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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
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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 task-
tailored control systems for shipboard operations
Technical Barriers Tailwinds from astern Port side winds
Starboard side winds
• Accurate models require the integration of the time- Local flow acceleration Poor field-of-view Main rotor vortex inges
varying ship airwake and the flight dynamics of the High vibrations High vibrations Uncommanded right ya
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 time-
accurate 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 1 8 5 5
• Based on GENHEL
• Updated : Higher order Peter-He inflow model, Gust penetration model
Maneuver controller model
Click Simplified MATLAB Based Simulation for Control Design
First!!
Load Initial Value
MAIN
ROTOR
Advanced
DESIGNED Ship Wake & SHIP WAKE &
Maneuver Main Rotor
CONTROLLER Gust Model GUST
Controller Module
FUSELAGE
Fuselage
Module EOM OUTPUT
PFCS
SENSOR SAS
TAIL Save
Equation of Motion
ROTOR Data
Mechanical Module
Sensor SAS Flight Control
Module Module System Module Tail Rotor
Module
STABILATOR
EMPENNAGE
Stabilator
Module Empennage
Module
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Time-Accurate Ship Airwake 1 8 5 5
• 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 1 8 5 5
• 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 1 8 5 5
Time-Accurate Ship Wake Account for Local Velocities
at Blade Elements, Fuselage,
Gust Velocities from CFD Empennage, Tail Rotor
Linear look-up
algorithm
3-D uniform grid
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Maneuver Controller 1 8 5 5
Maneuver Controller
yd UH-60 Flight y
Command Desired Output u
+- Compensator Dynamic
Model
Model
yd
Command y Stick input
K
d
Desired Target Model dt
Online Compensator
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PID Type Maneuver Controller 1 8 5 5
Nonlinear Dynamic model Longitudinal control
D d
ulat K lat xlat K lat xlat K lat xlat
I
dt
Linearized 29 state model Lateral control
d
ulong K long xlong K long xlong K long xlong
I D
dt
Heave axis control
Reduced 9 state model d
ucol K col xcol K col xcol K col
I D
xcol
dt
xlong u w q
Decoupled dynamic model xlat v p r
xcol [w]
Find the gains ulong long
for PID controller ulat lat ped
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Shipboard Departure 1 8 5 5
• 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 1 8 5 5
• Helicopter position w.r.t LHA coordinate system
80
60
40
20
250 Escape time is 46.5 sec Y(ft) 0
-20
200 -40
DI mesh -60
-80
150
Z(ft) -2000 -1500 -1000 -500 0
100 X(ft)
300
50
LHA ship 250
0 200
100 Z(ft) 150
0
0 -200
Y(ft) -400 100
-100 -600 X(ft) 50
-800
0
-2000 -1500 -1000 -500 0
X(ft)
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Simulation Results of Shipboard Departure 1 8 5 5
• 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
0
Roll
Phi
0 -2
Escape from DI mesh -4
-0.05
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
0.05 10
Theta
Pitch
0 0
-0.05 -10
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
0.05 5
Yaw
Psi
0 0
-0.05 -5
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
Time(sec) Time(sec)
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Simulation Results of Shipboard Departure 1 8 5 5
• Stick inputs(%)
Lateral cyclic input : Left 0%, Right 100%
Longitudinal cyclic input : Forward 0% , Aft 100% No wake
Steady wake
Collective input : Down 0%, Up 100% Time-varying wake
Pedal input : Left 0%, Right 100%
55
Escape from DI mesh 50
Lateral
Lateral
50
45 Hover
40 45
0 10 20 30 40 50 60 70 80 0 5 10 15 20 25 30 35 40
Longitudinal
Longitudinal
60 50
50
40 45
0 10 20 30 40 50 60 70 80 0 5 10 15 20 25 30 35 40
60 58
Collective
Collective
56
50
54
40
0 10 20 30 40 50 60 70 80 0 5 10 15 20 25 30 35 40
50 45
Pedal
Pedal
40
40
35
30
0 10 20 30 40 50 60 70 80 0 5 10 15 20 25 30 35 40
Time(sec) Time(sec)
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Shipboard Approach 1 8 5 5
• 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 1 8 5 5
• Helicopter position w.r.t. LHA coordinate system
0
-200
-400
-600
250
Entering time is 38.7 sec Y(ft)
-800
200 -1000
-1200
150
Z(ft) -1400
-500 0 500 1000 1500
100
X(ft)
50 300
250
0
100 200
0
0 -200 Z(ft) 150
-400
Y(ft) -100 -600
-800 X(ft) 100
50
0
-500 0 500 1000 1500
X(ft)
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Simulation Results of Shipboard Approach 1 8 5 5
• Helicopter angular rate and Attitude angle
No wake
Steady wake
Time-varying wake
- Angular rate(deg/sec) - Attitude angle(deg)
0.1
Enter the DI mesh -4
Roll
Phi
0
-6
-0.1 -8
0 10 20 30 40 50 60 0 10 20 30 40 50 60
0.1 10
Theta
Pitch
5
0
0
-0.1 -5
0 10 20 30 40 50 60 0 10 20 30 40 50 60
0.1 10
5
Yaw
Psi
0
0
-0.1 -5
0 10 20 30 40 50 60 0 10 20 30 40 50 60
Time(sec) Time(sec)
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Simulation Results of Shipboard Approach 1 8 5 5
• Stick inputs(%)
Later cyclic input : Left 0%, Right 100%
Longitudinal cyclic input : Forward 0% , Aft 100% No wake
Steady wake
Collective input : Down 0%, Up 100% Time-varying wake
Pedal input : Left 0%, Right 100%
50
50 Enter the DI mesh
Lateral
Lateral
40 45
30 40
0 10 20 30 40 50 60 38 40 42 44 46 48 50 52 54 56 58 60
65
Longitudinal
Longitudinal
70
60
60
55
0 10 20 30 40 50 60 38 40 42 44 46 48 50 52 54 56 58 60
Collective
Collective
60 60
55
40
50
0 10 20 30 40 50 60 38 40 42 44 46 48 50 52 54 56 58 60
60
60
Pedal
Pedal
50
40 40
0 10 20 30 40 50 60 38 40 42 44 46 48 50 52 54 56 58 60
Time(sec) Time(sec)
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Stochastic ship airwake model 1 8 5 5
• Correlated airwake is determined by Stochastic wake
passing through spectral filter with Time-varying wake
desired transfer function 50
Lateral
(ref.Clement, Labows et al.) 45
U0 1
40
White Correlated 38 40 42 44 46 48 50 52 54 56 58 60
2 w s
airwake 65
Longitudinal
Noise
Lu w
model
60
Transfer function
w : turbulence intensity 55
38 40 42 44 46 48 50 52 54 56 58 60
Lu : scale length of turbulence 60
Collective
U 0 : speed of the mean wind field 55
w : PSD temporal break frequency 50
38 40 42 44 46 48 50 52 54 56 58 60
• Modeling parameters were obtained
60
Pedal
50
from flight test data(temporal data)
• Need parameters that describe both 40
38 40 42 44 46 48 50 52 54 56 58 60
the temporal and the spatial Time(sec)
characteristics
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Conclusions 1 8 5 5
• 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 1 8 5 5
• Update the dynamic interface simulation model
Aerodynamic effects of moving ship deck currently in development (Peters-
He 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
Schedule and Milestones PENNSTATE
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Tasks 2001 2002 2003 2004 2005
• Update GenHel Simulation for
shipboard simulation Completed
• Develop simplified MATLAB Short Term
Sim for control design Long Term
• 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 task-
tailored control
• Lee PhD Degree
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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
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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 Actions Taken:
the Kickoff Meeting: • Interacting with U.S. Navy Advanced
• Need collaboration with U.S. Navy and Aerodynamics Group (Dave Findlay,
possibly DERA Colin Wilkinson, Susan Polsky)
• No formal interaction with DERA (now
QinetiQ?) at this time.