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e
an
ap
p
r
o
p
r
iate
p
er
f
o
r
m
an
ce
d
u
r
in
g
v
o
ltag
e
f
la
s
h
a
n
d
to
b
e
ab
le
to
d
ec
r
ea
s
e
th
e
s
e
n
s
it
iv
e
l
o
ad
v
o
ltag
e
T
HD,
a
t
w
o
-
o
b
j
ec
tiv
e
o
p
ti
m
izatio
n
h
a
s
b
ee
n
p
r
o
p
o
s
ed
in
th
is
p
ap
er
.
Hen
ce
,
in
t
h
is
m
et
h
o
d
,
v
o
ltag
e
s
a
g
w
ill
b
e
th
e
f
ir
s
t o
b
j
ec
tiv
e
an
d
v
o
lta
g
e
T
HD
w
i
ll b
e
co
n
s
id
er
ed
as th
e
s
e
co
n
d
o
b
j
ec
tiv
e
in
ST
A
T
C
OM
co
n
tr
o
l s
y
s
te
m
.
T
h
e
tu
n
in
g
o
f
f
u
zz
y
co
n
tr
o
ll
er
is
a
h
e
u
r
is
tic
w
o
r
k
.
T
o
elim
i
n
ate
s
u
c
h
p
r
o
b
le
m
s
t
h
e
e
v
o
lu
tio
n
ar
y
tech
n
iq
u
es
h
av
e
b
ee
n
ap
p
lied
in
s
o
lv
in
g
th
e
t
u
n
in
g
o
f
F
L
C
p
ar
am
eter
s
.
T
h
e
Gen
etic
A
l
g
o
r
ith
m
,
An
t
C
o
lo
n
y
Op
ti
m
izatio
n
a
n
d
G
A
w
h
ic
h
ar
e
th
e
f
o
r
m
s
o
f
p
r
o
b
ab
ilis
tic
h
eu
r
i
s
tic
al
g
o
r
ith
m
th
at
h
a
v
e
b
ee
n
s
u
cc
es
s
f
u
ll
y
u
s
ed
i
n
o
p
ti
m
iza
tio
n
o
f
F
u
zz
y
lo
g
ic
co
n
tr
o
ller
.
T
h
e
G
A
m
et
h
o
d
is
u
s
u
all
y
f
aster
b
ec
au
s
e
t
h
e
G
A
h
as
p
ar
allel
s
ea
r
ch
tech
n
iq
u
es
w
h
ic
h
e
m
u
l
at
e
n
atu
r
al
g
e
n
etics o
p
er
atio
n
s
.
T
h
e
GA
(
G
A
)
h
as
b
ee
n
ap
p
lied
to
o
p
tim
izatio
n
o
f
F
L
C
.
I
n
r
ec
en
t
y
ea
r
s
G
A
h
a
s
g
ai
n
ed
m
u
ch
p
o
p
u
lar
it
y
in
d
i
f
f
er
en
t
k
i
n
d
s
o
f
ap
p
licatio
n
s
b
ec
a
u
s
e
o
f
its
s
i
m
p
licit
y
,
ea
s
y
i
m
p
le
m
e
n
tat
io
n
an
d
r
eliab
le
co
n
v
er
g
e
n
ce
.
I
t
h
as
b
ee
n
f
o
u
n
d
to
b
e
r
o
b
u
s
t
in
s
o
l
v
in
g
co
n
ti
n
u
o
u
s
n
o
n
-
li
n
ea
r
o
p
ti
m
iza
t
io
n
p
r
o
b
lem
s
.
B
o
th
v
o
ltag
e
s
ag
a
n
d
T
HD
ca
n
b
e
m
o
d
i
f
ied
b
y
t
h
e
af
o
r
esaid
al
g
o
r
ith
m
.
On
t
h
e
o
t
h
er
h
an
d
,
to
in
v
e
s
tig
a
te
t
h
e
e
f
f
icie
n
c
y
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
;
p
er
f
o
r
m
an
ce
o
f
ST
A
T
C
OM
co
m
p
e
n
s
ato
r
d
u
r
i
n
g
v
ar
io
u
s
f
a
u
lt
s
i
n
a
t
y
p
ical
n
et
w
o
r
k
h
a
s
b
ee
n
te
s
ted
a
n
d
c
o
m
p
ar
ed
w
i
th
s
o
m
e
co
n
tr
o
ller
s
th
at
w
er
e
in
tr
o
d
u
ce
d
b
ef
o
r
e.
ST
A
T
C
OM
o
p
e
r
atio
n
,
m
u
lti
-
o
b
j
ec
tiv
e
o
p
ti
m
izatio
n
w
it
h
f
u
zz
y
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
,
an
d
G
A
alg
o
r
ith
m
h
a
v
e
b
ee
n
i
n
tr
o
d
u
c
ed
an
d
d
is
cu
s
s
ed
i
n
t
h
e
f
o
llo
win
g
s
ec
tio
n
s
.
A
f
ter
th
at,
w
e
h
av
e
in
tr
o
d
u
ce
d
t
h
e
p
r
o
p
o
s
ed
m
e
th
o
d
o
f
t
h
e
p
ap
er
,
an
d
th
e
f
in
a
l
s
ec
tio
n
co
n
t
ain
s
t
h
e
s
i
m
u
lat
io
n
r
esu
lt
s
.
2.
B
ASI
C
CO
NC
E
P
T
S O
F
S
T
AT
CO
M
A
ST
A
T
C
OM
i
s
a
s
o
lid
s
tate
p
o
w
er
elec
tr
o
n
ics
s
w
i
tch
in
g
d
ev
ice
co
n
s
i
s
ti
n
g
o
f
eith
er
M
OSFET
o
r
I
GB
T
,
a
ca
p
ac
ito
r
b
an
k
as a
n
en
er
g
y
s
to
r
a
g
e
d
ev
ice
a
n
d
i
n
j
ec
tio
n
tr
an
s
f
o
r
m
er
s
.
I
t i
s
li
n
k
ed
in
s
h
u
n
t
b
et
w
ee
n
a
d
is
tr
ib
u
tio
n
s
y
s
te
m
a
n
d
a
lo
ad
th
at
s
h
o
w
n
i
n
Fi
g
u
r
e
1
.
T
h
e
b
asic
id
ea
o
f
t
h
e
ST
A
T
C
OM
i
s
to
i
n
j
ec
t
a
co
n
tr
o
lled
v
o
ltag
e
g
en
er
ated
b
y
a
f
o
r
ce
d
co
m
m
u
ted
co
n
v
er
t
er
in
a
p
ar
allel
to
th
e
b
u
s
v
o
lt
ag
e
b
y
m
ea
n
s
o
f
a
n
in
j
ec
tin
g
tr
an
s
f
o
r
m
er
.
A
t
n
o
r
m
al
o
p
er
atin
g
co
n
d
itio
n
,
t
h
e
ST
A
T
C
OM
in
j
ec
ts
o
n
l
y
a
s
m
al
l
v
o
lta
g
e
to
co
m
p
e
n
s
ate
f
o
r
th
e
v
o
ltag
e
d
r
o
p
o
f
th
e
in
j
ec
tio
n
tr
an
s
f
o
r
m
e
r
an
d
d
ev
ice
lo
s
s
es.
Ho
w
e
v
er
,
w
h
e
n
v
o
lta
g
e
s
a
g
o
cc
u
r
s
i
n
t
h
e
d
is
tr
ib
u
tio
n
s
y
s
te
m
,
th
e
ST
A
T
C
OM
co
n
tr
o
l
s
y
s
te
m
ca
lc
u
late
s
a
n
d
s
y
n
t
h
esize
s
t
h
e
v
o
ltag
e
r
eq
u
ir
ed
to
p
r
eser
v
e
o
u
tp
u
t
v
o
ltag
e
to
th
e
lo
ad
b
y
i
n
j
ec
tin
g
a
co
n
tr
o
lled
v
o
ltag
e
w
it
h
a
ce
r
t
ain
m
ag
n
it
u
d
e
an
d
p
h
ase
an
g
le
i
n
to
th
e
d
i
s
tr
ib
u
ti
o
n
s
y
s
te
m
to
th
e
cr
itical
lo
ad
.
Fig
u
r
e
1
.
P
r
o
p
o
s
ed
S
T
A
T
C
OM
co
n
tr
o
l i
m
p
le
m
e
n
tat
io
n
3.
G
A
A
L
G
O
R
I
T
H
M
Gen
etic
alg
o
r
it
h
m
s
[5
]
-
[
6
]
,
w
h
ic
h
ar
e
ad
o
p
ted
f
r
o
m
th
e
p
r
in
cip
le
o
f
b
io
l
o
g
ical
ev
o
lu
tio
n
,
ar
e
ef
f
icien
t
s
ea
r
c
h
tech
n
iq
u
es
t
h
at
m
a
n
ip
u
la
te
th
e
co
d
in
g
r
ep
r
esen
ti
n
g
a
p
ar
a
m
eter
s
et
to
r
ea
ch
a
n
ea
r
o
p
ti
m
al
s
o
lu
tio
n
.
He
n
ce
b
y
s
tr
en
g
t
h
en
i
n
g
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
s
w
it
h
g
en
et
ic
al
g
o
r
ith
m
s
th
e
s
ea
r
c
h
in
g
a
n
d
attai
n
m
e
n
t
o
f
o
p
ti
m
al
f
u
zz
y
lo
g
ic
r
u
les
an
d
h
i
g
h
-
p
er
f
o
r
m
a
n
ce
m
e
m
b
e
r
s
h
ip
f
u
n
ctio
n
s
w
ill
b
e
ea
s
ier
an
d
f
aster
.
G
As
is
u
s
ed
r
eg
u
lar
l
y
to
s
o
lv
e
d
i
f
f
ic
u
lt
s
ea
r
c
h
,
o
p
ti
m
izat
io
n
a
n
d
m
ac
h
in
e
-
lear
n
in
g
p
r
o
b
le
m
s
t
h
at
h
av
e
p
r
ev
io
u
s
l
y
r
esis
ted
au
to
m
ated
s
o
lu
tio
n
s
.
T
h
ey
ca
n
b
e
u
s
ed
to
s
o
lv
e
d
if
f
ic
u
lt
p
r
o
b
le
m
s
q
u
ic
k
l
y
an
d
r
eliab
l
y
.
T
h
ese
alg
o
r
ith
m
s
ar
e
ea
s
y
to
i
n
ter
f
a
ce
w
it
h
e
x
is
ti
n
g
s
i
m
u
la
tio
n
s
a
n
d
m
o
d
els,
an
d
th
e
y
ar
e
ea
s
y
to
h
y
b
r
id
ize.
G
A
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
-
8
694
A
F
u
z
z
y
GA
B
a
s
ed
S
ta
tco
m
fo
r
P
o
w
er Qu
a
lity I
mp
r
o
ve
men
t (
S
.
Dee
p
a
)
485
in
cl
u
d
es
t
h
r
ee
m
aj
o
r
o
p
er
ato
r
s
:
s
elec
tio
n
,
cr
o
s
s
o
v
er
,
an
d
m
u
tatio
n
,
i
n
ad
d
itio
n
to
f
o
u
r
co
n
tr
o
l
p
ar
am
eter
s
:
p
o
p
u
latio
n
s
ize,
s
elec
tio
n
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
r
ate.
T
h
is
p
ap
er
is
co
n
ce
r
n
ed
p
r
im
ar
il
y
w
it
h
th
e
s
elec
tio
n
an
d
m
u
tatio
n
o
p
er
ato
r
s
.
T
h
er
e
ar
e
th
r
ee
m
ai
n
s
ta
g
es
o
f
a
g
e
n
etic
al
g
o
r
ith
m
;
th
e
s
e
ar
e
k
n
o
w
n
as
r
ep
r
o
d
u
ctio
n
,
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
.
T
h
e
s
tep
s
in
v
o
l
v
ed
in
g
en
e
tic
alg
o
r
ith
m
ar
e
d
escr
ib
ed
b
elo
w
.
1.
Star
t
:
Gen
er
ate
r
an
d
o
m
p
o
p
u
l
atio
n
o
f
n
c
h
r
o
m
o
s
o
m
es (
s
u
ita
b
le
s
o
lu
tio
n
s
f
o
r
th
e
p
r
o
b
le
m
)
.
2.
Fit
n
e
s
s
: E
v
al
u
ate
th
e
f
it
n
es
s
f
(
x
)
o
f
ea
ch
c
h
r
o
m
o
s
o
m
e
x
i
n
th
e
p
o
p
u
latio
n
.
3.
Ne
w
p
o
p
u
latio
n
:
C
r
ea
te
a
n
e
w
p
o
p
u
lat
io
n
b
y
r
ep
ea
tin
g
f
o
llo
w
i
n
g
s
tep
s
u
n
til
th
e
n
e
w
p
o
p
u
latio
n
i
s
co
m
p
lete.
a.
Selectio
n
:
Select
t
w
o
p
ar
en
t
ch
r
o
m
o
s
o
m
e
s
f
r
o
m
a
p
o
p
u
lat
io
n
ac
co
r
d
in
g
to
t
h
eir
f
itn
e
s
s
(
th
e
b
etter
f
it
n
es
s
,
th
e
b
ig
g
er
ch
a
n
ce
to
b
e
s
elec
t
ed
)
.
b.
C
r
o
s
s
o
v
er
:
W
it
h
a
cr
o
s
s
o
v
er
p
r
o
b
a
b
ilit
y
,
cr
o
s
s
o
v
er
th
e
p
ar
en
ts
to
f
o
r
m
n
e
w
o
f
f
s
p
r
i
n
g
(
ch
ild
r
en
)
.
I
f
n
o
cr
o
s
s
o
v
er
w
as p
er
f
o
r
m
ed
,
o
f
f
s
p
r
in
g
is
t
h
e
ex
ac
t c
o
p
y
o
f
p
ar
en
ts
.
c.
Mu
tatio
n
:
W
it
h
a
m
u
ta
tio
n
p
r
o
b
ab
ilit
y
,
m
u
tate
n
e
w
o
f
f
s
p
r
in
g
at
ea
ch
lo
cu
s
(
p
o
s
itio
n
in
ch
r
o
m
o
s
o
m
e)
.
4.
A
cc
ep
ti
n
g
:
P
lace
n
e
w
o
f
f
s
p
r
in
g
in
t
h
e
n
e
w
p
o
p
u
lat
io
n
.
5.
R
ep
lace
:
Use n
e
w
g
e
n
er
ated
p
o
p
u
latio
n
f
o
r
a
f
u
r
th
er
r
u
n
o
f
t
h
e
alg
o
r
it
h
m
6.
T
est
:
I
f
th
e
en
d
co
n
d
itio
n
i
s
s
a
tis
f
ied
,
s
to
p
,
an
d
r
etu
r
n
th
e
b
e
s
t so
lu
tio
n
i
n
cu
r
r
en
t p
o
p
u
latio
n
.
7.
L
o
o
p
:
Go
to
s
tep
2
.
4.
O
B
J
E
CT
I
V
E
F
UNC
T
I
O
NS
T
h
e
m
ai
n
o
b
j
ec
tiv
e
o
f
co
n
tr
o
ll
er
is
as f
o
llo
w
s
4
.
1
.
M
ini
m
iza
t
io
n o
f
Av
er
a
g
e
V
o
lt
a
g
e
Dev
ia
t
io
n
T
h
e
v
o
ltag
e
d
ev
iatio
n
i
n
d
ex
i
s
d
ef
in
ed
as
th
e
d
ev
ia
tio
n
o
f
t
h
e
v
o
lta
g
e
m
a
g
n
i
tu
d
e
o
f
b
u
s
i
f
r
o
m
th
e
u
n
i
t
y
a
s
w
h
er
e
V
i
-
r
ef
a
n
d
V
i
ar
e
th
e
r
ef
er
en
ce
a
n
d
ac
tu
al
v
o
lt
ag
es a
t
2
)
(
i
re
f
i
i
d
e
v
V
V
V
(
1
)
b
u
s
i
,
r
esp
ec
tiv
el
y
.
T
h
er
ef
o
r
e,
th
e
av
er
ag
e
v
o
ltag
e
d
ev
iatio
n
in
t
h
e
s
y
s
te
m
p
er
u
n
it
(
p
.
u
.
)
ca
n
b
e
ex
p
r
ess
ed
u
s
i
n
g
th
e
s
u
m
m
atio
n
o
f
n
o
r
m
a
lized
V
dev
-
i
i
f
o
r
all
b
u
s
e
s
g
i
v
e
n
b
y
M
V
V
f
m
i
n
o
r
m
i
d
e
v
a
v
r
d
e
v
i
1
(
2
)
w
h
er
e
M
is
t
h
e
to
tal
n
u
m
b
er
o
f
s
y
s
te
m
b
u
s
es.
4
.
2
.
M
ini
m
iza
t
io
n o
f
Av
er
a
g
e
V
o
lt
a
g
e
T
o
t
a
l H
a
r
m
o
nic D
is
t
o
r
t
io
n
(
T
H
D
V
)
T
h
e
av
er
ag
e
o
f
t
h
e
n
o
r
m
alize
d
T
HD
V
in
th
e
s
y
s
te
m
b
u
s
e
s
to
co
n
tr
o
l
th
e
T
HD
V
le
v
el
o
f
th
e
w
h
o
le
s
y
s
te
m
i
s
o
b
tain
ed
u
s
in
g
M
T
H
D
T
H
D
f
m
i
n
o
r
m
i
v
a
v
r
v
1
2
(
3
)
W
h
er
e
n
o
r
m
i
v
T
H
D
I
is
th
e
n
o
r
m
a
lized
T
H
D
v
i
n
b
u
s
i.
4
.
3
.
B
us
Vo
lt
a
g
e
L
i
m
it
s
E
ac
h
b
u
s
v
o
ltag
e
V
i
m
u
s
t
b
e
m
ai
n
tai
n
ed
ar
o
u
n
d
a
p
er
m
is
s
i
b
le
v
o
ltag
e
b
an
d
o
w
in
g
to
th
e
ef
f
ec
t
o
f
D
-
ST
A
T
C
OM
in
s
ta
llatio
n
o
n
s
y
s
te
m
b
u
s
v
o
lta
g
es.
T
h
is
is
ac
h
ie
v
ed
u
s
i
n
g
m
a
x
m
i
n
i
i
i
V
V
V
(
4
)
w
h
er
e
V
i
is
t
h
e
v
o
lta
g
e
at
b
u
s
i
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
IJ
PEDS
Vo
l.
8
,
No
.
1
,
Ma
r
ch
2
0
1
7
:
4
8
3
–
4
91
486
T
h
e
o
v
er
all
o
p
tim
al
ST
A
T
C
OM
p
r
o
b
lem
ca
n
b
e
co
n
f
i
g
u
r
ed
as
a
co
n
s
tr
ai
n
ed
m
u
lti
-
o
b
j
ec
tiv
e
o
p
tim
izatio
n
p
r
o
b
le
m
.
T
h
er
ef
o
r
e,
th
e
w
ei
g
h
ted
s
u
m
m
et
h
o
d
is
co
n
s
id
er
ed
in
t
h
e
cu
r
r
en
t
s
t
u
d
y
to
co
m
b
i
n
e
th
e
in
d
iv
id
u
al
o
b
j
ec
tiv
e
f
u
n
ctio
n
s
in
ter
m
s
o
f
a
s
i
n
g
le
o
b
j
ec
tiv
e
f
u
n
ctio
n
.
E
ac
h
co
n
s
tr
ain
t
v
io
latio
n
is
also
in
co
r
p
o
r
ated
in
th
e
o
v
er
all
o
b
j
ec
tiv
e
f
u
n
ctio
n
u
s
in
g
th
e
p
en
alt
y
f
u
n
c
tio
n
ap
p
r
o
ac
h
.
T
h
e
f
in
al
o
b
j
ec
tiv
e
f
u
n
ctio
n
to
b
e
m
in
i
m
ized
is
ex
p
r
ess
ed
as
)
0
,
m
a
x
(
)
0
,
[
m
a
x
(
m
a
x
m
a
x
2
2
1
1
i
i
m
i
i
i
V
V
V
V
f
w
f
w
F
(
5)
w
h
er
e
w
i
an
d
λ
ar
e
t
h
e
r
elati
v
e
f
ix
ed
w
eig
h
t
f
ac
to
r
s
a
s
s
i
g
n
ed
to
th
e
i
n
d
iv
id
u
a
l
o
b
j
ec
tiv
es
an
d
t
h
e
p
e
n
alt
y
m
u
ltip
lier
s
f
o
r
v
io
lated
co
n
s
tr
ain
ts
,
r
esp
ec
tiv
e
l
y
,
a
n
d
ar
e
lar
g
e,
f
ix
ed
s
ca
lar
n
u
m
b
er
s
.
I
n
a
d
d
itio
n
,
P
an
d
M
ar
e
th
e
to
tal
ST
A
T
C
OM
n
u
m
b
er
an
d
th
e
to
tal
b
u
s
n
u
m
b
er
,
r
esp
ec
tiv
el
y
.
T
h
e
w
e
ig
h
t
f
ac
to
r
s
s
h
o
u
ld
b
e
ass
ig
n
ed
to
th
e
in
d
iv
id
u
al
o
b
j
ec
tiv
e
f
u
n
ctio
n
s
b
ased
o
n
th
eir
i
m
p
o
r
tan
ce
.
T
h
ese
m
a
y
v
ar
y
b
ased
o
n
t
h
e
d
esire
d
p
r
ef
er
e
n
ce
s
o
f
th
e
p
o
w
er
s
y
s
te
m
o
p
er
ato
r
s
.
I
n
t
h
is
p
ap
er
,
th
e
p
r
o
p
er
w
ei
g
h
ti
n
g
f
ac
to
r
s
u
s
ed
ar
e
w
1
=
w
2
=
0
.
4
in
w
h
ic
h
t
h
e
f
ir
s
t
t
w
o
o
b
j
ec
tiv
es
ar
e
as
s
u
m
ed
to
b
e
eq
u
all
y
m
o
r
e
i
m
p
o
r
tan
t.
5.
VO
L
T
A
G
E
SA
G
D
E
T
E
C
T
I
O
N
T
h
e
ess
en
tial
p
ar
t
f
o
r
w
ell
-
p
er
f
o
r
m
an
ce
o
f
co
n
tr
o
ller
in
ST
A
T
C
OM
is
th
e
s
ag
d
etec
t
io
n
cir
cu
it.
Vo
ltag
e
s
ag
m
u
s
t
b
e
d
etec
te
d
f
ast
an
d
co
r
r
ec
ted
w
ith
a
m
i
n
i
m
u
m
o
f
f
alse
o
p
er
atio
n
s
.
T
h
e
v
o
ltag
e
s
a
g
d
etec
tio
n
m
et
h
o
d
is
b
ased
o
n
R
o
o
t
Me
a
n
s
Sq
u
ar
e
(
R
MS
)
o
f
th
e
e
r
r
o
r
v
ec
to
r
w
h
ic
h
allo
w
s
d
etec
tio
n
o
f
s
y
m
m
etr
ical
a
n
d
as
y
m
m
e
tr
ical
s
ag
s
,
as
w
ell
a
s
t
h
e
as
s
o
ciate
d
p
h
ase
j
u
m
p
.
T
h
e
co
n
tr
o
ller
s
y
s
te
m
is
p
r
ese
n
ted
in
F
ig
u
r
e
2
.
T
h
e
th
r
ee
-
p
h
ase
s
u
p
p
l
y
v
o
ltag
e
is
tr
a
n
s
f
o
r
m
ed
f
r
o
m
ab
c
to
o
d
q
f
r
a
m
e
u
s
i
n
g
P
ar
k
tr
an
s
f
o
r
m
atio
n
.
Ph
ase
L
o
c
k
ed
L
o
o
p
(
P
L
L
)
is
u
s
ed
to
tr
ac
k
s
u
p
p
l
y
v
o
lta
g
e
p
h
ase.
Fig
u
r
e
2
.
C
o
n
tr
o
l Str
u
ct
u
r
e
o
f
DVR
T
h
e
p
ar
k
tr
an
s
f
o
r
m
at
io
n
m
atr
i
x
is
s
h
o
w
n
a
s
f
o
llo
w
s
:
)
(
3
1
c
b
a
o
V
V
V
V
(
6
)
)
3
4
c
o
s
(
)
3
2
c
o
s
(
)
c
o
s
(
3
2
c
b
a
d
V
V
V
V
(
7
)
)
3
4
s
i
n
(
)
3
2
s
i
n
(
)
s
i
n
(
3
2
c
b
a
q
V
V
V
V
(
8
)
)
2
2
q
d
s
V
V
V
(
9
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
-
8
694
A
F
u
z
z
y
GA
B
a
s
ed
S
ta
tco
m
fo
r
P
o
w
er Qu
a
lity I
mp
r
o
ve
men
t (
S
.
Dee
p
a
)
487
C
lo
s
ed
lo
o
p
lo
ad
v
o
lta
g
e
f
e
ed
b
ac
k
is
ad
d
ed
,
an
d
is
i
m
p
le
m
e
n
ted
i
n
t
h
e
o
d
q
f
r
a
m
e
i
n
o
r
d
er
to
m
i
n
i
m
ize
an
y
s
tead
y
-
s
ta
te
er
r
o
r
in
th
e
f
u
n
d
a
m
en
tal
co
m
p
o
n
en
t.
W
h
e
n
t
h
e
g
r
id
v
o
lta
g
e
is
n
o
r
m
al,
t
h
e
ST
A
T
C
OM
s
y
s
te
m
is
h
eld
i
n
a
n
u
ll
s
tate
to
lo
w
er
it
s
lo
s
s
e
s
.
W
h
en
v
o
lta
g
e
s
a
g
is
d
etec
t
ed
,
th
e
ST
A
T
C
OM
s
w
itc
h
es
in
to
ac
tiv
e
m
o
d
e
to
r
ea
ct
a
s
f
ast
as
p
o
s
s
ib
le
to
in
j
ec
t
th
e
r
eq
u
ir
ed
ac
v
o
ltag
e.
T
h
e
in
j
ec
tio
n
v
o
lta
g
e
is
also
g
e
n
er
ated
ac
co
r
d
in
g
to
t
h
e
d
if
f
er
en
ce
b
et
w
ee
n
th
e
r
ef
er
en
ce
lo
ad
v
o
ltag
e
an
d
th
e
s
u
p
p
ly
v
o
ltag
e
an
d
i
t
i
s
ap
p
lied
to
th
e
co
n
v
er
ter
to
p
r
o
d
u
ce
th
e
p
r
ef
er
r
ed
v
o
ltag
e,
u
s
i
n
g
t
h
e
Vo
ltag
e
C
o
n
tr
o
l
b
ased
o
n
P
SO
-
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
.
B
y
n
o
tice
to
s
ta
n
d
ar
d
GA
a
l
g
o
r
ith
m
,
it
ca
n
b
e
f
i
n
d
o
u
t
t
h
e
ef
f
ec
t
o
f
p
o
p
u
latio
n
n
u
m
b
e
r
o
v
er
th
is
alg
o
r
ith
m
.
O
n
t
h
e
o
th
er
w
o
r
d
,
lo
w
n
u
m
b
er
s
o
f
p
o
p
u
latio
n
is
ca
u
s
ed
to
s
tic
k
i
n
lo
ca
l
o
p
ti
m
u
m
an
d
i
f
h
i
g
h
n
u
m
b
er
s
o
f
p
o
p
u
latio
n
i
s
ca
u
s
ed
to
d
ec
lin
e
alg
o
r
ith
m
v
e
lo
cit
y
.
T
h
er
ef
o
r
e
s
tan
d
ar
d
GA
alg
o
r
ith
m
is
n
’
t
p
r
o
f
i
t
f
o
r
s
o
lv
i
n
g
m
u
lti o
b
j
ec
tiv
e
o
p
ti
m
izatio
n
p
r
o
b
lem
s
.
I
n
th
is
p
ap
er
,
p
ar
am
eter
s
o
f
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
s
u
s
ed
f
o
r
v
o
ltag
e
s
a
g
an
d
v
o
ltag
e
T
HD
ar
e
d
eter
m
in
ed
b
y
G
A
.
T
h
ese
p
ar
a
m
eter
s
ar
e
i
n
p
u
t
a
n
d
o
u
t
p
u
t
s
ca
li
n
g
f
ac
to
r
s
,
in
p
u
t
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
p
ar
am
eter
s
an
d
co
ef
f
icien
ts
o
f
lin
ea
r
o
u
tp
u
t
f
u
n
ct
io
n
s
.
GA
iter
atio
n
s
ar
e
p
er
f
o
r
m
ed
b
y
t
h
e
MA
T
L
A
B
co
m
m
a
n
d
s
i
n
an
M
-
Fi
le.
T
h
e
MA
T
L
A
B
co
m
m
a
n
d
s
in
M
-
F
i
le
ar
e
as
s
h
o
w
n
i
n
F
ig
u
r
e
3
.
Fig
u
r
e
3.
MA
T
L
A
B
co
m
m
an
d
s
in
M
-
f
ile
T
h
e
tu
n
i
n
g
p
r
o
ce
s
s
o
f
F
L
C
r
u
l
es b
y
G
A
is
il
lu
s
tr
ated
b
y
th
e
f
o
llo
w
i
n
g
s
tep
s
.
1.
Div
id
e
th
e
i
n
p
u
t a
n
d
o
u
tp
u
t sp
ac
es o
f
th
e
s
y
s
te
m
to
b
e
co
n
tr
o
lled
in
to
f
u
zz
y
r
eg
io
n
s
.
2.
E
n
co
d
e
th
e
in
p
u
t
-
o
u
tp
u
t r
e
g
io
n
s
i
n
to
b
it
-
s
tr
in
g
s
.
3.
Use G
A
as a
lear
n
i
n
g
p
r
o
ce
d
u
r
e
to
g
en
er
ate
a
s
et
o
f
f
u
zz
y
r
u
les.
4.
Use th
e
n
e
w
l
y
g
e
n
er
ated
f
u
zz
y
r
u
le
s
to
d
eter
m
in
e
t
h
e
p
er
f
o
r
m
an
ce
a
n
d
ass
i
g
n
a
f
i
tn
e
s
s
v
al
u
e.
5.
Ass
i
g
n
a
n
e
g
ati
v
e
v
al
u
e
to
th
e
f
it
n
es
s
f
u
n
ctio
n
i
f
t
h
er
e
an
y
p
r
o
b
lem
p
er
s
i
s
ts
.
6.
I
f
s
to
p
p
in
g
cr
iter
io
n
is
n
o
t
m
et
g
o
to
Step
3
.
7.
Dete
r
m
i
n
e
a
m
ap
p
in
g
f
r
o
m
t
h
e
i
n
p
u
t
s
p
ac
e
to
th
e
o
u
tp
u
t
s
p
ac
e
b
ased
o
n
th
e
co
m
b
in
ed
f
u
zz
y
r
u
le
b
as
e
u
s
i
n
g
a
d
e
f
u
zz
i
f
y
i
n
g
p
r
o
ce
d
u
r
e.
T
h
is
p
ap
er
p
r
esen
ts
a
q
u
ick
s
o
lu
tio
n
to
t
h
e
p
r
o
b
le
m
s
u
s
in
g
t
h
e
G
A
alg
o
r
ith
m
.
6.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
NS
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
is
e
v
a
lu
ated
f
o
r
ST
A
T
C
OM
s
y
s
te
m
to
en
h
a
n
ce
t
h
e
p
o
w
er
q
u
alit
y
i
s
s
u
e.
T
h
e
p
o
w
er
d
is
tr
ib
u
tio
n
s
y
s
te
m
ca
s
e
s
tu
d
y
co
n
s
is
t
s
o
f
t
w
o
lo
ad
b
u
s
e
s
th
a
t
o
n
e
o
f
t
h
e
m
in
cl
u
d
es
th
e
s
e
n
s
iti
v
e
lo
ad
.
T
h
is
s
i
m
p
le
elec
tr
ical
n
e
t
w
o
r
k
h
as
b
ee
n
s
h
o
w
n
in
Fi
g
u
r
e
4
an
d
its
p
ar
am
eter
s
h
a
v
e
b
ee
n
in
tr
o
d
u
ce
d
in
T
ab
le
1
.
T
h
is
p
r
o
j
ec
t h
as b
ee
n
s
i
m
u
lated
i
n
th
e
M
A
T
L
A
B
/SI
MU
L
I
NK
.
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I
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u
r
e
4
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o
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tr
ib
u
t
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te
m
s
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h
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atic
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ab
le
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ar
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eter
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me
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e
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p
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o
l
t
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g
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n
=
5
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z
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s=2
2
5
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c
t
i
v
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t
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P
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l
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0
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r
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c
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r
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t
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l
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5
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.
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e
r
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e
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r
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n
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o
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Tr
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n
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U
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w
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t
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h
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n
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r
e
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e
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y
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z
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e
r
i
e
s
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i
l
t
e
r
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mp
e
d
a
n
c
e
s
R
s=
0
.
2
(
Ω
)
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s=6
(
M
H
)
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
t
h
e
p
r
o
p
o
s
ed
Fu
zz
y
G
A
(
FG
A
)
b
ased
o
p
tim
izatio
n
i
s
ev
al
u
ated
b
y
co
m
p
ar
i
n
g
its
r
es
u
lt
s
w
it
h
co
n
v
e
n
tio
n
a
l
Fu
zz
y
lo
g
ic
co
n
tr
o
ller
an
d
G
en
etic
f
u
zz
y
co
n
tr
o
ller
.
A
lg
o
r
ith
m
b
eg
i
n
s
w
it
h
g
en
er
atio
n
o
f
in
i
tial
p
o
p
u
latio
n
th
at
co
n
ta
in
s
5
0
ch
r
o
m
o
s
o
m
es.
E
ac
h
ch
r
o
m
o
s
o
m
e
o
f
th
i
s
p
o
p
u
latio
n
is
in
t
h
e
f
o
r
m
o
f
an
ar
r
a
y
w
h
ich
co
n
s
i
s
ts
o
f
2
2
co
lu
m
n
s
.
E
ac
h
co
lu
m
n
i
n
d
icate
s
p
o
s
s
ib
le
o
p
ti
m
al
v
alu
e
o
f
co
r
r
esp
o
n
d
in
g
F
L
C
p
ar
a
m
ete
r
.
I
n
th
i
s
s
t
u
d
y
,
to
tal
er
r
o
r
is
u
s
ed
w
h
ile
s
e
lecti
n
g
b
es
t
in
d
iv
id
u
al
s
.
Fo
r
th
i
s
p
u
r
p
o
s
e,
in
th
e
M
-
f
ile,
g
en
e
r
ated
p
ar
am
eter
s
ar
e
lo
ad
ed
to
th
e
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
b
y
t
h
e
co
m
m
a
n
d
“
s
e
t_
p
ar
am
(
)
”
an
d
ST
A
T
C
O
M
cir
cu
it
is
r
u
n
i
n
a
Si
m
u
l
in
k
Md
l
-
f
ile
b
y
t
h
e
co
m
m
a
n
d
“
s
i
m
(
)
”.
D
u
r
in
g
s
i
m
u
lat
io
n
,
er
r
o
r
is
ca
lcu
late
d
an
d
to
tal
er
r
o
r
is
s
en
t
to
an
ar
r
a
y
.
T
h
is
p
r
o
ce
d
u
r
e
is
p
er
f
o
r
m
ed
f
o
r
ea
ch
ch
r
o
m
o
s
o
m
e
o
f
in
itial p
o
p
u
lat
io
n
an
d
f
i
n
all
y
a
n
ar
r
a
y
w
it
h
5
0
r
o
w
s
is
f
o
r
m
ed
.
Af
ter
th
e
p
r
o
d
u
ctio
n
o
f
in
i
tial
p
o
p
u
latio
n
an
d
ca
lcu
la
tin
g
to
t
al
er
r
o
r
f
o
r
ea
ch
ch
r
o
m
o
s
o
m
e
in
th
e
P
o
p
u
latio
n
,
GA
iter
atio
n
s
b
eg
in
.
Fin
a
ll
y
,
ST
A
T
C
OM
s
y
s
te
m
is
m
ad
e
to
r
u
n
a
g
ain
u
s
i
n
g
n
e
w
p
ar
a
m
eter
s
to
o
b
tain
n
e
w
f
it
n
e
s
s
v
al
u
es.
T
h
is
c
y
cle
ter
m
i
n
ates
w
h
e
n
p
r
ed
eter
m
in
ed
n
u
m
b
er
o
f
i
ter
atio
n
is
r
ea
c
h
ed
.
T
h
e
f
itte
s
t
ch
r
o
m
o
s
o
m
e
o
f
ea
ch
p
o
p
u
latio
n
is
s
to
r
ed
in
an
ar
r
ay
a
n
d
at
th
e
en
d
o
f
th
e
it
er
atio
n
s
th
e
f
itte
s
t
ch
r
o
m
o
s
o
m
e
o
f
all
p
o
p
u
latio
n
s
is
o
b
tain
ed
.
T
ab
le
2
r
ep
r
esen
ts
t
h
e
p
ar
a
m
eter
ch
o
s
e
n
f
o
r
i
m
p
le
m
e
n
tatio
n
o
f
GA
-
F
L
C
an
d
ta
b
le
3
r
ep
r
esen
t
s
th
e
p
ar
a
m
eter
c
h
o
s
en
f
o
r
i
m
p
le
m
en
ta
tio
n
o
f
FG
A
.
T
ab
le
2
.
P
ar
am
eter
s
c
h
o
s
en
f
o
r
GA
i
m
p
le
m
e
n
tatio
n
P
a
r
a
me
t
e
r
f
o
r
G
A
-
F
L
C
V
a
l
u
e
P
o
p
u
l
a
t
i
o
n
s
i
z
e
20
N
o
.
o
f
i
t
e
r
a
t
i
o
n
1
0
0
C
r
o
sso
v
e
r
p
r
o
b
a
b
i
l
i
t
y
0
.
9
M
u
t
a
t
i
o
n
p
r
o
b
a
b
i
l
i
t
y
0
.
1
S
e
l
e
c
t
i
o
n
R
o
u
l
e
t
t
e
w
h
e
e
l
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
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8
8
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694
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ized
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zz
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n
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o
ller
f
o
r
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e
ST
A
T
C
OM
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y
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te
m
i
s
s
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o
w
n
i
n
F
ig
u
r
e
4
.
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m
b
er
o
f
d
i
m
e
n
s
i
o
n
s
i
n
th
e
p
r
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le
m
i
s
f
o
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r
.
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h
ese
d
i
m
en
s
io
n
s
ar
e
th
e
co
ef
f
icien
ts
o
f
t
w
o
P
I
co
n
tr
o
ller
s
s
o
t
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at
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m
i
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ed
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e
d
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ax
i
s
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d
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e
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th
er
i
s
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h
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e
q
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ax
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s
.
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f
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v
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g
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n
d
v
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ltag
e
T
HD.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
-
8
694
A
F
u
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491
RE
F
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NC
E
S
[1
]
P.
K.
Na
n
d
a
n
a
n
d
P
.
C.
S
e
n
,
“
A
c
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y
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f
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I
P
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n
tro
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o
r
d
c
m
o
to
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d
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s
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ter
n
a
ti
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n
a
l
J
o
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f
c
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n
tro
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o
l.
4
4
,
pp
.
2
8
3
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2
9
7
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1
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8
6
.
[2
]
A.
V
iso
li
,
“
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u
z
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se
d
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e
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w
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h
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tu
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in
g
o
f
P
ID
c
o
n
tr
o
ll
e
rs
,”
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E
T
ra
n
s
a
c
ti
o
n
s
o
n
sy
ste
ms
,
ma
n
a
n
d
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y
b
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e
ti
c
s
-
p
a
rt A
:
S
y
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ms
a
n
d
Hu
ma
n
s
,
v
o
l
/i
ss
u
e
:
29
(
6
),
1
9
9
9
.
[3
]
A.
V
isio
li
,
“
T
u
n
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n
g
o
f
PID
c
o
n
tro
ll
e
rs
wit
h
fu
zz
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l
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,”
IEE
E
p
ro
c
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e
d
i
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g
-
Co
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tr
o
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p
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:
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4
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[4
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A.
Be
sh
a
ra
ti
,
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t
a
l.
,
“
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lf
–
tu
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o
f
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ID
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p
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rc
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m
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th
o
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,”
IE
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ra
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s.
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n
In
d
u
stria
l
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.
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5
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.
[5
]
R.
Ca
p
o
n
e
t
to
,
e
t
a
l.
,
“
Ch
a
o
ti
c
se
q
u
e
n
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e
s
to
im
p
ro
v
e
th
e
p
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o
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o
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v
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lu
ti
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ry
a
lg
o
rit
h
m
s,”
IEE
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T
ra
n
s.
o
n
Evo
lu
ti
o
n
a
ry
Co
mp
u
t
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ol
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s
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:
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p
.
2
8
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2
0
0
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.
[6
]
Z
.
Z
h
ih
a
o
a
n
d
W
.
Jia
n
w
e
n
,
“
Ne
g
a
ti
v
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se
q
u
e
n
c
e
c
u
rr
e
n
t
fee
d
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fo
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wa
rd
c
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f
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re
e
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p
h
a
se
f
o
u
r
-
leg
S
T
AT
COM
u
n
d
e
r
u
n
b
a
l
a
n
c
e
d
lo
a
d
s
,
”
In
ter
n
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
P
o
w
e
r
S
y
st
e
m
T
e
c
h
n
o
lo
g
y
,
pp.
2
2
0
2
–
2
2
0
8
,
2
0
1
4
.
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