TELKOM
NIKA Indonesia
n
Journal of
Electrical En
gineering
Vol.12, No.6, Jun
e
201
4, pp. 4787 ~ 4
7
9
3
DOI: 10.115
9
1
/telkomni
ka.
v
12i6.552
3
4787
Re
cei
v
ed
De
cem
ber 3
0
, 2013; Re
vi
sed
March 12, 20
14; Accepted
March 26, 20
14
Marine Sink-Float Safety Device’s Co
ntrol System
Based on Fuzzy Control
Zi Yue Wu
1
, Jie Qi
2
, Chen
NanXue
3
Coll
eg
e of Engi
neer
ing, Sh
ang
hai Ocea
n Uni
v
ersit
y
, No.
999
, Hu Chen
gHu
an Ro
ad, Li
n g
ang n
e
w
cit
y
,
Shan
gh
ai, P.R. Chin
a
*Corres
p
o
ndi
n
g
author
, e-ma
i
l
: z
y
w
u
@sh
ou.
edu.cn
1
, w
u
yu
3
1
1
1
2
5
s@
163.c
o
m
2
,
xuec
he
nn
an@
gmai
l.com
3
A
b
st
r
a
ct
In order
to e
n
s
ure safety w
o
rk of marin
e
e
qui
p
m
ent, this
pap
er i
n
trod
u
c
es a k
i
nd
of
sink-flo
at
safety
dev
ice w
h
ich
ca
n mat
c
h
w
i
th mari
ne
equ
ip
me
nt
to
r
eali
z
e
protecti
o
n
w
o
rk, an
d a
fu
zz
y
co
ntroll
er
set
up by fu
zz
y
c
ontrol a
l
g
o
rith
m. T
he d
a
ta o
f
the contro
l s
ystem is c
o
ll
e
c
ted by
multi-s
ensor a
nd fi
lte
r
ed
throug
h the filt
er circuit. Un
d
e
r a 5 gr
ad
e sea co
nditi
on,
the marin
e
si
nk-float safety
device c
an c
a
rry
mar
i
ne
eq
ui
p
m
e
n
t, esca
pin
g
fro
m
the
ha
rsh mari
ne
en
viron
m
e
n
t by
divin
g
to
a ce
rtain d
epth. T
h
e
simulati
on i
n
MAT
L
AB/Simul
i
nk show
s that
the cont
rol sy
stem co
uld re
spons
e fast and op
erate sta
b
ly.
F
u
rthermore, i
t
is ab
le to c
ontrol s
i
nk-flo
at safe
ty dev
i
c
e efficie
n
tly
and r
eac
h to
the pr
eset d
e
p
t
h
accurate
ly. So w
e
can guar
an
teethe o
per
ati
o
n of mari
ne e
q
u
ip
ment reaso
nab
ly.
Ke
y
w
ords
: sink-float, safety
device, fu
zz
y c
o
ntrol
Copy
right
©
2014 In
stitu
t
e o
f
Ad
van
ced
En
g
i
n
eerin
g and
Scien
ce. All
rig
h
t
s reser
ve
d
.
1. Introduc
tion
Due
to
China
'
s
e
c
o
nomi
c
a
nd
so
cial d
e
velopme
n
t, lan
d
re
so
urce
s
a
nd
spa
c
e
hav
e be
en
difficult to meet the dem
a
nd of so
cial
developm
ent.People h
a
ve to pay more
attention to the
developm
ent
and utilizati
on of oce
a
n
reso
urce
s. There are in
cr
e
a
si
ng nu
mbers of re
search
about ma
rine
engine
erin
g
equipme
n
t.Develo
p
ing
marin
e
equip
m
ent has b
e
c
ome o
ne of
the
importa
nt research di
re
ctio
ns
of state a
nd university.For exam
pl
e, the maritime
buoyage, AIDS
to navigation
lights, the
ocean
wave e
n
e
rgy a
nd
win
d
ene
rgy p
o
w
er ge
neration devi
c
e a
s
well
as
small
mari
ne mo
nitorin
g
platform [1].
Gene
rally, m
any mari
ne e
quipme
n
tare
alway
s
floatin
g
on the se
a, which a
r
e di
re
ctly influenced
by various
e
n
vironm
ental
factors,
espe
cially the stro
ng
wind and big waves, and it will make the equi
pment drift, overturn,
even directly damage
the
marin
e
eq
uip
m
ent. The
r
ef
ore, it is
ne
ce
ssary to rese
arch
safety d
e
vice of m
a
ri
ne eq
uipme
n
t [2].
The ma
rine
si
nk-flo
at safety device
whi
c
h we
de
sign
e
d
ca
n coop
erate with m
a
ri
ne eq
uipme
n
t to
provide b
uoy
ancy,a
c
cordi
ng to differe
nt marine
eq
uipment
s, the safety device can adju
s
t the
external structure or co
mbi
nation
fo
rm
s to
meet
th
e
requireme
nts
of the
sin
k
ing
and
floating.
In
bad
e
n
viron
m
ental condi
tions,
the co
ntrol system
will
control
safety
device whi
c
h can carry
marin
e
eq
uip
m
ent de
scen
d to settled
depth to
a
v
oid influen
ce ofbig
wav
e
s. And it a
l
so
guarantee
s th
e ope
ratio
n
of
the ma
rine
e
quipme
n
t. In
this
pro
c
e
s
s, the ma
rine
si
n
k
-float
safety
s’
control
syste
m
ha
s great
signifi
can
c
e t
o
gua
rante
e
t
he no
rmal
wo
rk
of the eq
ui
pment in m
a
rine
work platform
. At pre
s
e
n
t, control m
e
tho
d
mai
n
ly in
cl
ude PI
D al
go
rithm [3], "big
syste
m
" the
o
ry
of cont
rol alg
o
rithm [4], the
fuzzy
cont
rol
algorith
m
[5, 6] and n
eural
netwo
rk
co
ntrol algo
rithm [
7
]
as well a
s
some alg
o
rith
m improve
d
by above se
veral ki
nd
s o
f
algorithm.
The fuzzy co
ntrol
strategy is eff
e
ctive fo
r sy
stems whi
c
h h
a
ve large tim
e
con
s
tant
s a
nd distu
r
ba
nces a
s
well a
s
fit
for sy
stem
s that lack
of a
c
curate
math
ematical
mod
e
l. Its usesre
gular mathe
m
atics varia
b
l
es
repla
c
e
ling
u
i
s
tic va
riabl
es and
then
co
mbine
with t
he p
h
ysi
c
al
system. Beca
use
the m
a
ri
ne
sin
k
-float safety device is difficult to establish
accu
ra
te mathemati
c
al mod
e
l, so
we use the fuzzy
control
al
go
rithm
to esta
blish co
ntrol sy
stem.
Th
e d
a
t
a of the
co
ntrol
system
co
llected
by mu
lti-
sen
s
o
r
is filte
r
edby filter
m
e
thod in
ord
e
r
to elim
in
ate
errors an
d int
e
rferen
ce
sig
nals.In the
en
d
,
the simulatio
n
of sink-float
safety dev
ice
control i
s
do
ne by MATLAB/Simulink.
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ISSN: 23
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046
TELKOM
NI
KA
Vol. 12, No. 6, June 20
14: 4787 – 4
793
4788
2. The Struc
t
ure of Sink-float Safet
y
Dev
i
ce
The
sin
k
-float
safety devi
c
e is
sh
own in
Fi
gure 1,
whi
c
h m
a
inly in
cl
ude
s the
sol
a
r pa
nel,
external g
a
sbag an
d security buoy. T
he solar
pan
el is em
bed
d
ed on the to
p of the external
gasbag. T
h
e
external
ga
sba
g
i
s
h
ang
ing a
r
ou
nd
t
he e
dge
of t
he
se
curity b
uoy, whi
c
h
can
provide
s
buo
yancy
to
the sin
k
-float saf
e
ty
devic
e
when it i
s
on t
he surfa
c
e
of oce
an. Se
cu
rity
buoy is one o
f
the most important
pa
rts,
which can re
alize the si
nki
ng and floatin
g by the way of
water inj
e
ctio
n and draina
g
e
.
Figure 3. The
Overall Stru
cture of Marin
e
Safety Device
The m
a
rin
e
e
quipme
n
t is i
n
stalle
d at th
e cent
e
r
p
o
si
tion of the
si
nk-flo
at
safet
y
device,
and the exte
rnal g
a
sbag
and
se
cu
rity
buoy are uni
formly dist
ri
b
u
ted on the
perip
he
ry. The
maximum loading of si
nk-float safety device
is
160kg.If the load is less than
160kg, we
can
increase the
water
storage of secu
rity buoy to
reach
the equilibri
um
state; if the load i
s
heavier
than 160
kg,
we can
cha
nge the
size
of the se
cu
rity buoy an
d external g
a
sb
ag to me
et
requi
rem
ents.
In addition,
we
can u
s
e
a com
b
i
nati
on way of many devices
to achi
eve the
security
state of equilibrium acco
rding
to the wei
ght
of the load. As shown in
Figure 2, three
combi
nation f
o
rm
s of sin
k
-f
loat safety de
vice lik
e thi
s
way a, b and
c.The d
e
vice
is not limited
to
these th
ree f
o
rm
s in figu
re, and the n
u
mbe
r
and
combinatio
n form
s are al
so determined
by
different mari
ne equi
pment
.
(a)
(b)
(c
)
Figure 2. The
Combin
ation
Form
s of
the Sink-float Sa
fety Device
The liq
uid l
e
vel se
nsorsa
nd p
r
e
s
sure
sen
s
o
r
s a
r
e
hangi
ng
aro
u
nd the
oute
r
of the
se
curity bu
oy, and they are also
con
n
e
c
ted with
th
e
internal
cont
rol mod
u
le. Und
e
r a 5 g
r
ade
sea co
ndition
,
the
cont
rol module will
m
a
ke sin
k
in
g
in
stru
ction
s
an
d the a
c
tuato
r
sta
r
t wo
rkin
g in
se
curity bu
oy. Therefo
r
e,
water is flo
w
into t
he security buoy, reali
z
ing th
e dive
work g
r
a
duall
y
.
At the settled
depth, the
si
n
k
-float
safety device
conn
e
c
ted
with
marine e
quipm
en
t is u
pen
ded
i
n
water.
Gen
e
rally, after 48
hours, the
co
ntrol
m
odule
willsend
s
a
st
op comma
nd automatically
to
anothe
r a
c
tu
ator, then
the
sin
k
-flo
at safety device
wil
l
float to the
surfa
c
e
of th
e ma
rine. By
the
way, the safe
ty device has
compl
e
ted th
e safety prote
c
tion task.
3. The Desig
n
of Con
t
rol
Sy
stem
In orde
r to ensure normal
work of the si
nk
-flo
at safet
y
device and
marin
e
equip
m
ent, it
is very impo
rtant to de
si
gn an effici
e
n
t contro
l sy
stem. By analyzing the
chara
c
te
risti
c
s of
several curre
n
t mainly con
t
rol method
s,
and this
p
a
p
e
r is p
r
o
p
o
s
e
s
a mod
e
of fuzzy cont
rol to
achi
eve safety and ste
adi
ness in th
e control
system
of marin
e
si
nk-flo
at safet
y
device. Fu
zzy
control i
s
based o
n
lin
gui
stic va
riable
s
rather t
han
re
gular math
e
m
atics vari
ab
les. T
o
a
c
hi
e
v
e a
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TELKOM
NIKA
ISSN:
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046
Optim
a
l Asymm
e
tric S-sh
ape Accele
rat
i
on/De
cel
e
rati
on for Multi-a
x
ial… (Ch
ang
-ya
n
Ch
ou
)
4789
prop
er
cont
rol re
sult, on
e must give
up traditio
n
a
l com
p
lex
math equ
atio
ns a
nd ad
op
t th
e
accumul
a
ted
experie
nce of manipulat
o
r
s to control the
entire sy
ste
m
.
3.1. The Ov
e
r
all Design o
f
Con
t
rol Sy
stem
In orde
r to make
sure eve
r
y factorin
put
to
the control system a
c
curately, we use five
pre
s
sure
sen
s
ors an
d two
liquid
level
sensors to
mo
nitor
sign
als.
The li
quid
lev
e
l sen
s
ors an
d
pre
s
sure se
n
s
ors a
r
e h
a
n
g
ing a
r
ou
nd
the outer
of
the secu
rity b
uoy. Use the
actuato
r
s
(the
valve in the
se
curity
buoy
) reali
z
e th
e
work of
wate
r inj
e
ction
a
n
d
d
r
aina
ge.
There i
s
a
fil
t
er
circuit to filtering si
gnal
swh
i
ch
colle
cted
by sen
s
o
r
s
a
s
to elimin
ate
interferen
ce.
Otherwi
se,
we
use fu
zzy co
ntrol alg
o
rith
m to de
sign
a fuzzy co
nt
roller to
co
ntrol actu
ator. T
he overall sy
stem
stru
cture diag
ram is
sho
w
n
in Figure 3.
Figure 3. Overall Syst
em Structu
r
e Di
agram
3.2. Filtering Principle
The m
a
rin
e
si
nk-flo
at safety device flo
a
ts o
n
the
se
a, whi
c
h i
s
di
re
ctly influence
d
by the
variou
s e
n
vironmental
factors,
so it n
e
c
e
s
sary to
d
e
sig
n
a filter circuit
exclu
d
ing the
fault
of
sen
s
o
r
s
and
other inte
rference erro
r si
gnal
s gen
er
a
t
ed by the ou
tside
worl
d. T
he ma
rine
si
nk-
float safety d
e
vice
ca
rrie
d
marin
e
eq
uip
m
ent di
ve to
a certain
dept
h to avoid
ba
d environme
n
t
in
a 5 grad
e se
a conditio
n
o
r
more tha
n
5 grad
ec
ondit
i
on. Acco
rdin
g to hydrome
c
ha
nics analy
s
is
method [1],
ata 5 g
r
a
de
sea
condition
, the dete
c
te
dpre
s
su
reof
wave d
e
tecti
ng unit i
s
ab
out
350
N. Therefore, the filter circuit sh
ould
ru
le out the si
gnal
s beyon
d
0-360
N befo
r
e sin
k
ing.
3.3. The Stru
cture o
f
Fu
zz
y
Controller
The diffe
ren
c
e
between
fuzzy control sy
st
em a
nd g
ene
ral
control
syste
m
is th
e
controller designed
by fuzzy contro
ller.
This
system
is a doubl
e input and
double output
cont
rol
system.
The
r
e a
r
e t
w
o
act
uators
aim to
differe
nt
working
p
r
o
c
e
ss,
and
one
of t
he a
c
tuato
r
s
is
use
d
fo
r d
r
ai
nage
an
d a
n
o
ther is u
s
e
d
to
wate
r
in
jection. The
basi
c
structu
r
e of
the
fu
zzy
controlle
r in
clud
es four part
s
: fu
zzi
fication,
fu
zzy kno
w
le
dge
base, de
ci
si
on ma
kin
g
and
defuzz
i
fication [8-11], it is
s
h
own in Figure 4.
Figure 4. Basic Structu
r
e o
f
Fuzzy Controller
3.3.1. Fuzzi
fication
For an a
c
tua
lly control p
r
oce
s
s, there
is al
ways a range of inp
u
t to fuzzy co
ntrolle
r,
whi
c
h i
s
call
ed the
“do
m
ain”. T
he m
a
inly purpo
se
o
f
fuzzifi
cation
isthe
domai
n tran
sfo
r
mat
i
on,
namely, givin
g
assig
n
me
n
t
to the lan
g
uage
va
ria
b
le. Otherwi
se,
we
sh
ould
define la
ngu
age
variable
s
of i
nput an
d out
put. The d
ept
h deviation
"
e
"
(stated d
epth
R – me
asure
d
depth Y
)
an
d
the rate of depth chan
ge
"ec"
serve as the in
put variable
s
of
the fuzzy control. The b
a
si
c domai
n
of depth devi
a
tion
"
e
"
is [-5, 5], m and the
basi
c
dom
ai
n of depth g
r
adient
"ec"
is
[-1,1], m/s
.
We
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TELKOM
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Vol. 12, No. 6, June 20
14: 4787 – 4
793
4790
also
cho
o
se
the type of membershi
p
functi
on i
s
Gau
s
sian
function
which h
a
s
co
ntrol
cha
r
a
c
teri
stic of stabilizati
on and low sensitiv
ity. Th
e membershi
p
function of
input e and
ec
is
sho
w
n in Fig
u
re 5. The m
e
mbe
r
ship fu
nction of outp
u
t is sho
w
n in
Figure 6.
Figure 5. The
Membershi
p
Functio
n
of Input
"
e
"
and
"
ec
"
Figure 6. The
Membershi
p
Functio
n
of O
u
tput
"
U
"
3.3.2. Fuzzy
Kno
w
l
e
dge
Bank
Figure 7. The
Proce
s
s of the Device Divi
ng
The fuzzy kn
owle
dge b
a
n
k
incl
ude
s d
a
taba
se an
d
rule ba
se.
The data
b
a
s
e mainly
inclu
d
e
s
the
membe
r
ship
function
of
langu
age
va
riable a
nd tra
n
sform facto
r
etc. The
rul
e
basein
c
lude
s a seri
es of
control rul
e
s
whi
c
h re
presented by lan
guag
e variab
les. In the fuzzy
control p
r
o
c
e
ss, th
e
cont
ro
l rule
is the
core
of
fu
zzy controlle
r, whi
c
h dire
ctly aff
e
cts the
co
ntrol
perfo
rman
ce
of
the control system.Th
e
d
e
sig
n
p
r
in
cipl
e of fu
zzy
co
ntrol
rule
s i
s
t
he dyn
a
mic a
nd
static
re
spo
n
s
e of th
e sy
stem outp
u
t is
the be
st.
Wh
en the
error i
s
la
rge, it sh
ould to eli
m
in
ate
the erroras
soon a
s
po
ssi
b
le; whe
n
th
e error i
s
sm
all, the sele
ction of input
mainly to avoid
overshoot.Th
e
fuzzy control rule
s ca
n be writt
en in
the form of the followin
g
statement :
IF E
A
AND
E
C
B
TH
E
N
U
C
. As shown in Figure 7, it is t
he expected process of marine sin
k
-
float safety d
e
vice divin
g
to a certai
n d
epth.
At the begin
n
ing
of diving (n
ea
r the poi
nt a), t
h
e
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TELKOM
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ISSN:
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Optim
a
l Asymm
e
tric S-sh
ape Accele
rat
i
on/De
cel
e
rati
on for Multi-a
x
ial… (Ch
ang
-ya
n
Ch
ou
)
4791
depth deviati
on is p
o
sitive
big and th
e rate of depth
cha
nge i
s
ve
ry small, it is nece
s
sa
ry fully-
open the valu
e to eliminate
the deviation
.So we ca
n concl
udeth
a
t the rul
e
nea
r the point "a"is:If
("e" is PB)
an
d ("e
c
" i
s
Z
O
or PS) then
("
U" is
FO
). Ne
ar the
poi
nt "b", the de
pth
deviation "e" i
s
very small an
d the "ec" is bigge
r, theref
ore,
it need
s a signal to prevent
oversh
oot and sh
ock of
the sy
stem
at the m
o
ment.
Therefore,
th
e rul
e
n
e
a
r
p
o
int “b
” i
s
: If ("e" is PS
) a
n
d
("e
c
"is PB)t
hen
("U" isSO
). Similarly, we ca
n con
c
lu
de th
e other
control rule
s.
3.3.3. Decisi
on Making
The
co
re
of fuzzy control is de
ci
sio
n
ma
king,
which
in
clude
s “on
-
lin
e
cal
c
ulatio
n”
method
and
“che
ck the
table” met
hod.In a
c
tu
a
l
co
ntrol
proce
s
s, the f
u
zzy qua
ntity is
transfo
rme
d
into clea
r qua
ntity, and the
n
the cl
ear q
uantity in the domain is transfo
rme
d
into
pra
c
tical
cont
rol varia
b
le. The fuzzy cont
rol rul
e
s a
r
e shown in Tabl
e 1.
Table 1. Fu
zzy Control Rul
e
s
3.3.4. Defu
zzification
The fuzzy su
bset i
s
obtain
ed thro
ugh fu
zzy infe
ren
c
e
need tran
slat
e into preci
s
i
on value
by defuzzificaton, in orde
r to get the final cont
rol
o
u
tput. Defu
zzification i
s
ba
sed
on the fu
zzy
relation
R =
A * B * C (A is depth
devia
tion
"
e
"
, B is ra
te of depth chang
e
"ec"
) to co
mpute th
e
control output
for each
com
b
ination of in
put. The com
m
on metho
d
of defuzzificat
i
on is maximu
m
membe
r
ship
degree
meth
od a
nd
ce
ntroid meth
od.
Gene
rally, th
e centroi
d
m
e
thod i
s
th
e
better
method
rathe
r
than oth
e
rs
and it ca
n be
cal
c
ulat
ed
b
y
the formula.
We u
s
e the
centroid meth
od
to defuzzificat
on, tran
slatin
g fuzzy qu
ant
ity into precisi
on value.
3.4. The Desi
gn of An
ti-ja
mming Diffe
rentia
tor
In this control
system, we
use
t
w
o-dime
nsio
nal fuzzy
controlle
r.
Th
e depth d
e
via
t
ion
"
e
"
and depth g
r
adie
n
t
"ec"
serv
e as the inp
u
t variable
s
of the fuzzy control, but
the
"
ec
"
is
differential
si
gnal. The
r
efo
r
e, it is ne
ce
ssary to
add
the differenti
a
tor to the controlle
r. Du
e to
differential
si
gnal
s processed by
comm
on differe
nt
iator will p
r
o
d
u
c
e burr an
d a
ppea
r di
storti
on,
we
use
the
re
al optimal
co
ntrol
synthe
si
s fun
c
ti
on, n
a
m
ed fun
c
tion
fsun(), to
achi
eve differe
ntial
sign
al. By the
way, it can improve the
control efficie
n
c
y of fuzzy co
ntrolle
r.
For a second
orde
r di
spe
r
sed syste
m
:
1
1
01
0
,
|
|
.
(1)
The optimal
control synth
e
si
s
function
of discrete system
f sunx
k
,
x
k
,
r
,
h
[12,
13] is:
′
1
1
8
|
|
′
i
x
′
ix
′
f sun
rsat
,
,
|
|
f
s
un
rs
at
1
1
,
1
,
|
|
.
(
2
)
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ISSN: 23
02-4
046
TELKOM
NI
KA
Vol. 12, No. 6, June 20
14: 4787 – 4
793
4792
Based on th
e optimal control synth
e
s
is fun
c
tion:
f sunx
k
,
x
k
,
r ,
h
, we c
a
n
establi
s
h the
discrete o
p
tica
l feedba
ck system as follo
ws:
1
1
,
|
|
f s
f sun
,
,
,
.
(
3
)
Anti-jammin
g
differentiato
r is a b
e
tter di
fferentiato
r which can
achi
eve very good
differential
si
gnal by elimi
nating the
external
di
stu
r
b
ances and p
r
ovide
the re
alize
d
dynam
ic
perfo
rman
ce i
ndex of clo
s
e
d
-loo
p syste
m
.
4. The Simulation of the
Con
t
rol Sy
st
em
The
simulatio
n
mod
e
l of t
he fuzzy
con
t
roller [1
4] e
s
tablish
ed by
MATLAB/Simulink i
s
sho
w
n
in
Fig
u
re
8. T
he A
J
D m
odul
e i
s
accompli
sh
ed
by S-fu
nctio
n
of a
n
ti-jammi
ng diffe
rentiat
o
r
and the S-fun
c
tion written in C lang
uag
e
.
Figure 8. The
Simulation Model
of the Fu
zzy Controll
er
At beginni
ng
of the
sin
k
-fl
oat safety de
vice
w
ant to
dive, the d
e
vice
at the
su
rface
of
oce
an, gene
rally, we set the stetted de
pt
h is 4.5m,
so the initial deviation (
"
e
"
) is 4.5m. The
expecte
d sim
u
lation re
sult
of the device
diving is sho
w
n in Figu
re
9.
Figure 9. The
Curve of De
pth Variation
5. Conclusio
n
This pa
per i
n
trodu
ce a
marin
e
sin
k
-f
loat safety device aim
s
a
t
the field of marine
engin
eeri
ng
equipm
ent a
nd de
sign a
control sy
ste
m
for the de
vice thro
ugh
using the fu
zzy
control meth
od. The con
t
rol system
can
cont
rol the mari
ne safety device
carried m
a
rine
equipm
ent re
ach
a certain
depth to av
oid ha
rsh
se
a enviro
n
me
nt automatically, ensu
r
ing
the
norm
a
l wo
rk
of the marine
equipme
n
t. As a re
sul
t, the co
ntrol sy
stem could resp
on
se fast
and
operate stabl
y
as well
a
s
cost-effe
ctive.
Comp
ari
ng
with manu
al co
ntrol, the
co
ntrol
system
ca
n
redu
ce the
workl
oad of
staff and impro
v
e the det
ect
i
on accu
ra
cy. Absolutely, the syste
m
n
o
t
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
2302-4
046
Optim
a
l Asymm
e
tric S-sh
ape Accele
rat
i
on/De
cel
e
rati
on for Multi-a
x
ial… (Ch
ang
-ya
n
Ch
ou
)
4793
only can u
s
e
d
in marine
safety device
but also
ca
n use
d
in small subm
ari
nes, amp
h
ibi
ous
robot
s as
well
as othe
r are
a
s of the mari
ne engi
nee
rin
g
equipm
ent.
Referen
ces
[1]
W
u
Z
i
y
u
e, Z
h
ang S
h
u
a
i, Gao tin
g
, Qi ji
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.
Desig
n
of th
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s
t
em and
Res
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of the
H
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dromec
ha
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cs Base
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n
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all M
a
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qui
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h
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ang
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chnol
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hu T
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zz
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u
q
i
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i
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h
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