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1 Vanderbilt University Vibro-Acoustics Laboratory Decentralized Structural Acoustic Control of a Launch Vehicle Payload Fairing Kenneth D Frampton Dept. of Mechanical Engineering Vanderbilt University

Vanderbilt University Vibro-Acoustics Laboratory 1 Decentralized Structural Acoustic Control of a Launch Vehicle Payload Fairing Kenneth D Frampton Dept

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1

Van

derb

ilt

Un

ivers

ity

Vibro-AcousticsLaboratory

Decentralized Structural Acoustic Control of a Launch Vehicle

Payload FairingKenneth D Frampton

Dept. of Mechanical Engineering

Vanderbilt University

Van

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Vibro-AcousticsLaboratory

Objectives Develop decentralized control systems for launch

vehicle payload fairings Control of fairing vibro-acoustic response based on

group management middleware services– Groups assigned by modal sensitivity– Groups assigned geographically

Investigate the effects of networked embedded systems constraints on control performance

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Launch Vehicle Payload Fairing

Initial efforts focus on a 1/3 scale model Study of a 40 mode finite element model Modes 8,9,13,14,15,16 are known to be

the most efficient radiators

High noise levels in launch vehicles cause damage to payloads

Reduction in noise levels will save in payload deployment costs

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Decentralized Control Control of large scale systems with networked

embedded processors Each “node” consists of an inexpensive, small,

computationally limited processor with sensors, actuators and network communications

Large numbers of nodes distributed throughout the system

Robustness to failures and scalability are critical issues

A11 A12 A13 A14 A15 A16 A17 A18

Disturbance

VibratingBeam

Sensors & Actuators

DecentralizedControl

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Control based on Group Management Middleware Assuming that groups can be defined and managed

– How well can specific modes be targeted?– At what cost is this type of control achieved?– What information exchange among group members offers

the best advantage?– What type of grouping yields the best performance?

Two types of locally optimal control design– Each node receives sensor signals from all group members

to produce local control signal– Each node uses it’s local sensor signal to command

actuators of all group members Grouping based on structural modes or geographic

neighbors

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Two-Port Control Design Objective is to minimize Disturbance to Performance

path with sensor/control closed loop– Performance Targeted Modes: 8, 9, 13, 14, 15, 16– Modal Groups: 15 sensors most sensitive to each mode

We can design compensators that are locally, but not globally, optimal

Plant

Compensator

DisturbancePerformance

Control Sensor

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Sensor Data ExchangeModal Grouping

100 150 200 250 300 350 40010

-1

100

Control Effort norm = 0.34506Open Loop norm = 35.0741Closed Loop norm = 34.814

Without control

With control

Frequency, Hz

Dis

turb

ance

to

Sen

sor

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Val

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Actuation Data ExchangeModal Grouping

100 150 200 250 300 350 40010

-1

100

Control Effort norm = 0.33419Open Loop norm = 35.0741Closed Loop norm = 33.7718

Fairing Modal Control by Modal Groups, Actuator Comm.

Without controlWith control

Frequency, Hz

Dis

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Sin

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Sensor Data ExchangeGeographic Grouping, Reach 5

150 200 250 300 350 400

10-1

100

Control Effort norm = 0.36824

Open Loop norm = 35.0741

Closed Loop norm = 29.2118

Frequency, Hz

Dis

turb

ance

to

Sen

sor

Sin

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lar

Val

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Without controlWith control

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Effects of Communication Delay

Effects established through SIESTA simulations of beam vibration control

Control system sampling rate of 2 kHz 100 node system Delays accumulate as signals are passed

from node to node

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Effects of Delay:Bandwidth 750 Hz, Reach 5

200 300 400 500 600 700-70

-65

-60

-55

-50

-45

-40

-35

-30

-25

-20

Freq=750Hz, Share=5

Frequency(Hz)

Tra

nsfe

r fu

nctio

n es

timat

e(dB

)

No feedbackdelay010delay200delay800

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Effects of Delay:Bandwidth 750 Hz, Reach 5

120 140 160 180 200 220 240 260 280 300 320

-65

-60

-55

-50

-45

-40

-35

-30

-25

Freq=750Hz, Share=5

Frequency(Hz)

Tra

nsf

er

fun

ctio

n e

stim

ate

(dB

)

No feedbackDelay 10Delay 200Delay 800

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Conclusions Fairing Control

– Specific modes can be targeted for control– Control effort and spillover are not a problem– Sensor data exchange among nodes is not necessarily the best

approach. Exchanging control signals or a mixed approach may be preferable.

– Geographic grouping may be as good as modal grouping IF you have a good model and good design tools

Effects of Delay– For a system with a bandwidth in the hundreds of Hz and a sampling

rate of 2 kHz, delays on the order of hundreds of microseconds can result in significant degradation in performance.

– The reach of the system is affects the impact due to accumulated delays