1 지진하중을 받는 구조물의 mr 댐퍼의 동특성을 고려한 반능동 신경망제어...

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지진하중을 받는 구조물의 지진하중을 받는 구조물의 MR MR 댐퍼의 동특성을 고려한댐퍼의 동특성을 고려한

반능동 신경망제어 반능동 신경망제어

Heon-Jae Lee1), Hyung-Jo Jung 2), Ju-Won Oh 3) , In-Won Lee4)

1) Graduate Student, Dept. of Civil and Environmental Engineering, KAIST

2) Assistant Professor, Dept. of Civil Engineering, Sejong University

3) Professor, Department of Civil Engineering, Hannam University

4) Professor, Dept. of Civil and Environmental Engineering, KAIST

Heon-Jae Lee1), Hyung-Jo Jung 2), Ju-Won Oh 3) , In-Won Lee4)

1) Graduate Student, Dept. of Civil and Environmental Engineering, KAIST

2) Assistant Professor, Dept. of Civil Engineering, Sejong University

3) Professor, Department of Civil Engineering, Hannam University

4) Professor, Dept. of Civil and Environmental Engineering, KAIST

2003 년도 대한토목학회 학술발표회

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IntroductionIntroduction

Semi-active control strategy has attractive feature such as

- bounded input and bounded output stability - small energy requirement - not only the reliability of passive control but also the

adaptability of fully active control

Neural network also has attractive feature such as

- ability of producing continuous control signal - adaptability for non-linear problems - no need the mathematical model for solving any

engineering problems

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Proposed MethodProposed Method

STRUCTURE

Neural Network

xx ,gx

fMR Damper

Clipped

Algorithmdf

v

Clipped Neuro-Control

Block diagram of the proposed method

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Clipped AlgorithmClipped Algorithm

• desired force (by neural network) :

• generated force (by MR damper) :df

f

df

f

0v

0v

0v

0v

maxVv

maxVv

5

Numerical ExampleNumerical Example

velocity of 3rd floor

ground acceleration

controlforce

displacement of 3rd floor

velocity of 1st floor

displacement of 1st floor

gx Example Structure;Dyke el al. (1996)

Neural Netwokr used inthis study

0 4 8 12 16 20-4

-2

0

2

4

El Centro(0.348g)

0 2 4 6-4

-2

0

2

4

Kobe(0.334g)

0 2 4 6 8-2

-1

0

1

2

California(0.156g)

Training

Verification

6

0 2 4 6-1

-0.5

0

0.5

1

0 2 4 6-1

-0.5

0

0.5

1

Time(sec)

Dis

pla

cem

ent

(cm

)D

isp

lace

men

t (c

m)

• Displacement of the 3rd floor (El Centro)• Displacement of the 3rd floor (El Centro)

Training ResultsTraining Results

Clipped

optimal

Proposed

method

: uncontrolled : controlled

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• Acceleration of the 1st floor (El Centro)• Acceleration of the 1st floor (El Centro)

Training ResultsTraining Results

Clipped optimal

Proposed

method

0 2 4 6-1000

-500

0

500

1000

Time(sec)

Acc

eler

atio

n (

cm/s

ec2

)A

ccel

erat

ion

(cm

/sec

2)

0 2 4 6-1000

-500

0

500

1000

: uncontrolled : controlled

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Control ResultsControl Results

ControlStrategy

UncontrolledClippedoptimal

Proposedmethod

0.541 0.115 (1.000) 0.117 (1.017)

0.825 0.186 (1.000) 0.171 (0.919)

0.963 0.236 (1.000) 0.240 (1.017)

0.541 0.115 (1.000) 0.117 (1.017)

0.320 0.090 (1.000) 0.111 (1.233)

0.201 0.101 (1.000) 0.082 (0.812)

861 733 (1.000) 429 (0.585)

1040 746 (1.000) 503 (0.674)

1401 705 (1.000) 571 (0.810)

- 954 (1.000) 852 (0.893))(Nf

aix

id

ix

)(cm

)(cm

)/( 2scm

• Maximum responses under El Centro earthquake• Maximum responses under El Centro earthquake

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ControlStrategy


Proposedmethod

0.341 0.054 (1.000) 0.043 (0.796)

0.480 0.094 (1.000) 0.071 (0.755)

0.576 0.114 (1.000) 0.100 (0.877)

0.341 0.054 (1.000) 0.043 (0.796)

0.179 0.041 (1.000) 0.048 (1.171)

0.107 0.041 (1.000) 0.039 (0.951)

570 389 (1.000) 181 (0.465)

653 285 (1.000) 250 (0.877)

744 285 (1.000) 273 (0.958)

- 411 (1.000) 319 (0.776))(Nf

aix

id

ix

)(cm

)(cm

)/( 2scm

• Maximum responses under California earthquake• Maximum responses under California earthquake

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ControlStrategy


Proposedmethod

1.486 0.700 (1.000) 0.480 (0.686)

2.373 1.181 (1.000) 0.819 (0.693)

2.877 1.444 (1.000) 1.013 (0.702)

1.486 0.700 (1.000) 0.480 (0.686)

0.895 0.487 (1.000) 0.373 (0.766)

0.528 0.328 (1.000) 0.208 (0.634)

2337 1936 (1.000) 940 (0.486)

2793 1929 (1.000) 1438 (0.745)

3676 2280 (1.000) 1445 (0.634)

- 1324 (1.000) 1513 (1.143))(Nf

aix

id

ix

)(cm

)(cm

)/( 2scm

• Maximum responses under Kobe earthquake• Maximum responses under Kobe earthquake

110 0.2 0.4 0.6 0.8

0.3

0.4

0.5

0.6

Peak Ground Acceleration (g)

Max

imu

m d

rift

of

3rd f

loor

Clipped optimalProposed method

Kobe earthquake

California earthquake

El Centro earthquake


• Maximum drift of the 3rd floor• Maximum drift of the 3rd floor

12Peak Ground Acceleration (g)

Clipped optimalProposed method

Kobe earthquake

California earthquake

El Centro earthquake


• Maximum acceleration of the 1st floor• Maximum acceleration of the 1st floorM

axim

um

acc

eler

atio

n o

f 1st

flo

or

0 0.2 0.4 0.6 0.80

0.4

0.8

1.2

1.6

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ConclusionsConclusions

• A semi-active neuro-control technique using MR damper for seismically excited structure is proposed.

• The performance of the proposed method is better than that of the clipped optimal control method.

( max. drift of 3rd floor : 5 ~ 34 % reduction,

max. acceleration of 1st floor : 37 ~ 69 % reduction )

The proposed semiactive neuro-control technique using MR dampers could be effectively used for control of seismically excited structures!

1 지진하중을 받는 구조물의 mr 댐퍼의 동특성을 고려한 반능동 신경망제어...

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