pi: asst. prof. joseph f. horn tel: (814) 865 6434 email: [email protected] graduate students: dooyong...

PENNSTATE1 8 5 5

PI: Asst. Prof. Joseph F. HornTel: (814) 865 6434 Email: [email protected]

Graduate Students: Dooyong Lee, PhD CandidateDerek Bridges, PhD Candidate

Project PS 5.2Simulation and Control of Shipboard Launch and

Recovery Operations

2005 RCOE Program Review

May 3, 2005

PENNSTATE1 8 5 5

• 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 Barriers• 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. Better engineering tools needed to reduce costs for analyzing current and future ships / aircraft.

• A practical, fully autonomous or piloted assisted landing AFCS has not yet been developed, need to assess requirements and potential benefits

PENNSTATE1 8 5 5

• 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

• Simulate UH-60 operating off LHA and validate model with JSHIP flight test data

• Develop new concepts in AFCS design for shipboard operations

• Develop a real-time simulation facility of shipboard operations (using DURIP funds)

PENNSTATE1 8 5 5

PSU DI Simulation Program

• Developed “tunable” pilot model for different levels of tracking tolerance

• Integrated CFD solutions of ship airwake with non-linear flight dynamics model

• Demonstrated using UH-60A / LHA combination, same as JSHIP flight test program

• Validated model with flight test data from JSHIP program

• Evaluate task tailored control laws

Matlab based DI simulation program(based on GENHEL)

Human pilot model(Optimal control model)

Time-accurateship airwake from CFD

Stochastic airwake model

Real-time simulation

Validation with flight test data

(from JSHIP program)Task-tailored control law design(using CONDUIT)

PENNSTATE1 8 5 5

Stochastic Ship Airwake Modeling

• A method for extracting equivalent airwake disturbances from flight test data (or high order simulation model) has been developed

Method is similar to that used for turbulence models developed at NASA Ames (Ref. Labows and Tischler et al, MacFarland - SORBET Model)

Filters are derived to simulate the spectral properties of the airwake, can compare to traditional turbulence models (e.g. von Karman, Dryden)

Spectral filters are based on von Karman model, and modified to fit the desired forms of spectral characteristics

• Stochastic airwake model can be readily used for flight control optimization

HelicopterDynamics

Pilot stick inputs

SAS

++

+

White noise Linear filter

Stochastic airwake model

Optimized to reject disturbances

Designed to fit the spectral properties

of the airwake

PENNSTATE1 8 5 5

Stochastic Ship Airwake ModelingSample Results for Vertical Component, 0° WOD

Extracted from simulationwith full time-varying airwake

von Karman Turbulence ModelLw = 37.8667 ft, w = 2.8067 ft/sec

32

2

1539.09754.19958.21

3398.07478.214

s

VL

sVL

sVL

sVL

sVL

VL

sHwww

wwww

“Best Fit” Spectral FilterLw =10.7156 ft, w = 4.81 ft/sec

32

2

8985.13169.35601.21

9173.05913.114

sV

Ls

V

Ls

V

L

sV

Ls

V

L

V

L

sHwww

wwww

Frequency (rad/sec)

PS

D o

f ve

rtic

al g

ust

co

mp

on

en

t, (

ft/s

ec)2

/(ra

d/s

ec)

PENNSTATE1 8 5 5

Stochastic Ship Airwake Modeling

Equivalent Airwake DisturbancesFull Time-Varying Airwake

• Comparison of response with stochastic airwake model, equivalent disturbances and full time-varying airwake (spectral data averaged over five runs)

Frequency (rad/sec)

LA

TL

ON

PE

DC

OL

- Input autospectrum(0 deg WOD), dB

Autospectra identified by CIFER

Stochastic Airwake

LA

TL

ON

PE

DC

OL

Frequency (rad/sec)

- Input autospectrum(30 deg WOD), dB

PENNSTATE1 8 5 5

• Using CONDUIT to optimize SAS gains• Include ADS-33 HQ specs as constraints in optimization• Include longitudinal acceleration feedback and pitch attitude feedback

Optimize for minimal gust

response

AirwakeSpectralFilters

Task-Tailored Control Design

Longitudinal accelerationfeedback to

improve gust response

Pitch attitude feedback to

provide closed-loop

stability

PENNSTATE1 8 5 5

Stability Augmentation System

• Optimize gains using CONDUIT

Based on phase-lag compensator

Design parameters include the prefix “dpp_”

Roll SAS

Pitch SAS

Yaw SAS

PENNSTATE1 8 5 5

HQ specs

• Selected design specs from CONDUIT as constraints

Closed-loop eigenvalues(EigLcG1), Gain/Phase margin(StbMgG1), Crossover frequency(CrsLnG1), Bandwidth for roll/pitch(BnwAtH1)

• New spec for disturbance rejection(DisRnL1)

Based on psd of angular rate response to corresponding gust input

Whitenoise

PSDTransfer function

)(

)()(

sq

sqsH

g

(Example) – Pitch rate

Frequency [rad/sec]M

agn

itu

de

[dB

]

Level I

Level II

Level III

PENNSTATE1 8 5 5

HQ Specification Window

• Original SAS configurations - 30 degree WOD condition

rollpitchyaw

(1)(2)(3)

CrsLnG1 (1) CrsLnG1 (2) CrsLnG1 (3) EigLcG1 (1)EigLcG1 (2)EigLcG1 (3)StbMgG1 (1)StbMgG1 (2)StbMgG1 (3)BnwAtH1 (1)BnwAtH1 (2)DisRnL1 (2)DisRnL1 (3)DisRnL2 (1)

S J J

H H H

PENNSTATE1 8 5 5

HQ Specification Window

• Modified SAS configurations - 30 degree WOD condition

S J J

H H H

CrsLnG1 (1) CrsLnG1 (2) CrsLnG1 (3) EigLcG1 (1)EigLcG1 (2)EigLcG1 (3)StbMgG1 (1)StbMgG1 (2)StbMgG1 (3)BnwAtH1 (1)BnwAtH1 (2)DisRnL1 (2)DisRnL1 (3)DisRnL2 (1)

rollpitchyaw

(1)(2)(3)

PENNSTATE1 8 5 5

Simulation Results - Hovering Flight

• Angular rate responses (deg/sec)

Result with Original SAS configurationsResult with Optimized SAS configurations

Time [sec]

P,

de

g/s

ec

Q,

de

g/s

ec

R,

de

g/s

ec

- 30 degree WOD

P,

de

g/s

ec

Q,

de

g/s

ec

R,

de

g/s

ec

Time [sec]

- 0 degree WOD

PENNSTATE1 8 5 5


• SAS outputs (%)


- 30 degree WOD

Time [sec]

RS

AS

, %

PS

AS

, %

YS

AS

, %

RS

AS

, %

PS

AS

, %

YS

AS

, %

Time [sec]

- 0 degree WOD

PENNSTATE1 8 5 5

• Pilot stick inputs (%)


- 0 degree WOD - 30 degree WOD

Time [sec] Time [sec]


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%

LA

T,

%L

ON

, %

PE

D,

%C

OL

, %

LA

T,

%L

ON

, %

PE

D,

%C

OL

, %

PENNSTATE1 8 5 5


• Angular rate autospectrum (dB)


- 30 degree WOD

P,

dB

Q,

dB

R,

dB

- 0 degree WOD


P,

dB

Q,

dB

R,

dB

Frequency [rad/sec] Frequency [rad/sec]

PENNSTATE1 8 5 5

• Pilot stick input autospectrum (dB)





LA

T,

dB

LO

N,

dB

PE

D,

dB

CO

L,

dB


LA

T,

dB

LO

N,

dB

PE

D,

dB

CO

L,

dB

PENNSTATE1 8 5 5

H infinity Controller for SAS

• Include frequency-dependent weight functions for control inputs and outputs• Produce a controller K∞

to reduce the tracking deviations to reject disturbances

• We is a high-gain low-pass filter for good tracking and disturbance rejection• Wu is a low-gain high-pass filter to improve the robustness and to limit the control activity

H∞ controller(K∞)

Aircraft(UH-60)

Weighting(We)

Weighting(Wu)

Gust Filter(Wg)

+ + +

-

dw

d

uee

eu

yref + +

dt

PENNSTATE1 8 5 5

H infinity Controller Design

22212

12111

21

DDC

DDC

BBA

G

uDwDxCy

uDwDxCz

uBwBxAx

22212

12111

21

x

• Obtain a controller solving a classical 4-block problem based on 8-rigid-state linearized aircraft model 3 diagonal components of weighting functions iterate to find the optimal weighting parameters

w

z

u

yAircraft

We

Wu

=dw

dt=

pqr

=ee

eu=

rsaspsasysas

=, , , , ,

14-state H∞ controller

u

w

x

DDC

DDC

BBA

y

z

x

22212

12111

21

PENNSTATE1 8 5 5


• Angular rate responses (deg/sec)

Time [sec]

P,

de

g/s

ec

Q,

de

g/s

ec

R,

de

g/s

ec

- 30 degree WOD

P,

de

g/s

ec

Q,

de

g/s

ec

R,

de

g/s

ec

Time [sec]

- 0 degree WOD

Result with Original SAS configurationsResult with Optimized SAS configurationsResult with H infinity controller

PENNSTATE1 8 5 5


• SAS outputs (%)

- 30 degree WOD

Time [sec]

RS

AS

, %

PS

AS

, %

YS

AS

, %

RS

AS

, %

PS

AS

, %

YS

AS

, %

Time [sec]

- 0 degree WOD


PENNSTATE1 8 5 5


• Pilot stick inputs (%)


Time [sec] Time [sec]

LA

T,

%L

ON

, %

PE

D,

%C

OL

, %

LA

T,

%L

ON

, %

PE

D,

%C

OL

, %


PENNSTATE1 8 5 5


• Angular rate autospectrum (dB)

- 30 degree WOD

P,

dB

Q,

dB

R,

dB

- 0 degree WOD


P,

dB

Q,

dB

R,

dB



PENNSTATE1 8 5 5


• Pilot stick input autospectrum (dB)



LA

T,

dB

LO

N,

dB

PE

D,

dB

CO

L,

dB


LA

T,

dB

LO

N,

dB

PE

D,

dB

CO

L,

dB


PENNSTATE1 8 5 5

Rotorcraft Flight Simulator

• Flight dynamics model is based on Genhel• Use FlightGear environment for visualization

• Integrated with time-varying airwake data from CFD• Integrated with CHARM freewake model

PENNSTATE1 8 5 5

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

(using JSHIP data)• Develop stochastic airwakes

disturbance model and develop physical understanding

• Develop real-time simulation capability at PSU

• Incorporate CHARM free wake into the model

• Task tailored control law design, support with real-time simulator at PSU

• Lee PhD Degree• Derek Bridges PhD Degree

2003

CompletedShort TermLong Term

2006

PENNSTATE1 8 5 5

•Developed stochastic airwake disturbance model for 0° and 30° WOD, use for off-line analysis, real-time simulation and flight control design

•Real-time simulation facility is ready, integrated with time-varying airwake model and CHARM freewake model

•Developed task-tailored control laws using CONDUIT and H infinity control method

•Presented results at 2004 AIAA AFM conference, paper published in AIAA Journal of Aircraft, paper submitted to Journal of Aerospace Engineering (special issue on shipboard aviation)

2004 Accomplishments

Planned Accomplishments for 2005•Will present results at 2005 AHS Forum and submit as journal article•Continue to update and improve model, include the deck ground effects •Further study in task tailored control laws to improve disturbance rejection•Expand flight control design efforts, autonomous landing flight control system, position hold over ship deck

• Investigate use of equivalent airwake disturbances as tool for validating ship CFD airwake models.

PENNSTATE1 8 5 5

Technology Transfer Activities:

Leveraging or Attracting Other Resources or Programs:

Recommendations atthe 2004 Review:

Actions Taken:

• Presented results at 2004 AIAA AFM Conference• Briefing to Navy Flight Dynamics Group at in Summer 2004, planning further interaction.

• Obtained JSHIP flight test data for validation, Cdr. Kevin Delemar at NRTC is contact • Integrating with CHARM free wake model• Integrated model and controllers with simulation facility developed under DURIP funds

Get with Navy to focus the project and also to interface with CFD activities (flow field).

Met with Navy. Received recommendations and we are planning more interaction. Proposed use of equivalent airwake disturbance model as tool for validation of CFD airwakes.

PENNSTATE1 8 5 5

Overview of Accomplishments2001-2005

Advanced Simulation Model for Shipboard Operations• Interface with time accurate CFD solutions of ship airwake• High order Peters-He inflow• Tunable OCM pilot model • MATLAB / Simulink version of model for rapid

development and control design• Validation against JSHIP flight test data • Implemented in real-time simulation facility at PSU

Stochastic Airwake Disturbance Model• Method for extracting equivalent disturbances from simulation

with full CFD airwake (can also be applied to flight test data)• Derived spectral filters to represent airwake disturbances

Task-Tailored Control Design for Shipboard Operations• Optimized SAS for operation in airwake using CONDUIT®

• Use spectral filters in control synthesis• Optimized SAS using H∞ synthesis

Publications• 5 conference papers, 1 journal paper published, 1 journal paper under review



32

2

1539.09754.19958.21

3398.07478.214

sV

Ls

V

Ls

V

L

sV

Ls

V

L

V

L

sHwww

wwww


32

2

8985.13169.35601.21

9173.05913.114

sVL

sVL

sVL

sVL

sVL

VL

sHwww

wwww

Frequency (rad/sec)

PS

D o

f v

ert

ica

l g

us

t c

om

po

ne

nt,

(ft

/se

c)2

/(ra

d/s

ec

)



32

2

1539.09754.19958.21

3398.07478.214

sV

Ls

V

Ls

V

L

sV

Ls

V

L

V

L

sHwww

wwww


32

2

8985.13169.35601.21

9173.05913.114

sVL

sVL

sVL

sVL

sVL

VL

sHwww

wwww

Frequency (rad/sec)

PS

D o

f v

ert

ica

l g

us

t c

om

po

ne

nt,

(ft

/se

c)2

/(ra

d/s

ec

)


response





provide closed-loop

stability


response


response





provide closed-loop

stability

PENNSTATE1 8 5 5

Future Path

Additional Basic Research

Transition to Applications / Applied Research

• Should pursue similar analyses to study effects of building airwakes on UAVs operating in urban areas, proposed as follow on for next RCOE

• Potential to investigate impacts on shipboard handling qualities requirements – Maritime ADS-33.

• Could make further efforts to pursue the fully coupled problem, model effect of rotor wake on ship airwake, would need more CFD expertise

• Apply equivalent airwake disturbance method to validate ship airwake CFD analysis. Airwake disturbance can be extracted from flight test and compared to simulation with CFD wake

• Use stochastic airwake model as a simplified and more compact model for use in trainers

• Apply maneuver controller and simulation for analysis of new aircraft and new ship designs

pi: asst. prof. joseph f. horn tel: (814) 865 6434 email: [email protected] graduate students: dooyong...

Documents

advanced simulation

flight test time

jship flight test program

model industry

model improvements

jship flight test data

control of shipboard

pilot control