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PI: Asst. Prof. Joseph F. HornTel: (814) 865 6434 Email: joehorn@psu.edu

Graduate Student: Dooyong Lee, PhD Candidate

Project PS 5.2Simulation and Control of Shipboard Launch and

Recovery Operations

2002 RCOE Program Review

April 3, 2003

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• 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

Background / Problem Statement

Technical BarriersStarboard side windsLocal flow accelerationHigh vibrations

Port side windsMain rotor vortex ingestionUncommanded right yaw

Tailwinds from asternPoor field-of-viewHigh vibrations

• Accurate models require the integration of the time-varying ship airwake and the flight dynamics of the 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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• 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

Task Objectives:

Approaches:

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)

• 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)

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• Based on GENHEL

• Updated : Higher order Peter-He inflow model, Gust penetration model

Maneuver controller model

MATLAB/SIMULINK based DI Program

Simplified MATLAB Based Simulation for Control Design

T AILROT OR

T ai l RotorModule

ST ABILAT OR

Stabi latorModule

SHIP WAKE & GUST

Ship Wake &Gust Model

SENSOR

SensorModule

OUT PUT

SaveData

SAS

SASModule

PFCS

MechanicalFl ight Control

System Module

MAINROT OR

Main RotorModule

Cl ickFirst!!

Load Ini tial Value

FUSELAGE

FuselageModule EOM

Equation of MotionModule

EMPENNAGE

EmpennageModule

DESIGNEDCONT ROLLER

AdvancedManeuverControl ler

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• Established CFD solutions of ship wake(Sezer-Uzol , Dr. Long)Parallel flow solver PUMA2 is used to calculate the flowTime-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

Time-Accurate Ship Airwake

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Application of Time-Accurate Ship Airwake

• 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)

0.0 0.1 0.2 0.3 19.8 19.9 20.0…

19.9…

Data loadData load

InterpolationInterpolation

Reverse

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Time-Accurate Ship Wake Gust Velocities from CFD

Account for Local Velocities at Blade Elements,

Fuselage, Empennage, Tail Rotor

3-D uniform grid

Linear look-up algorithm

Gust Penetration

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Maneuver Controller

Desired Output

Model

UH-60 Flight

Dynamic

Model

+-dyCommand Compensator u

y

Maneuver Controller

Desired Target Model

K

dt

d

y Stick input

Online Compensator

dyCommand

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PID Type Maneuver Controller

longDlonglong

Ilonglonglonglong x

dt

dKxKxKu

latDlatlat

Ilatlatlatlat x

dt

dKxKxKu

Nonlinear Dynamic modelNonlinear Dynamic model

Find the gains

for PID controller

Find the gains

for PID controller

Linearized 29 state modelLinearized 29 state model

Reduced 9 state modelReduced 9 state model

Decoupled dynamic modelDecoupled dynamic model

Longitudinal control

Lateral control

Heave axis control

colDcolcol

Icolcolcolcol x

dt

dKxKxKu

][wx

rpvx

qwux

col

lat

long

pedlatlat

longlong

u

u

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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

Shipboard Departure

Phase III Phase II Phase I

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-800-600

-400-200

0

-100

0

100

0

50

100

150

200

250

-2000 -1500 -1000 -500 0

-80

-60

-40

-20

0

20

40

60

80

-2000 -1500 -1000 -500 00

50

100

150

200

250

300

• Helicopter position w.r.t LHA coordinate system

Simulation Results of Shipboard Departure

DI mesh

LHA ship

Escape time is 46.5 sec

X(ft)Y(ft)

Z(ft)X(ft)

X(ft)

Y(ft)

Z(ft)

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0 10 20 30 40 50 60 70 80-0.05

0

0.05

0 10 20 30 40 50 60 70 80-0.05

0

0.05

0 10 20 30 40 50 60 70 80-0.05

0

0.05

0 10 20 30 40 50 60 70 80

-4

-2

0

0 10 20 30 40 50 60 70 80-10

0

10

0 10 20 30 40 50 60 70 80-5

0

5

• Helicopter angular rate and Attitude angle High oscillatory motion is cause by time-varying ship airwake

Simulation Results of Shipboard Departure

- Angular rate(deg/sec) - Attitude angle(deg)

Escape from DI mesh

Ro

llP

itc

hY

aw

No wakeSteady wakeTime-varying wake

Time(sec) Time(sec)

Ph

iT

he

taP

si

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0 10 20 30 40 50 60 70 8040

45

50

55

0 10 20 30 40 50 60 70 8040

50

60

0 10 20 30 40 50 60 70 8040

50

60

0 10 20 30 40 50 60 70 8030

40

50

0 5 10 15 20 25 30 35 4045

50

0 5 10 15 20 25 30 35 4045

50

0 5 10 15 20 25 30 35 40

54

56

58

0 5 10 15 20 25 30 35 40

35

40

45

• 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%

Simulation Results of Shipboard Departure

Hover

No wakeSteady wakeTime-varying wake

Lat

eral

Lo

ng

itu

din

alC

olle

ctiv

eP

edal

Time(sec) Time(sec)

Lat

eral

Lo

ng

itu

din

alC

olle

ctiv

eP

edal

Escape from DI mesh

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• 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

Shipboard Approach

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-800-600

-400-200

0

-100

0

100

0

50

100

150

200

250

-500 0 500 1000 1500

-1400

-1200

-1000

-800

-600

-400

-200

0

-500 0 500 1000 15000

50

100

150

200

250

300

• Helicopter position w.r.t. LHA coordinate system

Simulation Results of Shipboard Approach

X(ft)Y(ft)

Z(ft)

X(ft)

X(ft)

Y(ft)

Z(ft)

Entering time is 38.7 sec

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0 10 20 30 40 50 60-0.1

0

0.1

0 10 20 30 40 50 60-0.1

0

0.1

0 10 20 30 40 50 60-0.1

0

0.1

0 10 20 30 40 50 60-8

-6

-4

0 10 20 30 40 50 60-5

0

5

10

0 10 20 30 40 50 60-5

0

5

10

• Helicopter angular rate and Attitude angle

Simulation Results of Shipboard Approach

- Angular rate(deg/sec) - Attitude angle(deg)

Enter the DI mesh

Ro

llP

itc

hY

aw

Ph

iT

he

taP

si

No wakeSteady wakeTime-varying wake

Time(sec) Time(sec)

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0 10 20 30 40 50 6030

40

50

0 10 20 30 40 50 60

60

70

0 10 20 30 40 50 60

40

60

0 10 20 30 40 50 60

40

60

38 40 42 44 46 48 50 52 54 56 58 6040

45

50

38 40 42 44 46 48 50 52 54 56 58 6055

60

65

38 40 42 44 46 48 50 52 54 56 58 6050

55

60

38 40 42 44 46 48 50 52 54 56 58 60

40

50

60

• Stick inputs(%) 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%

Simulation Results of Shipboard Approach

Lat

eral

Lo

ng

itu

din

alC

olle

ctiv

eP

edal

Lat

eral

Lo

ng

itu

din

alC

olle

ctiv

eP

edal

Time(sec) Time(sec)

No wakeSteady wakeTime-varying wake

Enter the DI mesh

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38 40 42 44 46 48 50 52 54 56 58 6040

45

50

38 40 42 44 46 48 50 52 54 56 58 6055

60

65

38 40 42 44 46 48 50 52 54 56 58 6050

55

60

38 40 42 44 46 48 50 52 54 56 58 60

40

50

60

Time(sec)

Stochastic ship airwake model

• Correlated airwake is determined by passing through spectral filter with desired transfer function (ref.Clement, Labows et al.)

• Modeling parameters were obtained from flight test data(temporal data)• Need parameters that describe both the temporal and the spatial characteristics

Lat

eral

Lo

ng

itu

din

alC

olle

ctiv

eP

edal

Stochastic wakeTime-varying wake

wu

w sL

U

1

2 0

Transfer function

Correlatedairwakemodel

White

Noise

w

u

w

U

L

0

: turbulence intensity

: scale length of turbulence

: speed of the mean wind field

: PSD temporal break frequency

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Conclusions

• Dynamic interface simulation modelMATLAB 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 lawsShipboard 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

• 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

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Schedule and Milestones

Tasks 2001 2002 2004 2005

• 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 task-

tailored control• Lee PhD Degree

2003

CompletedShort TermLong Term

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• Improved Dynamic Interface SimulationIntegration of time varying CFD solutions of LHA airwakeIntegration with simple stochastic time-varying gust fieldPeters-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

2002 Accomplishments

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:

Leveraging or Attracting Other Resources or Programs:

Recommendations atthe Kickoff Meeting:

Actions Taken:

• 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.

• DURIP equipment grant supporting helicopter simulator project, being used for this project• Currently pursuing data from JSHIP program to help validate model.

• Need collaboration with U.S. Navy and possibly DERA

• Interacting with U.S. Navy Advanced Aerodynamics Group (Dave Findlay, Colin Wilkinson, Susan Polsky)

• No formal interaction with DERA (now QinetiQ?) at this time.