rotor vortex inges
Uncommanded right ya
• Accurate models require the integration of the time- Local flow acceleration Poor field-of-view
High vibrations
varying ship airwake and the flight dynamics of the High vibrations
helicopter
• Currently pilot workload requirements and HQ
analysis must be assessed using expensive flight
tests and piloted simulation
• A practical fully autonomous or piloted assisted
landing AFCS has not yet been developed, need to
assess requirements and potential benefits
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Task Objectives:
• Develop advanced simulation model of the shipboard dynamic interface
• Validate the model using available test data
• Use the model to develop advanced flight control systems to address workload issues in the DI
Approaches:
• Develop a MATLAB/SIMULINK based simulation of the H-60 based on GenHel (will facilitate
model improvements and control law development)
• Develop a maneuver controller to simulate pilot control during launch and recovery operations
• Integrate simulation with ship airwake models, investigate relative effects of steady and timeaccurate CFD wakes, and stochastic wake models based on CFD and flight test data
• Validate model with available data
• Develop new concepts in AFCS design for shipboard operations
• Develop a real-time simulation facility of shipboard operations (using DURIP funds)
Expected Results:
• A simulation tool for analyzing handling qualities in the DI and predicting safe landing envelopes
• A methodology for designing a task-tailored AFCS for shipboard operations
• A conceptual design of an autonomous landing systems and assessment of the system
requirements for such a system (possible UAV applications)
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MATLAB/SIMULINK based DI Program
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• Based on GENHEL
• Updated : Higher order Peter-He inflow model, Gust penetration model
Maneuver controller model
Click
First!!
Simplified MATLAB Based Simulation for Control Design
Load Initial Value
MAIN
ROTOR
Advanced
DESIGNED
Maneuver
CONTROLLER
Controller
Ship Wake & SHIP WAKE &
Gust Model
GUST
Main Rotor
Module
FUSELAGE
Fuselage
Module
EOM
OUTPUT
Equation of Motion
Module
Save
Data
PFCS
SENSOR
Sensor
Module
SAS
SAS
Module
Mechanical
Flight Control
System Module
TAIL
ROTOR
Tail Rotor
Module
STABILATOR
EMPENNAGE
Stabilator
Module
Empennage
Module
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Time-Accurate Ship Airwake
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• Established CFD solutions of ship wake(Sezer-Uzol , Dr. Long)
Parallel flow solver PUMA2 is used to calculate the flow
Time-varying, inviscid CFD solutions of the airwake of an LHA class ship
3-D, internal and external, non-reacting, compressible, unsteady solutions of
problems for complex geometries
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Application of Time-Accurate Ship Airwake
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•
•
•
•
•
Time step of base dynamic model is 0.01 sec
Time varying solutions are stored at every 0.1sec(total 20 sec)
Start from the pseudo steady state solution
Airwake data is loaded at every 0.1 sec
Linear interpolation method is used for ( ~ 0.01 sec)
Data load
0.0
0.1
0.2
0.3
…
19.8
19.9
20.0
19.9
Reverse
Interpolation
…
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Gust Penetration
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Time-Accurate Ship Wake
Gust Velocities from CFD
Account for Local Velocities
at Blade Elements, Fuselage,
Empennage, Tail Rotor
Linear look-up
algorithm
3-D uniform grid
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Maneuver Controller
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Maneuver Controller
Command
yd
Desired Output
Model
+-
u
Compensator
UH-60 Flight
Dynamic
Model
y

yd
Command
Desired Target Model
y
K

d
dt
Online Compensator
Stick input
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PID Type Maneuver Controller
Nonlinear Dynamic model
Linearized 29 state model
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Longitudinal control
I
D d
ulat  K lat xlat  K lat
 xlat  K lat xlat
dt
Lateral control
d
I
D
ulong  K long xlong  K long

x

K
xlong
 long
long
dt
Heave axis control
Reduced 9 state model
I
D
ucol  K col xcol  K col
 xcol  K col
xlong  u w q  
Decoupled dynamic model
xlat  v
p r  
xcol  [w]
Find the gains
for PID controller
d
xcol
dt
ulong   long 
ulat   lat  ped 
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Shipboard Departure
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• Shipboard departure sequences
 Phase I : From the stationkeeping location accelerating to a
desired climb rate and a desired horizontal acceleration
 Phase II : Keeping a constant climb rate and horizontal
acceleration
 Phase III: Reducing the climb rate and horizontal
acceleration to zero, and ending in a steady level flight
Phase III
Phase II
Phase I
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Simulation Results of Shipboard Departure
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• Helicopter position w.r.t LHA coordinate system
80
60
40
20
250
Y(ft)
Escape time is 46.5 sec
0
-20
200
-40
DI mesh
-60
-80
150
Z(ft)
-2000
-1500
-1000
-500
0
-500
0
X(ft)
100
300
50
LHA ship
250
0
200
100
0
-200
0
Y(ft)
Z(ft) 150
-400
-100
-600
-800
X(ft)
100
50
0
-2000
-1500
-1000
X(ft)
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Simulation Results of Shipboard Departure
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• Helicopter angular rate and Attitude angle
 High oscillatory motion is cause by time-varying ship airwake
No wake
Steady wake
Time-varying wake
- Angular rate(deg/sec)
- Attitude angle(deg)
0.05
Phi
Roll
0
-2
0
Escape from DI mesh
-0.05
0
10
20
30
40
50
60
70
-4
80
Theta
Pitch
0
0
10
20
30
40
50
60
70
80
-10
30
40
50
60
70
80
0
10
20
30
40
50
60
70
80
0
10
20
30
40
50
60
70
80
5
Psi
Yaw
20
0
0.05
0
-0.05
10
10
0.05
-0.05
0
0
10
20
30
40
Time(sec)
50
60
70
80
0
-5
Time(sec)
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Simulation Results of Shipboard Departure
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• Stick inputs(%)
Lateral cyclic input : Left  0%, Right  100%
Longitudinal cyclic input : Forward  0% , Aft 100%
Collective input : Down  0%, Up  100%
Pedal input : Left  0%, Right  100%
No wake
Steady wake
Time-varying wake
10
20
30
40
50
60
70
80
60
50
40
60
0
10
20
30
40
50
60
70
80
50
40
0
10
20
30
40
50
60
70
Hover
0
5
10
15
20
25
30
35
40
0
5
10
15
20
25
30
35
40
0
5
10
15
20
25
30
35
40
0
5
10
15
20
25
30
35
40
50
45
58
56
54
80
45
50
40
30
Longitudinal
0
50
45
Collective
Longitudinal
Collective
Lateral
45
40
Pedal
Escape from DI mesh
50
Pedal
Lateral
55
0
10
20
30
40
Time(sec)
50
60
70
80
40
35
Time(sec)
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Shipboard Approach
• Shipboard approach sequences
 Phase I : From the steady level flight, accelerating to a desired
decent rate and a desired horizontal deceleration
 Phase II : Keeping a constant descent rate and horizontal
deceleration
 Phase III: Reducing the decent rate and horizontal
deceleration to zero, and ending in a station keeping
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Simulation Results of Shipboard Approach
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• Helicopter position w.r.t. LHA coordinate system
0
-200
-400
-600
250
Entering time is 38.7 sec
Y(ft)
200
-800
-1000
-1200
150
Z(ft)
-1400
-500
100
0
500
1000
1500
1000
1500
X(ft)
50
300
0
250
100
200
0
-200
0
Y(ft)
-400
-100
-600
-800
X(ft)
Z(ft) 150
100
50
0
-500
0
500
X(ft)
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Simulation Results of Shipboard Approach
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• Helicopter angular rate and Attitude angle
No wake
Steady wake
Time-varying wake
- Angular rate(deg/sec)
- Attitude angle(deg)
0.1
-4
Phi
Roll
Enter the DI mesh
0
-0.1
-6
0
10
20
30
40
50
0
0
10
20
30
40
50
60
10
20
30
40
50
60
0
10
20
30
40
50
60
0
10
20
30
40
50
60
5
0
-5
10
Psi
Yaw
0.1
0
-0.1
0
10
Theta
Pitch
0.1
-0.1
-8
60
0
10
20
30
Time(sec)
40
50
60
5
0
-5
Time(sec)
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Simulation Results of Shipboard Approach
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• Stick inputs(%)
Longitudinal
Collective
0
10
20
30
40
50
60
70
60
0
10
20
30
40
50
60
60
40
0
10
20
30
40
50
60
60
Pedal
Pedal
Lateral
40
30
40
0
10
20
30
Time(sec)
No wake
Steady wake
Time-varying wake
50
Enter the DI mesh
Longitudinal
50
Collective
Lateral
Later cyclic input : Left  0%, Right  100%
Longitudinal cyclic input : Forward  0% , Aft 100%
Collective input : Down  0%, Up  100%
Pedal input : Left  0%, Right  100%
40
50
60
45
40
38
65
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
52
54
56
58
60
60
55
38
60
55
50
38
60
50
40
38
Time(sec)
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Stochastic ship airwake model
Correlated
airwake
model
Transfer function
 w : turbulence intensity
Lu : scale length of turbulence
U 0 : speed of the mean wind field
 w : PSD temporal break frequency
• Modeling parameters were obtained
from flight test data(temporal data)
• Need parameters that describe both
the temporal and the spatial
characteristics
Lateral
45
40
38
Longitudinal
2 w
U0  1 


Lu  s   w 
50
Collective
White
Noise
Stochastic wake
Time-varying wake
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
52
54
56
58
60
40
42
44
46
48
50
Time(sec)
52
54
56
58
60
65
60
55
38
60
55
50
38
60
Pedal
• Correlated airwake is determined by
passing through spectral filter with
desired transfer function
(ref.Clement, Labows et al.)
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50
40
38
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Conclusions
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• Dynamic interface simulation model
MATLAB based simulation model for UH-60(based on GenHel)
Gust penetration model
- Integrated with time-varying, inviscid CFD solutions of the airwake for an LHA ship
using 3-D look-up algorithm
Maneuver controller
- Develop a PID controller to simulate pilot control for launch and recovery
operations
- Investigate pilot workload during launch and recovery, use to develop improved
control laws
Shipboard approach and departure operations
- The time-varying airwake effects on the helicopter appear to be significant for pilot
workload when operating in the helicopter/ship dynamic interface
Potential areas for improvement
-Data storage requirements for time varying are extensive, might make real-time
implementation difficult.
-A stochastic airwake implementation should be investigated.
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Future Work
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• Update the dynamic interface simulation model
 Aerodynamic effects of moving ship deck currently in development (PetersHe inflow model with moving ground effect)
 Model of Ship Deck Motion, use Navy SMP software
 Improve maneuver controller to handle a variety of shipboard operations
 Develop a stochastic time-varying wake model based on the statistical
properties of the temporal and spatial variations of the CFD airwake
• Still pursuing validation data. JSHIP flight test data may be most
promising, matches the current configuration that we are
simulating – LHA + UH-60A.
• Task-tailored control systems for shipboard operations
 Optimized stability augmentation
 TRC / position hold over flight deck
 Autonomous landing
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Schedule and Milestones
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Tasks
• Update GenHel Simulation for
shipboard simulation
• Develop simplified MATLAB
Sim for control design
• Interface GenHel with ship air
wake solutions and ship motion
• Develop maneuver controller
• Validation of DI simulation
• Investigate relative fidelity of
time-accurate and stochastic
wakes
• Develop low-fidelity real-time
simulation capability at PSU
• Piloted simulation of DI
simulation (cooperative effort
with industry) and analyze HQ
requirements
• Task tailored control design
• Piloted simulation of tasktailored control
• Lee PhD Degree
2001
2002
2003
2004
2005
Completed
Short Term
Long Term
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2002 Accomplishments
• Improved Dynamic Interface Simulation
Integration of time varying CFD solutions of LHA airwake
Integration with simple stochastic time-varying gust field
Peters-He inflow model, currently developing with moving ground effect
• Developed Maneuver Controller to simulate pilot control inputs during launch and
recovery operations
• Analysis of effects of time varying wake on flight dynamics
• Developing real-time simulation facility for piloted simulation and visualization tool
• Presented results at AHS Flight Controls Specialists’ Meeting
Planned Accomplishments for 2003
• Will present newest results at 2003 AHS Forum and AIAA Atmospheric Flight Mechanics
Conference, submit AHS Forum paper as journal article
• Continue to update and improve model
• Developing advanced stochastic time-varying airwake model with temporal and spatial
variations in gust field, based on statistical properties of CFD airwake solutions.
• Start development of task-tailored control laws / autonomous landing systems
• Continue development of real-time simulation
PENNSTATE
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Technology Transfer Activities:
• Collaboration with Lyle Long, used latest LHA airwake solutions
• Horn and Long briefed U.S. Navy Advanced Aerodynamics Group at Pax River.
Continue to interact with this group.
• Presented work at AHS Flight Controls Technical Specialists’ Meeting
• Paper to be presented at 2003 AHS Forum / AIAA AFM Conference.
Leveraging or Attracting Other Resources or Programs:
• DURIP equipment grant supporting helicopter simulator project, being used for this project
• Currently pursuing data from JSHIP program to help validate model.
Recommendations at
the Kickoff Meeting:
• Need collaboration with U.S. Navy and
possibly DERA
Actions Taken:
• Interacting with U.S. Navy Advanced
Aerodynamics Group (Dave Findlay,
Colin Wilkinson, Susan Polsky)
• No formal interaction with DERA (now
QinetiQ?) at this time.