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IS
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]
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2.
1
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C
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F
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in
[1]
,
we
ha
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c
h
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ra
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s
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:
1
1
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2
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)
(
s
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us
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be
s
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d.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
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J
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l
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5
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31
4
3
ba
b
b
;
3
2
1
4
1
2
b
b
b
b
c
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;
24
cb
;
6
1
1
1
1
0
1
0
()
i
F
s
s
a
T
T
L
C
C
L
L
L
L
L
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;
5
1
1
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1
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1
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0
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(
)
(
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i
s
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s
F
i
F
s
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a
T
T
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L
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C
R
L
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L
L
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C
C
C
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4
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(
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i
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n
v
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T
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L
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C
R
L
C
C
C
C
L
K
K
T
;
3
0
1
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1
1
1
()
i
F
s
i
F
s
F
i
n
v
F
a
T
T
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R
T
L
C
L
C
L
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L
C
K
K
C
L
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;
2
i
i
F
s
i
i
n
v
F
a
T
T
T
C
R
T
K
K
C
;
1
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v
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a
T
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K
C
;
0
.
0
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0
.
0
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1
;
1
0
;
1
i
i
n
v
T
m
s
T
K
K
Co
n
s
t
r
a
i
n
t
s
on
r
e
s
o
na
n
c
e
c
o
n
di
t
i
o
n
s
in
PPFs:
T
h
e
L
a
n
d
C
p
a
r
a
m
e
t
e
r
s
in
a
b
ra
n
c
h
m
us
t
be
r
e
s
o
na
t
e
d
at
a
c
e
r
t
a
i
n
f
r
e
que
n
c
y
.
1
n
n
L
C
(3)
Co
n
s
t
r
a
i
n
t
of
pa
s
s
i
v
e
po
w
e
r
f
i
l
t
e
r
v
a
l
ue
s
:
pa
s
s
i
v
e
po
w
e
r
f
i
l
t
e
r
v
a
l
ue
s
m
us
t
be
po
s
i
t
i
v
e
a
n
d
m
e
e
t
s
y
s
t
e
m
s
t
a
b
i
l
i
ty
a
n
d
r
e
s
o
n
a
n
c
e
c
o
n
di
t
i
o
n
s
.
m
a
x
m
a
x
m
a
x
0
(
,
,
)
(
,
,
)
i
i
i
R
L
C
R
L
C
(4)
t
he
v
a
l
ue
s
of
R
max
,
L
m
a
x,
a
nd
C
max
a
r
e
de
t
e
rm
i
n
e
d
u
n
de
r
s
t
a
b
l
e
c
o
n
di
t
i
o
n
s
(2)
.
PPFs
m
us
t
be
c
o
m
pe
n
s
a
t
e
d
w
i
t
h
a
m
a
xi
m
um
c
a
p
a
c
i
t
y
b
ut
n
o
t
e
xc
e
e
d
t
h
e
r
e
qui
r
e
d
m
a
xi
m
u
m
l
i
m
i
t
m
i
n
m
a
x
c
c
c
Q
Q
Q
(5)
c
o
n
s
t
ra
i
nt
of
DC
-
b
us
vo
l
t
a
ge
v
a
l
ue
:
0
<
U
dc
<
U
dc
-
max
(6)
Co
n
t
r
o
l
l
e
r
pa
ra
m
e
t
e
r
s
c
o
n
s
t
ra
i
nt
s
:
Co
n
t
r
o
l
l
e
r
p
a
r
a
m
e
t
e
r
s
m
us
t
be
po
s
i
t
i
v
e
a
n
d
s
a
t
i
s
fy
s
y
s
t
e
m
s
t
a
b
i
l
i
t
y
c
o
n
di
t
i
o
n
s
(2)
.
0
<
K
p
<
K
p
m
a
x
;
0
<
K
i
<
K
imax
(7)
a
c
c
o
r
di
n
g
to
[5]
,
t
h
e
v
a
l
ue
of
K
p
a
n
d
K
i
is
t
o
o
s
m
a
l
l
or
t
o
o
l
a
rge
to
c
a
us
e
s
y
s
t
e
m
i
n
s
t
a
b
i
l
i
t
y
.
O
b
j
e
c
t
i
ve
f
un
c
t
i
o
n
:
we
c
o
n
s
i
de
r
t
h
e
m
a
i
n
o
b
j
e
c
t
i
v
e
as
fo
l
l
ow
s
:
m
i
n
(
)
ss
F
T
H
D
i
T
H
D
u
(8)
2.
2
.
V
o
r
te
x
S
e
ar
c
h
A
l
go
r
i
th
m
a
nd
I
ts
A
p
p
l
i
c
a
ti
o
n
f
or
D
e
s
i
gn
i
n
g
H
yb
r
i
d
A
c
ti
v
e
P
o
w
e
r
F
i
l
t
e
r
T
h
e
V
o
r
t
e
x
s
e
a
r
c
h
a
l
go
r
i
t
hm
is
f
i
r
s
t
p
r
o
po
s
e
d
in
[2
3
,
2
4
].
Let
us
c
o
n
s
i
de
r
a
t
w
o
-
di
m
e
n
s
i
o
n
a
l
o
pt
i
m
i
z
a
t
i
o
n
p
r
o
b
l
e
m
.
In
a
t
w
o
-
di
m
e
n
s
i
o
n
a
l
c
a
s
e
,
a
v
o
r
t
e
x
pa
t
t
e
rn
can
be
m
o
de
l
l
e
d
by
a
num
b
e
r
of
n
e
s
t
e
d
c
i
r
c
l
e
s
.
H
e
r
e
,
t
h
e
l
a
r
ge
s
t
c
i
r
c
l
e
of
t
h
e
vo
r
t
e
x
is
f
i
r
s
t
c
e
nt
e
r
e
d
on
t
h
e
s
e
a
r
c
h
s
p
a
c
e
,
w
h
e
r
e
t
h
e
i
ni
t
i
a
l
c
e
nt
e
r
can
be
c
a
l
c
ul
a
t
e
d
us
i
ng
(
9
)
.
A
de
s
c
r
i
p
t
i
o
n
of
t
h
e
VS
a
l
go
ri
t
hm
is
a
l
s
o
p
r
o
v
i
de
d
in
a
l
go
r
i
t
hm
1.
0
2
u
p
p
e
r
lim
it+
lo
w
e
r
lim
it
(9)
00
m
a
x
(
)
2
u
p
p
e
r
l
i
m
i
t
m
i
n
l
o
w
e
r
l
i
m
i
t
r
(10)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
In
do
n
e
s
i
a
n
J
E
l
e
c
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&
Co
m
p
S
c
i
,
V
o
l
.
18
,
N
o
.
1
,
A
p
r
i
l
20
20
:
443
-
4
51
446
T
h
e
s
o
l
ut
i
o
n
s
t
ha
t
e
xc
e
e
d
t
h
e
bou
n
da
ri
e
s
a
r
e
s
hi
f
t
e
d
i
n
t
o
t
h
e
bo
un
da
ri
e
s
,
as
in
(
11
)
.
;
;
;
i
i
i
i
i
k
i
i
i
i
i
k
k
k
i
i
i
i
i
k
rand
uppe
rl
i
m
i
t
l
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e
rl
i
m
i
t
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e
rl
i
m
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t
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e
r
l
i
m
i
t
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e
rl
i
m
i
t
s
uppe
rl
i
m
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t
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rl
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e
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i
m
i
t
l
ow
e
rl
i
m
i
t
s
uppe
r
l
i
m
i
t
(11)
T
h
e
i
n
i
t
i
a
l
ra
d
i
us
r
0
can
be
c
a
l
c
ul
a
t
e
d
w
i
t
h
(10)
.
B
e
c
a
us
e
a
0
=
1,
t
h
e
r
e
s
ul
t
i
ng
f
un
c
t
i
o
n
v
a
l
ue
is
1(
x
)
⋅
g
am
m
ai
n
c
i
n
v
(
x,
a
0
)
≈1,
w
h
i
c
h
m
e
a
n
s
r
0
≈
0
as
i
n
di
c
a
t
e
d
b
e
fo
r
e
.
0
0
0
1
.
.
(
,
)
r
g
a
m
m
a
inc
inv
x
a
x
(12)
b
y
m
e
t
h
o
ds
of
(12)
,
t
h
e
i
ni
t
i
a
l
ra
di
us
v
a
l
ue
r
0
can
be
c
o
m
put
e
d
as
r
0
≈10
.
R
a
d
i
us
at
e
a
c
h
i
t
e
ra
t
i
o
n
is
c
a
l
c
ul
a
t
e
d
by
us
i
n
g
(
13)
.
0
1
.
.
(
,
)
tt
r
gammaincinv
x
a
x
(13)
In
t
h
i
s
a
l
go
ri
t
hm
pa
ra
m
a
t
e
r
t
a
of
t
h
e
i
n
v
e
r
s
e
i
n
c
o
m
pl
e
t
e
g
a
m
m
a
f
un
c
t
i
o
n
de
f
i
n
e
s
t
h
e
r
e
s
o
l
ut
i
o
n
of
t
h
e
s
e
a
r
c
h
.
By
e
qua
l
l
y
s
a
m
pl
i
n
g
v
a
l
ue
s
w
i
t
h
i
n
[1
,
0]
i
nt
e
r
v
a
l
at
a
c
e
r
t
a
i
n
s
t
e
p
s
i
z
e
,
t
h
e
r
e
s
o
l
ut
i
o
n
of
t
h
e
s
e
a
r
c
h
can
be
a
dj
us
t
e
d.
F
o
r
t
h
i
s
pu
r
po
s
e
,
at
ge
n
e
r
a
t
i
o
n
t,
a
t
is
o
b
t
a
i
n
e
d
by
us
i
n
g
(1
4)
.
0
t
t
aa
Ma
x
Int
(14)
w
h
e
r
e
0
a
is
s
e
l
e
c
t
e
d
as
0
1
a
to
e
n
s
u
r
e
f
ul
l
c
o
ve
r
a
ge
of
t
he
s
e
a
r
c
h
s
p
a
c
e
at
t
h
e
f
i
r
s
t
i
t
e
r
a
t
i
o
n
,
t
i
s
t
h
e
i
t
e
r
a
t
i
o
n
i
n
de
x,
a
nd
Max
I
t
r
r
e
p
r
e
s
e
nt
s
t
h
e
m
a
xi
m
u
m
num
b
e
r
of
i
t
e
r
a
t
i
o
n
s
.
V
o
r
t
e
x
S
e
a
r
c
h
a
l
go
r
i
t
hm
f
l
ow
c
h
a
r
t
for
de
s
i
g
n
i
ng
H
A
P
F
is
s
how
n
as
in
F
i
gu
r
e
2.
A
l
go
r
i
t
h
m
1.
I
nput
s
:
I
ni
t
i
a
l
c
e
n
t
e
r
0
is
c
a
l
c
ul
a
t
e
d
by
us
i
ng
(
9)
I
ni
t
i
a
l
r
a
d
i
us
0
or
0
is
c
a
c
ul
a
t
e
d
by
us
i
ng
(
1
0)
B
e
s
t
f
i
t
ne
s
s
so
f
a
r
(
)
=
i
n
f
O
ut
pu
t
:
B
e
s
t
s
o
l
ut
i
o
n
=
0
;
R
e
pe
a
t
/*
G
e
ne
r
a
t
e
c
a
nd
i
da
t
e
s
o
l
u
t
i
o
ns
by
us
i
ng
G
a
us
s
i
a
n
d
i
s
t
r
i
bu
t
i
o
n
a
r
o
u
nd
t
he
c
e
n
t
e
r
w
i
t
h
a
s
t
a
nda
r
d
de
v
i
a
t
i
o
n
(
r
a
di
u
s
)
*/
G
e
ne
r
a
t
e
(
)
;
If
e
xc
e
e
de
d
,
t
h
e
n
s
h
i
f
t
t
h
e
(
)
v
a
l
u
e
s
i
nt
o
t
he
bo
und
a
r
i
e
s
as
in
(
11)
;
/*
S
e
l
e
c
t
t
h
e
be
s
t
s
o
l
u
t
i
o
n
f
r
o
m
(
)
to
r
e
p
l
a
c
e
t
h
e
c
u
r
r
e
nt
c
e
nt
e
r
*/
′
=
(
(
)
)
;
if
(
′
)
<
(
)
=
′
(
)
=
(
′
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e
l
s
e
K
e
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h
e
be
s
t
s
o
l
u
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n
f
o
und
so
f
a
r
;
E
nd
/*
C
e
n
t
e
r
is
a
l
w
a
y
s
s
h
i
f
t
e
r
to
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h
e
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t
s
o
l
u
t
i
o
n
f
o
und
so
f
a
r
*/
+
1
=
;
/*
D
e
c
r
e
a
s
e
t
he
s
t
a
nd
a
r
d
d
e
v
i
a
t
i
o
n
(
r
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us
)
f
o
r
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he
n
e
xt
i
t
e
r
a
t
i
o
n*/
+
1
=
(
)
;
=
+
1
;
U
nt
i
l
t
he
m
a
x
i
m
um
num
be
r
of
i
t
e
r
a
t
i
o
ns
is
r
e
a
c
he
d
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
V
or
t
e
x
s
e
ar
c
h
a
l
gor
i
t
hm
f
or
d
e
s
i
gn
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y
br
i
d
ac
t
i
v
e
pow
e
r
f
i
l
t
e
r
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M
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447
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e
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I
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p
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t
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r
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o
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,
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1
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0
,
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d
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,
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p
,
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m
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l
a
t
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o
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t
a
b
i
l
i
t
y
t
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s
t
?
F
i
t
n
e
s
s
O
u
t
p
u
t
t
h
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b
e
s
t
s
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l
u
t
i
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n
d
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e
s
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o
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e
s
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o
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t
e
x
S
e
a
r
c
h
A
l
g
o
r
i
t
h
m
(
C
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,
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1
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1
,
L
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U
d
c
,
K
p
,
K
i
X
)
(
%
%
)
5%
ss
T
H
D
i
T
H
D
u
F
i
gu
r
e
2.
V
o
rt
e
x
s
e
a
r
c
h
a
l
go
r
i
t
h
m
f
l
ow
c
h
a
r
t
for
de
s
i
g
n
i
ng
H
A
P
F
A
ppl
i
c
a
t
i
o
n
of
t
h
e
VS
A
l
go
r
i
t
h
m
fo
r
H
y
b
r
i
d
A
c
t
i
v
e
P
ow
e
r
F
i
l
t
e
r
D
e
s
i
g
n
is
de
s
c
r
i
b
e
d
as
f
o
l
l
o
w
s
:
T
h
e
a
l
go
ri
t
hm
b
e
gi
n
s
by
e
n
t
e
ri
n
g
t
h
e
uppe
r
a
n
d
l
o
w
e
r
l
i
m
i
t
v
a
l
u
e
s
of
t
h
e
pa
ra
m
e
t
e
r
s
to
be
s
e
a
r
c
h
e
d
b
a
s
e
d
on
t
h
e
c
o
n
s
t
ra
i
nt
s
in
t
h
e
f
o
r
m
ul
a
s
f
r
o
m
(3
)
to
(7)
,
t
h
e
n
t
h
e
s
e
l
i
m
i
t
s
w
i
l
l
be
i
n
c
l
ude
d
in
t
h
e
VS
a
l
go
ri
t
hm
to
f
i
n
d
a
s
e
t
of
pa
r
a
m
e
t
e
r
s
to
be
s
e
a
r
c
h
e
d
(
,
1
,
1
,
0
,
,
,
)
.
N
e
xt
,
t
h
e
s
e
p
a
r
a
m
e
t
e
r
s
w
i
l
l
be
c
h
e
c
ke
d
for
s
t
a
b
l
e
c
o
n
di
t
i
o
n
s
us
i
ng
f
o
r
m
u
l
a
(2),
if
n
o
t
s
t
a
b
l
e
c
o
n
di
t
i
o
n
,
r
e
t
u
rn
to
VS
a
l
go
r
i
t
hm
to
c
r
e
a
t
e
a
n
e
w
s
e
t
of
pa
ra
m
e
t
e
r
s
,
if
s
t
a
b
l
e
c
o
n
di
t
i
o
n
is
s
a
t
i
s
f
i
e
d,
t
h
e
s
e
pa
ra
m
e
t
e
r
s
w
i
l
l
be
s
e
t
up
i
nt
o
t
h
e
H
A
P
F
s
i
m
ul
a
t
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o
n
m
o
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l
to
f
i
n
d
t
h
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THDi
s
%
a
n
d
THDu
s
%
v
a
l
ue
s
.
T
h
e
v
a
l
ue
of
%
m
us
t
be
l
e
s
s
t
h
a
n
1
a
nd
%
m
us
t
be
l
e
s
s
t
h
a
n
2
,
a
c
c
o
r
d
i
n
g
to
IE
E
E
5
19
s
t
a
n
d
a
r
d
[2
5
],
t
he
v
a
l
ue
of
1
is
l
e
s
s
t
ha
n
or
e
qua
l
to
5%
a
n
d
2
is
l
e
s
s
t
h
a
n
or
e
qu
a
l
to
5%.
T
h
e
r
e
f
o
r
e
,
to
s
a
t
i
s
fy
1
a
nd
2
,
t
h
e
o
b
j
e
c
t
i
v
e
f
un
c
t
i
o
n
F
m
us
t
be
l
e
s
s
t
ha
n
5%,
t
h
e
n
s
t
o
p
a
n
d
p
ri
n
t
o
ut
t
h
e
r
e
s
ul
t
s
.
V
o
r
t
ex
S
e
a
r
c
h
a
l
go
ri
t
hm
f
l
ow
c
h
a
r
t
for
de
s
i
g
n
i
ng
H
A
P
F
is
de
s
c
ri
b
e
d
as
in
F
i
gur
e
2.
3.
S
I
M
U
LA
TI
O
N
R
ES
U
LTS
AND
DISCUSSIO
N
To
de
m
o
n
s
t
ra
t
e
t
h
e
e
f
fe
c
t
i
ve
n
e
s
s
of
t
h
e
p
r
o
po
s
e
d
de
s
i
gn
m
e
t
h
o
d.
L
e
t
'
s
c
o
n
s
i
de
r
,
l
e
t
us
c
o
n
s
i
de
r
a
H
A
P
F
m
o
de
l
as
s
h
o
w
n
in
F
i
g
u
r
e
1.
T
hr
e
e
-
p
h
a
s
e
s
o
ur
c
e
v
o
l
t
a
ge
is
3
80V
-
50H
z
.
T
H
D
of
t
h
e
l
o
a
d
c
urr
e
nt
is
s
h
o
w
n
in
F
i
g
u
r
e
3.
A
c
c
o
r
di
n
g
to
[1]
,
t
h
e
pa
ra
m
e
t
e
r
s
of
t
h
e
H
A
P
F
s
y
s
t
e
m
w
i
t
h
t
ra
di
t
i
o
na
l
de
s
i
g
n
m
e
t
h
o
d
a
r
e
c
a
l
c
ul
a
t
e
d
in
T
a
b
l
e
1.
In
a
ddi
t
i
o
n
,
t
h
e
c
o
n
t
r
o
l
l
e
r
p
a
r
a
m
e
t
e
r
s
a
r
e
ra
n
do
m
l
y
s
e
l
e
c
t
e
d
w
i
t
h
t
h
e
b
e
s
t
p
a
r
a
m
e
t
e
r
s
of
K
p
=
30
a
n
d
K
i
=
0.
1
,
s
w
i
t
c
h
i
n
g
f
r
e
que
n
c
y
f
=
1
0kH
z
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
In
do
n
e
s
i
a
n
J
E
l
e
c
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ng
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m
p
S
c
i
,
V
o
l
.
18
,
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o
.
1
,
A
p
r
i
l
20
20
:
443
-
4
51
448
F
i
gu
r
e
3.
T
H
D
of
t
h
e
l
o
a
d
c
urr
e
nt
T
he
p
a
r
a
m
e
t
e
r
s
in
T
a
b
l
e
1,
we
o
b
t
a
i
n
t
h
e
w
a
v
e
f
o
r
m
s
of
t
h
e
H
A
P
F
s
y
s
t
e
m
s
h
o
w
n
in
F
i
g
u
r
e
4.
F
r
o
m
F
i
gu
r
e
4,
we
s
e
e
t
h
a
t
:
T
H
D
of
t
h
e
s
uppl
y
c
urr
e
nt
i
s
de
c
r
e
a
s
e
s
f
r
o
m
32.
77%
to
2.
1
%,
T
H
D
of
t
h
e
s
o
ur
c
e
v
o
l
t
a
ge
u
s
is
1
.
69
%,
w
hi
l
e
t
h
e
r
e
a
c
t
i
v
e
pow
e
r
de
c
r
e
a
s
e
d
to
140v
a
r
f
ro
m
2359v
a
r,
t
h
a
t
i
s
,
t
h
e
c
a
p
a
c
i
t
y
c
o
m
pe
n
s
a
t
e
d
by
PPFs
is
2219v
a
r.
T
H
D
of
t
h
e
s
u
ppl
y
c
urr
e
n
t
i
s
s
h
o
w
n
in
F
i
g
ur
e
5.
T
H
D
of
t
h
e
s
o
u
r
c
e
vo
l
t
a
ge
u
s
is
s
h
o
w
n
in
F
i
gu
r
e
6.
T
a
b
l
e
1.
H
A
P
F
P
a
r
a
m
e
t
e
r
s
b
y
T
ra
di
t
i
o
n
a
l
D
e
s
i
g
n
M
e
t
h
o
d
C
F
(µF
)
C
1
(µF
)
L
1
(m
H
)
L
0
(m
H
)
U
dc
(V
)
T
H
D
i
s
(
%
)
T
H
D
u
s
(
%
)
1
1
6
.
8
3
4
9
.
2
2
9
.
7
7
0
.
2
535
2
.
1
1
.
6
9
F
i
gu
r
e
4.
W
a
v
e
fo
r
m
s
of
H
A
P
F
w
i
t
h
t
ra
d
i
t
i
o
n
a
l
de
s
i
g
n
m
e
t
h
o
d
F
i
gu
r
e
5.
T
H
D
of
t
h
e
s
uppl
y
c
urr
e
n
t
i
s
F
i
gu
r
e
6.
T
H
D
of
t
h
e
s
o
ur
c
e
v
o
l
t
a
ge
u
s
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
V
or
t
e
x
s
e
ar
c
h
a
l
gor
i
t
hm
f
or
d
e
s
i
gn
i
ng
h
y
br
i
d
ac
t
i
v
e
pow
e
r
f
i
l
t
e
r
(
Chau
M
i
nh
T
huy
e
n
)
449
w
ith
t
h
e
p
r
o
po
s
e
d
de
s
i
gn
m
e
t
h
o
d,
t
h
e
b
e
s
t
p
a
r
a
m
e
t
e
r
s
of
H
A
P
F
a
f
t
e
r
10
i
t
e
ra
t
i
o
n
s
a
r
e
s
h
o
w
n
in
T
a
b
l
e
2.
F
r
o
m
t
h
e
pa
ra
m
e
t
e
r
s
in
T
a
b
l
e
2,
we
ob
t
a
i
n
t
h
e
w
a
v
e
fo
r
m
s
of
t
h
e
H
A
P
F
s
y
s
t
e
m
s
h
o
w
n
in
F
i
g
u
r
e
7.
T
a
b
l
e
2.
H
A
P
F
P
a
r
a
m
e
t
e
r
s
w
i
t
h
t
he
P
r
o
po
s
e
d
M
ul
t
i
-
O
b
j
e
c
t
i
ve
O
pt
i
m
i
z
a
t
i
o
n
M
e
t
h
o
d
C
F
(µF
)
C
1
(µF
)
L
1
(m
H
)
L
0
(m
H
)
U
dc
(V
)
K
p
K
i
T
H
D
i
s
(%
)
T
H
D
u
s
(%
)
1
3
6
.
6
7
3
0
1
.
2
2
2
6
.
6
1
.
0
1
6
7
4
.
1
3
9
4
.
9
5
0
.
6
5
1
.
1
4
1
.
2
8
F
i
gu
r
e
7.
W
a
v
e
fo
r
m
s
of
H
A
P
F
w
i
t
h
t
h
e
p
r
o
po
s
e
d
de
s
i
gn
m
e
t
h
o
d
F
r
o
m
F
i
gu
r
e
7,
we
can
s
e
e
t
h
a
t
:
T
H
D
of
t
h
e
s
uppl
y
c
urr
e
n
t
i
s
de
c
r
e
a
s
e
s
f
r
o
m
3
2.
77
%
to
1
.
14%
,
w
h
i
l
e
t
h
e
r
e
a
c
t
i
v
e
po
w
e
r
de
c
r
e
a
s
e
d
to
90v
a
r
f
r
o
m
2
359v
a
r
,
so
t
h
e
c
o
m
pe
n
s
a
t
i
o
n
po
w
e
r
by
PPFs
is
2269v
a
r
.
T
H
D
of
t
h
e
s
upp
ly
c
urr
e
n
t
i
s
in
s
t
e
a
dy
-
s
t
a
t
e
is
s
h
o
w
n
in
F
i
g
u
r
e
8,
T
H
D
of
t
h
e
s
o
ur
c
e
v
o
l
t
a
ge
u
s
in
s
t
e
a
dy
-
s
t
a
t
e
is
s
h
o
w
n
in
F
i
gu
r
e
9.
F
i
gu
r
e
8.
T
H
D
of
t
h
e
s
uppl
y
c
urr
e
n
t
i
s
F
i
gu
r
e
9.
T
H
D
of
t
h
e
s
o
ur
c
e
v
o
l
t
a
ge
u
s
A
c
c
o
r
di
n
g
to
IE
E
E
S
t
d.
519
-
19
92
R
e
c
o
m
m
e
n
de
d
Pr
a
c
t
i
c
e
s
a
n
d
R
e
qui
r
e
m
e
nt
s
for
h
a
rm
o
ni
c
c
o
n
t
r
o
l
in
e
l
e
c
t
r
i
c
a
l
po
w
e
r
s
y
s
t
e
m
s
[2
5
],
t
h
e
n
t
o
t
a
l
h
a
rm
o
ni
c
d
i
s
t
o
r
t
i
o
n
of
c
ur
r
e
nt
is
l
e
s
s
t
h
a
n
or
e
qua
l
5
%.
T
H
D
of
t
h
e
s
uppl
y
vo
l
t
a
ge
is
l
e
s
s
t
ha
n
or
e
qu
a
l
5%
.
F
r
o
m
t
h
e
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[
1]
C
hua
np
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u
,
et
al
.
,
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l
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in
200
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nc
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on
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r
G
e
ne
r
a
t
i
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n
a
nd
S
u
pp
l
y
,
2009
,
pp.
1
-
7.
[
2]
M
i
n
h
T
huy
e
n
C
ha
u
,
“
G
e
ne
r
a
l
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z
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d
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o
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pe
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br
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d
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x
p
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s
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L
e
t
t
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r
s
,
v
o
l
.
11
,
p
p.
14
09
-
1415
,
20
17.
[
3]
M
i
n
hT
huy
e
n
C
ha
u,
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S
t
a
bl
e
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e
l
f
-
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,
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nt
e
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at
i
on
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J
o
ur
n
al
of
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l
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e
d
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ng
i
ne
e
r
i
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R
e
s
e
ar
c
h
,
v
o
l
.
12
,
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.
7162
-
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,
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017
.
[
4]
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br
a
hi
m
A
l
h
a
m
r
o
uni
,
et
a
l
.
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ndo
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J
E
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C
S)
.
v
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l
.
15
,
pp
.
581
-
592
,
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9.
[
5]
M.
C
h
a
u,
et
a
l
.
,
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l
.
5
,
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.
147
2
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[
6]
M
i
n
h
T
huy
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n
C
ha
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da
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p.
34
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016
.
[
7]
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L
uo
,
et
a
l
.
,
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e
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e
nt
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y
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l
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a
ns
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c
t
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on
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l
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r
y
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v
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l
.
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,
p
p.
424
-
43
2,
20
09.
[
8]
Z.
S
h
ua
i
,
A.
L
uo
,
C.
T
u
,
D.
L
i
u
,
“
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e
w
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o
nt
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l
m
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,
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E
T
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l
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c
t
r
oni
c
s
,
v
o
l
.
4,
pp.
1
051
-
105
7,
20
11
.
[
9]
C
ha
u
M
i
n
h
T
huy
e
n,
“
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m
pr
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d
p
-
q
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a
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t
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nt
e
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n
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on
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our
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of
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t
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c
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l
a
nd
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om
pu
t
e
r
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ngi
ne
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i
ng
(
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J
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C
E
)
,
v
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l
.
8,
p
p.
291
0
-
2919
,
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.
[
10]
H.
A
ka
g
i
,
et
al
.
,
“
G
e
ne
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a
l
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z
e
d
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h
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ns
t
a
n
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o
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a
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t
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t
s
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ppl
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t
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o
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l
e
c
t
r
i
c
a
l
E
ng
i
ne
e
r
i
ng
of
J
ap
an
,
v
o
l
.
10
3,
pp
.
483
-
49
0,
19
83.
[
11]
Y.
K.
L
a
t
ha
,
et
a
l
.
,
“
C
o
nt
r
o
l
S
t
r
a
t
e
gy
f
o
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T
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e
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h
a
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hu
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l
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h
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i
n
i
m
um
C
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r
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t
M
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s
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m
e
n
t
s
,
”
I
nt
e
r
n
at
i
on
al
J
o
ur
na
l
of
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l
e
c
t
r
i
c
al
an
d
C
om
pu
t
e
r
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ngi
ne
e
r
i
n
g
(
I
J
E
C
E
)
,
v
o
l
.
1,
pp
.
31
-
42,
2
011
.
[
12]
P
a
nka
j
G
a
kh
a
r
a
n
d
M
a
no
j
G
up
t
a
,
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no
v
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l
c
o
nt
r
o
l
s
t
r
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t
e
gy
f
o
r
pow
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r
qua
l
i
t
y
i
m
pr
o
v
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m
e
nt
in
g
r
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d
-
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o
nne
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t
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d
s
o
l
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pho
t
o
vo
l
t
a
ic
s
y
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m
,
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ndone
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i
an
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c
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ne
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om
pu
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(
I
J
E
E
C
S)
,
v
o
l
.
15
,
pp.
12
64
-
1272
,
201
9.
[
13]
C
ha
u
V
a
n
B
a
o
A
nd
C
ha
u
M
i
nh
T
huy
e
n.
,
“
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-
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us
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l
t
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C
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t
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s
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v
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l
.
13,
no
.
1,
pp
.
27
-
33,
20
19
.
[
14]
An
L
uo
,
et
al
.
,
“
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g
n
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T
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an
s
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ons
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s
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l
.
2
4,
pp
.
75
-
84,
2
009
.
[
15]
C.
C.
M.
M
o
ur
a
,
et
a
l
.
,
“
D
e
t
e
r
m
i
na
t
i
o
n
of
t
he
R
-
L
-
C
par
am
e
t
e
r
s
of
a
pas
s
i
v
e
h
ar
m
o
ni
c
f
i
l
t
e
r
u
s
i
n
g
ge
ne
t
i
c
al
gor
i
t
hm
,”
in
10
th
I
nt
e
r
na
t
i
o
na
l
C
o
nf
e
r
e
nc
e
on
H
a
r
m
o
ni
c
s
a
nd
Q
ua
l
i
t
y
of
P
o
w
e
r
,
20
02,
p
p.
49
5
-
500.
[
16]
S
ur
e
s
h
kum
a
r
,
R
a
m
e
s
h
r
e
d
dy
a
nd
A
r
c
ha
na
,
“
T
h
e
a
pp
l
i
c
a
t
i
o
n
of
ps
o
to
hy
br
i
d
a
c
t
i
v
e
po
w
e
r
f
i
l
t
e
r
d
e
s
i
g
n
f
o
r
3
pha
s
e
4
-
w
i
r
e
s
y
s
t
e
m
w
i
t
h
b
a
l
a
nc
e
d
&
unb
a
l
a
nc
e
d
l
o
a
ds
,
”
I
nt
e
r
na
t
i
ona
l
j
o
ur
na
l
of
ad
v
anc
e
s
in
e
ngi
ne
e
r
i
ng
&
t
e
c
h
nol
ogy
,
v
o
l
.
2
,
pp
.
32
-
42
,
2012
.
[
17]
N.
S.
H
a
s
a
n
,
et
al
.,
“
H
a
r
m
o
ni
c
S
u
ppr
e
s
s
i
o
n
of
S
h
unt
H
y
br
i
d
F
i
l
t
e
r
u
s
i
ng
L
Q
R
-
PSO
ba
s
e
d
,
”
I
nt
e
r
n
at
i
on
a
l
J
o
ur
n
al
of
E
l
e
c
t
r
i
c
al
an
d
C
om
put
e
r
E
ng
i
ne
e
r
i
ng
(
I
J
E
C
E
)
,
v
o
l
.
7,
pp.
8
69
-
876
,
201
7.
[
18]
S
he
ng
qi
ng
Li
,
et
al
.
,
“
M
ul
t
i
obj
e
c
t
i
v
e
o
pt
i
m
al
de
s
i
gn
f
o
r
pas
s
i
v
e
po
w
e
r
f
i
l
t
e
r
s
in
hy
br
i
d
pow
e
r
f
i
l
t
e
r
s
y
s
t
e
m
ba
s
e
d
on
m
ul
t
i
-
i
s
l
a
nd
p
ar
t
i
c
l
e
s
w
ar
m
opt
i
m
i
z
a
t
i
on
,”
in
7t
h
I
nt
e
r
na
t
i
o
na
l
C
o
nf
e
r
e
nc
e
on
P
o
w
e
r
E
l
e
c
t
r
o
ni
c
s
a
nd
M
o
t
i
o
n
C
o
nt
r
o
l
,
2012
,
pp.
2
859
-
286
3.
[
19]
S
ur
e
s
h
kum
a
r
a
nd
K.
R
a
m
e
s
h,
“
T
he
a
pp
l
i
c
a
t
i
o
n
PSO
hy
br
i
d
a
c
t
i
v
e
p
o
w
e
r
f
i
l
t
e
r
d
e
s
i
g
n
f
o
r
3
ph
a
s
e
4
-
w
i
r
e
s
y
s
t
e
m
w
i
t
h
v
a
r
i
a
b
l
e
l
o
a
d
,
”
I
nt
e
r
n
at
i
ona
l
J
o
ur
na
l
of
E
ngi
ne
e
r
i
ng
In
v
e
nt
i
ons
,
v
o
l
.
1,
pp
.
39
-
46
,
2012
.
[
20]
N
i
e
n
-
C
he
Y
a
ng
a
nd
M
i
nh
-
D
uy
L
e
,
“
M
u
l
t
i
-
o
bj
e
c
t
i
v
e
b
a
t
a
l
g
o
r
i
t
h
m
w
i
t
h
t
i
m
e
-
v
a
r
y
i
ng
i
ne
r
t
i
a
w
e
i
g
ht
s
f
o
r
o
pt
i
m
a
l
de
s
i
g
n
of
pa
s
s
i
v
e
po
w
e
r
f
i
l
t
e
r
s
s
e
t
,
”
I
E
T
G
e
ne
r
at
i
on
,
T
r
an
s
m
i
s
s
i
on
&
D
i
s
t
r
i
bu
t
i
on
,
v
o
l
.
9,
p
p.
64
4
-
654
,
2015
.
[
21]
R
r
a
c
hi
d
D
e
h
i
n
i
a
nd
S
l
i
m
a
n
e
S
e
f
i
a
n
e
,
“
P
o
w
e
r
qua
l
i
t
y
a
nd
c
o
s
t
i
m
pr
o
v
e
m
e
nt
by
pa
s
s
i
v
e
po
w
e
r
f
i
l
t
e
r
s
s
y
nt
he
s
i
s
u
s
i
ng
a
nt
c
o
l
o
n
y
a
l
g
o
r
i
t
hm
,
”
J
ou
r
na
l
of
T
he
or
e
t
i
c
a
l
and
A
pp
l
i
e
d
I
nf
o
r
m
a
t
i
on
T
e
c
hno
l
og
y
,
v
o
l
.
1,
pp
.
70
-
79
,
2012
.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
V
or
t
e
x
s
e
ar
c
h
a
l
gor
i
t
hm
f
or
d
e
s
i
gn
i
ng
h
y
br
i
d
ac
t
i
v
e
pow
e
r
f
i
l
t
e
r
(
Chau
M
i
nh
T
huy
e
n
)
451
[
22]
A
hm
e
d
F
a
h
e
e
m
Z
o
ba
a
,
“
O
p
t
i
m
a
l
m
ul
t
i
-
o
bj
e
c
t
i
v
e
de
s
i
g
n
of
hy
br
i
d
a
c
t
i
v
e
po
w
e
r
f
i
l
t
e
r
s
c
o
ns
i
d
e
r
i
ng
a
d
i
s
t
o
r
t
e
d
e
nv
i
r
o
nm
e
nt
,
”
I
E
E
E
T
r
a
ns
a
c
t
i
on
s
on
I
nd
us
t
r
i
a
l
E
l
e
c
t
r
on
i
c
s
,
v
o
l
.
61,
pp.
1
07
-
114
,
2014
.
[
23]
B
e
r
a
t
D
o
ğ
a
n,
T
a
m
e
r
Ö
l
m
e
z
,
“A
ne
w
m
e
t
a
h
e
ur
i
s
t
i
c
f
o
r
num
e
r
i
c
a
l
f
u
nc
t
i
o
n
o
pt
i
m
i
z
a
t
i
o
n:
V
o
r
t
e
x
S
e
a
r
c
h
a
l
g
o
r
i
t
hm
”
,
I
nf
or
m
a
t
i
on
Sc
i
e
nc
e
s
,
V
o
l
um
e
29
3,
P
a
g
e
s
1
25
-
145
,
2015
.
[
24]
D
oğ
a
n
B,
Ö
l
m
e
z
T.
"
M
o
di
f
i
e
d
O
f
f
-
l
a
t
t
i
c
e
AB
M
o
de
l
f
o
r
P
r
o
t
e
i
n
F
o
l
di
ng
P
r
o
bl
e
m
U
s
i
ng
t
h
e
V
o
r
t
e
x
S
e
a
r
c
h
A
l
go
r
i
t
hm
,
"
I
n
t
e
r
na
t
i
ona
l
J
ou
r
na
l
of
M
ac
hi
ne
L
e
ar
ni
ng
and
C
om
p
u
t
i
n
g
.
v
o
l
.
5,
pp
.
329
-
33
3,
20
15.
[
25]
I
E
E
E
S
t
d.
519
-
199
2.
I
E
E
E
R
e
c
om
m
e
nde
d
P
r
ac
t
i
c
e
s
and
R
e
qu
i
r
e
m
e
nt
s
f
o
r
H
ar
m
o
ni
c
C
on
t
r
o
l
in
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l
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c
t
r
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c
a
l
P
ow
e
r
Sy
s
t
e
m
s
,
199
3.
Evaluation Warning : The document was created with Spire.PDF for Python.