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N
:
2502
-
4752
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
om
p S
c
i
,
V
ol
.
3
9
, N
o.
3
,
S
e
p
t
e
m
b
e
r
20
25
:
1
449
-
1
458
1450
L
F
C
P
in
m
ul
t
i
-
m
i
c
r
o
g
r
i
d
PS
[
3]
.
C
a
s
c
a
de
d
c
ont
r
ol
l
e
r
s
s
uc
h
as
f
r
a
c
t
i
ona
l
-
or
de
r
-
PI
a
nd
f
r
a
c
t
i
ona
l
-
or
de
r
-
PD
a
r
e
pr
opos
e
d
to
c
ont
r
ol
a
hy
dr
o
-
t
he
r
m
a
l
PS
in
[
4]
.
A
P
I
D
c
ont
r
ol
l
e
r
is
c
o
m
p
a
r
e
d
by
us
i
ng
an
a
d
a
pt
i
v
e
f
uz
z
y
l
og
i
c
c
ont
r
ol
l
e
r
w
i
t
h
H
∞
c
r
i
t
e
r
i
on
i
n
[
5]
.
T
he
s
e
a
ppr
oa
c
he
s
i
m
pr
o
v
e
t
he
r
e
a
c
t
i
v
i
t
y
a
nd
opt
i
m
i
z
e
t
he
c
ont
r
ol
l
e
r
s
i
n
or
de
r
t
o r
e
duc
e
a
nd c
on
v
e
r
g
e
t
he
a
r
e
a
c
ont
r
ol
e
r
r
or
w
i
t
h f
r
e
que
nc
y
de
v
i
a
t
i
on t
o z
e
r
o a
s
f
a
s
t
a
s
pos
s
i
bl
e
.
T
he
m
ode
l
pr
e
di
c
t
i
v
e
c
ont
r
ol
(
M
P
C
)
a
ppr
oa
c
h
i
s
a
l
s
o
w
i
de
l
y
us
e
d
f
or
L
F
C
P
.
A
n
M
P
C
c
ont
r
ol
s
M
S
-
M
A
I
P
S
w
i
t
h
c
ons
i
de
r
a
t
i
on
of
g
e
n
e
r
a
t
e
r
a
t
e
c
ons
t
r
a
i
nt
s
(
G
R
C
)
i
n
[
6]
.
A
not
he
r
a
ppr
oa
c
h
us
e
s
di
s
t
ur
ba
nc
e
r
e
j
e
c
t
i
on
f
or
M
S
M
A
I
P
S
in
[
7]
.
F
ur
t
he
r
m
or
e
,
i
n
[
8
]
,
a
n
M
P
C
i
s
a
l
s
o
us
e
d
f
or
P
S
w
i
t
h
r
e
ne
w
a
bl
e
e
ne
r
gy
-
w
i
nd
e
ne
r
gy
.
B
y
a
d
v
a
nc
i
n
g
M
P
C
,
a
da
pt
i
v
e
M
P
C
w
i
t
h
K
a
l
m
a
n
f
i
l
t
e
r
i
s
us
e
d
f
or
hi
g
h
-
pe
n
e
t
r
a
t
i
on
r
e
ne
w
a
bl
e
e
ne
r
gy
m
i
c
r
ogr
i
ds
in
[
9]
.
An
L
M
I
-
d
e
l
a
y
m
a
r
g
i
n
e
s
t
i
m
a
t
i
on
-
ba
s
e
d
c
ont
r
ol
l
er
f
or
PS
w
i
t
h
c
om
m
uni
c
a
t
i
on
de
l
a
y
is
pr
e
s
e
nt
e
d
i
n
[
10]
.
A
n
e
v
e
nt
-
t
r
i
gg
e
r
e
d
-
ba
s
e
d
c
ont
r
ol
l
e
r
i
s
us
e
d
f
or
P
S
w
i
t
h
t
i
m
e
d
e
l
a
y
i
n
[
11]
.
T
he
s
e
r
e
s
e
a
r
c
he
s
pr
o
v
i
de
d
e
e
p unde
r
s
t
a
ndi
ng
of
v
a
r
i
ous
c
ont
r
o
l
m
e
t
hods
on
m
a
n
y
P
S
s
c
e
na
r
i
os
.
T
he
s
l
i
di
ng
m
ode
c
ont
r
ol
(
S
M
C
)
a
ppr
oa
c
h
g
r
e
a
t
l
y
i
nc
r
e
a
s
e
s
t
he
r
obus
t
ne
s
s
of
c
ont
r
ol
in
L
F
C
P
.
T
he
r
e
-
f
or
e
,
i
n
r
e
c
e
nt
y
e
a
r
s
,
S
M
C
ha
s
be
e
n
us
e
d
i
n
v
a
r
i
ous
r
e
s
e
a
r
c
h
on
L
F
C
P
.
M
a
ny
a
ppl
i
c
a
t
i
ons
of
S
M
C
a
r
e
i
nt
r
oduc
e
d
in
[
12]
.
T
he
c
ha
t
t
e
r
i
n
g
pr
obl
e
m
of
S
M
C
is
r
e
j
e
c
t
e
d
due
to
t
he
s
uc
c
e
s
s
f
ul
i
m
pl
e
m
e
nt
a
t
i
on
of
s
e
c
ond
-
or
de
r
S
M
C
i
n
[
13]
.
A
s
e
c
ond
-
or
de
r
S
M
C
w
i
t
h
t
he
e
xt
e
nde
d
obs
e
r
v
e
r
i
s
us
e
d
f
or
r
ob
us
t
L
F
C
i
n
[
14]
.
F
ur
t
he
r
m
or
e
,
t
hi
r
d
-
or
de
r
S
M
C
w
i
t
h
s
t
a
t
e
obs
e
r
v
e
r
is
de
v
e
l
ope
d
in
[
15]
.
S
M
C
is
a
l
s
o
us
e
d
f
or
PS
w
i
t
h
t
he
c
oope
r
a
t
i
on
of
w
i
nd
pow
e
r
a
nd
t
i
m
e
-
de
l
a
y
c
ons
i
de
r
a
t
i
on
i
n
[
16]
.
R
e
s
e
a
r
c
h
i
n
[
17]
doe
s
t
he
s
a
m
e
t
hi
ng
but
t
ops
i
t
of
f
w
i
t
h
dr
oop
a
nd
pi
t
c
h
a
ng
l
e
c
ont
r
ol
t
he
n
pr
oc
e
e
ds
to
t
e
s
t
it
us
i
ng
t
he
I
E
E
E
39
bu
s
s
y
s
t
e
m
.
A
not
he
r
s
e
c
ond
-
or
de
r
S
M
C
w
i
t
h
a
da
pt
i
v
e
be
h
a
v
i
or
a
nd
c
o
m
m
uni
c
a
t
i
on
-
de
l
a
y
PS
is
i
n
v
e
s
t
i
g
a
t
e
d
in
[
18]
.
B
a
t
t
e
r
y
e
ne
r
gy
s
t
or
a
g
e
s
y
s
t
e
m
(
B
E
S
S
)
i
s
a
l
s
o
us
e
d
w
i
t
h
S
M
C
i
n
[
19]
.
C
l
a
s
s
i
c
a
l
S
M
C
i
s
f
ur
t
he
r
o
pt
i
m
i
z
e
d
b
y
s
m
a
r
t
a
l
g
or
i
t
h
m
s
s
uc
h
a
s
g
r
e
y
w
ol
f
opt
i
m
i
z
a
t
i
on
(
G
W
O
)
a
nd
pa
r
t
i
c
l
e
s
w
a
r
m
opt
i
m
i
z
a
t
i
on
(
P
S
O
)
in
[
20]
.
A
da
pt
i
v
e
hi
g
h
-
or
de
r
S
M
C
is
a
l
s
o
a
ppl
i
e
d
i
n
[
21]
.
L
i
ne
a
r
m
a
t
r
i
x
i
ne
qua
l
i
t
y
(
L
M
I
)
a
ppr
oa
c
h
f
or
t
he
dy
na
m
i
c
i
nt
e
gr
a
l
S
M
C
w
i
t
h
c
ons
i
de
r
a
t
i
on
of
t
i
m
e
de
l
a
y
i
s
r
e
s
e
a
r
c
he
d
in
[
22]
.
B
a
c
ks
t
e
ppi
ng
-
ba
s
e
d
S
M
C
is
pr
opos
e
d
in
[
23]
a
nd
c
o
m
pa
r
e
d
w
i
t
h
ot
he
r
a
d
v
a
nc
e
d
S
M
C
s
.
E
l
e
c
t
r
i
c
a
l
v
e
hi
c
l
e
a
gg
r
e
g
a
t
or
s
a
r
e
c
ons
i
de
r
e
d
f
or
L
F
C
P
in
[
24]
a
nd
m
odi
f
i
e
d
PSO
-
ba
s
e
d
I
nt
e
g
r
a
l
S
M
C
is
us
e
d.
A
H
∞
s
t
a
t
e
f
e
e
dba
c
k
f
o
r
S
M
C
w
i
t
h
de
l
a
y
e
d
c
o
m
m
uni
c
a
t
i
on
is
de
v
e
l
ope
d
in
[
25]
.
T
he
s
e
S
M
C
c
ont
r
ol
l
e
r
s
de
a
l
w
i
t
h
m
a
n
y
t
y
pe
s
of
L
F
C
pr
obl
e
m
s
a
nd
t
he
S
M
C
c
ont
r
ol
l
e
r
pr
obl
e
m
i
t
s
e
l
f
, pr
o
m
ot
i
ng
hi
g
h s
t
a
bi
l
i
t
y
of
t
he
P
S
.
T
hi
s
pa
pe
r
pr
o
v
i
de
s
a
t
hor
oug
h
r
e
s
e
a
r
c
h
of
t
he
l
a
t
e
s
t
i
m
pr
o
v
e
m
e
nt
s
i
n
S
M
C
f
or
L
F
C
P
,
w
i
t
h
a
c
on
-
c
e
nt
r
a
t
i
on
on
M
S
M
A
I
P
S
.
W
i
t
h
t
he
i
nt
e
g
r
a
t
i
on
of
m
a
ny
r
e
c
e
nt
hi
g
hl
y
i
nno
v
a
t
i
v
e
pi
e
c
e
s
of
r
e
s
e
a
r
c
h,
w
e
a
i
m
t
o
a
c
hi
e
v
e
a
c
ont
r
ol
l
e
r
t
ha
t
c
a
n
a
da
pt
t
o
m
a
ny
P
S
a
nd
f
i
x
t
he
S
M
C
c
ha
t
t
e
r
i
ng
pr
obl
e
m
s
f
or
opt
i
m
i
z
e
d
L
F
C
be
ha
v
i
or
.
2.
M
A
T
H
E
M
A
T
I
C
A
L
M
O
D
E
L
OF
T
W
O
-
S
O
U
R
C
E
,
M
U
L
T
I
-
A
R
E
A
P
O
WE
R
S
Y
S
T
E
M
T
he
e
x
a
m
i
ne
d
s
y
s
t
e
m
is
a
t
w
o
-
s
our
c
e
,
m
ul
t
i
-
a
r
e
a
pow
e
r
s
y
s
t
e
m
(
T
S
M
A
P
S
)
c
ons
i
s
t
i
n
g
of
t
w
o
g
e
ne
r
a
t
i
on
s
our
c
e
s
in
e
a
c
h
a
r
e
a
a
nd
a
t
ot
a
l
of
t
hr
e
e
a
r
e
a
s
.
F
i
g
ur
e
1
r
e
pr
e
s
e
nt
s
a
l
l
t
he
c
om
pone
nt
s
of
t
he
T
S
M
A
P
S
. T
he
s
ubs
e
c
t
i
ons
s
how
t
he
m
a
t
he
m
a
t
i
c
a
l
s
t
a
t
e
-
s
pa
c
e
e
xpr
e
s
s
i
ons
of
a
l
l
a
r
e
a
s
.
2.1.
A
r
e
a 1’
s
s
ys
t
e
m
m
od
e
l
A
c
ont
r
ol
a
r
e
a
w
i
t
hi
n
a
pow
e
r
s
y
s
t
e
m
of
t
e
n
i
nt
e
g
r
a
t
e
s
bot
h
t
he
r
m
a
l
(
w
i
t
h
a
non
-
r
e
he
a
t
t
ur
bi
ne
)
a
nd
hy
dr
o
g
e
ne
r
a
t
i
ng
uni
t
s
,
e
a
c
h
w
i
t
h
di
s
t
i
nc
t
dy
na
m
i
c
c
ha
r
a
c
t
e
r
i
s
t
i
c
s
.
W
hi
l
e
t
he
t
he
r
m
a
l
uni
t
pr
ov
i
de
s
a
s
i
m
pl
i
f
i
e
d
d
y
na
m
i
c
r
e
s
pons
e
,
t
he
h
y
dr
opo
w
e
r
pl
a
nt
of
f
e
r
s
r
a
pi
d
r
e
s
pons
e
c
a
pa
bi
l
i
t
i
e
s
e
s
s
e
nt
i
a
l
f
or
a
bs
or
bi
n
g
s
udde
n l
oa
d c
ha
ng
e
s
.
A
r
e
a
1’
s
dy
n
a
m
i
c
e
qu
a
t
i
ons
a
r
e
de
r
i
v
e
d be
l
ow
.
,
1
=
,
12
−
,
31
(
1)
̇
1
=
−
1
1
1
+
1
1
1
+
1
1
2
−
1
1
,
1
−
1
1
1
(
2)
̇
1
=
−
1
1
1
+
1
1
1
(
3)
̇
1
=
−
1
1
1
−
1
1
1
−
1
1
1
1
(
4)
̇
2
=
−
2
1
2
+
2
1
2
−
2
̇
2
(
5)
̇
2
=
−
1
1
2
+
1
1
2
+
1
1
̇
2
(
6)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
om
p S
c
i
I
S
S
N
:
2502
-
4752
L
oa
d
f
r
e
que
nc
y
c
ont
r
ol
f
or
m
ul
t
i
-
ar
e
a pow
e
r
s
y
s
t
e
m
w
i
t
h t
w
o
-
s
our
c
e
…
(
Q
uoc
T
hai
P
han
)
1451
̇
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−
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2
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1
−
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7)
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1
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12
+
31
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1
−
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2
−
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31
3
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1
2
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1
1
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1
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2
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2
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̇
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2
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1
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−
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1
)
2
+
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1
2
1
+
2
1
2
1
2
1
(
11)
F
i
g
ur
e
1.
S
t
a
t
e
-
s
pa
c
e
m
ode
l
of
t
he
T
S
M
A
P
S
pow
e
r
s
y
s
t
e
m
2.2.
A
r
e
a 2’
s
s
ys
t
e
m
m
od
e
l
T
he
r
e
h
e
a
t
t
he
r
m
a
l
uni
t
i
s
a
n
e
f
f
i
c
i
e
nt
ba
s
e
-
l
oa
d
g
e
ne
r
a
t
or
,
but
i
t
s
r
e
he
a
t
s
t
a
g
e
i
nt
r
oduc
e
s
a
s
l
ow
e
r
,
m
o
r
e
c
o
m
pl
e
x
d
y
na
m
i
c
r
e
s
pons
e
t
ha
n
a
non
-
r
e
he
a
t
t
ur
bi
ne
.
I
nt
e
g
r
a
t
i
ng
t
hi
s
s
l
ow
-
r
e
s
pondi
ng
pl
a
nt
w
i
t
h
a
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
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s
i
a
n J
E
l
e
c
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n
g
&
C
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p S
c
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,
V
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.
3
9
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3
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p
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1
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1452
f
a
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t
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o
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a
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d
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t
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F
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y
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oni
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e
t
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i
r
c
ont
r
a
s
t
i
ng
dy
na
m
i
c
s
.
T
h
e
dy
na
m
i
c
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qua
t
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ons
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r
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a
l
s
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r
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d be
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o
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.
,
2
=
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12
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1
3
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.
3
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13)
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2
2
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2
3
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2
4
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2
2
,
2
−
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2
2
(
14)
̇
3
=
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2
3
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3
(
15)
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3
=
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3
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3
2
−
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3
3
2
(
16)
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4
=
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2
4
+
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4
−
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.
4
(
17)
.
2
4
4
4
4
2
2
2
11
R
g
v
v
g
H
H
H
T
P
P
P
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T
T
(
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4
−
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2
−
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4
4
2
(
19)
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=
−
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1
3
+
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1
−
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2
)
3
+
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2
3
(
20)
̇
4
=
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4
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2
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2
4
)
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2
4
2
−
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4
2
4
2
(
21)
̇
4
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2
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2
2
4
2
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2
2
4
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4
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(
22)
,
3
,
3
1
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ti
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P
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P
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2.3.
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r
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ys
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m
m
od
e
l
T
he
g
a
s
po
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'
s
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ne
dy
na
m
i
c
s
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m
a
ke
s
i
t
a
n
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nv
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l
ua
bl
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our
c
e
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or
m
a
na
g
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ng
s
udde
n
l
oa
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f
l
uc
t
ua
t
i
on.
H
o
w
e
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e
r
,
t
hi
s
dy
na
m
i
c
i
nt
e
g
r
a
t
i
on
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nt
r
oduc
e
s
a
ne
w
l
a
ye
r
of
c
o
m
pl
e
xi
t
y
t
ha
t
m
us
t
be
r
i
g
or
ous
l
y
a
ddr
e
s
s
e
d t
o e
ns
ur
e
c
ont
r
ol
l
e
r
s
t
a
bi
l
i
t
y
.
T
h
e
e
qua
t
i
ons
of
t
hi
s
a
r
e
a
’
s
d
y
na
m
i
c
a
r
e
de
r
i
v
e
d be
l
o
w
.
̇
3
=
−
1
3
3
+
3
3
5
+
3
3
6
−
3
3
,
3
−
3
3
3
(
24)
̇
5
=
−
1
2
5
+
1
2
5
+
2
5
.
(
25)
̇
5
=
−
1
3
5
+
1
3
5
(
26)
̇
5
=
−
1
5
5
−
1
5
3
−
1
5
5
3
(
27)
̇
6
=
−
1
6
+
1
6
′
(
28)
̇
′
6
=
−
1
′
6
+
1
6
−
̇
6
(
29)
̇
6
=
−
1
6
+
1
6
+
̇
6
(
30)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
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p S
c
i
I
S
S
N
:
2502
-
4752
L
oa
d
f
r
e
que
nc
y
c
ont
r
ol
f
or
m
ul
t
i
-
ar
e
a pow
e
r
s
y
s
t
e
m
w
i
t
h t
w
o
-
s
our
c
e
…
(
Q
uoc
T
hai
P
han
)
1453
̇
6
=
−
6
−
1
3
−
1
6
3
(
31)
.
3
=
,
3
+
3
3
(
32)
̇
,
3
=
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31
−
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,
23
=
2
(
31
+
23
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3
−
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31
1
−
2
23
2
(
33)
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5
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2
5
+
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−
2
3
)
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3
5
(
34)
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=
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6
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(
35)
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′
=
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6
′
+
(
1
+
)
6
+
(
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+
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3
(
36)
3.
O
B
S
E
R
V
E
R
D
E
S
I
G
N
A
s
t
a
t
e
obs
e
r
v
e
r
is
a
c
ont
r
ol
m
e
c
ha
ni
s
m
t
ha
t
de
l
i
v
e
r
s
an
a
ppr
oxi
m
a
t
i
on
of
t
he
nu
m
e
r
i
c
a
l
i
nt
e
r
na
l
s
t
a
t
e
s
of
a
s
pe
c
i
f
i
c
r
e
a
l
s
y
s
t
e
m
,
T
S
M
A
P
S
i
n t
hi
s
s
c
e
na
r
i
o,
by
ut
i
l
i
z
i
ng
m
e
a
s
ur
e
m
e
nt
s
t
a
ke
n
f
r
om
bot
h
t
he
i
nput
a
nd
out
put
of
t
ha
t
s
y
s
t
e
m
. F
i
r
s
t
, s
t
a
t
e
-
s
pa
c
e
e
xpr
e
s
s
i
on of
t
he
s
y
s
t
e
m
i
s
e
xpr
e
s
s
e
d a
s
:
{
̇
(
)
=
(
)
+
(
)
+
∑
(
)
+
=
1
≠
(
)
=
(
)
(
37)
w
i
t
h,
is
a
s
t
a
t
e
v
e
c
t
or
w
i
t
h
p
s
t
a
t
e
v
a
r
i
a
bl
e
s
.
M
a
t
r
i
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e
s
w
i
t
h
di
m
e
ns
i
ons
of
p×
p.
i
s
a
c
on
t
r
ol
v
e
c
t
o
r
w
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t
h
m
c
ont
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ol
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a
r
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a
bl
e
s
.
M
a
t
r
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c
e
s
w
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h
di
m
e
n
s
i
ons
of
p
×
m
.
is
a
s
t
a
t
e
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e
c
t
o
r
c
o
nn
e
c
t
i
n
g
t
o
a
not
h
e
r
a
r
e
a
.
M
a
t
r
i
c
e
s
w
i
t
h
di
m
e
ns
i
ons
e
qu
a
l
to
t
he
s
t
a
t
e
v
a
r
i
a
bl
e
.
is
a
l
oa
d
di
s
t
u
r
b
a
n
c
e
v
e
c
t
o
r
w
i
t
h
g
l
o
a
d
d
i
s
t
ur
b
a
n
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e
v
a
r
i
a
bl
e
s
.
M
a
t
r
i
c
e
s
w
i
t
h
di
m
e
n
s
i
o
ns
of
p
×
g.
is
an
out
pu
t
v
e
c
t
o
r
w
i
t
h
h
o
ut
put
va
r
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a
bl
e
s
.
M
a
t
r
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c
e
s
w
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t
h
di
m
e
ns
i
o
ns
of
h×
p.
T
he
n,
s
t
a
t
e
-
s
pa
c
e
e
xpr
e
s
s
i
on
of
t
he
obs
e
r
v
e
r
is
e
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e
s
s
e
d
as
:
{
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(
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=
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(
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+
(
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+
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(
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+
[
(
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−
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(
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]
=
1
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(
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=
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(
38)
W
i
t
h
,
̂
(
t
)
is
t
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e
e
s
t
i
m
a
t
e
d
s
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t
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of
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)
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(
t
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t
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e
e
s
t
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m
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t
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s
t
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t
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of
(
t
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is
t
h
e
o
b
s
e
r
v
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r
g
a
i
n
.
4.
I
N
T
E
G
R
A
L
S
M
C
I
nt
e
g
r
a
l
s
l
i
di
ng
m
ode
c
ont
r
ol
(
I
S
M
C
)
w
i
t
h
a
s
t
a
t
e
e
s
t
i
m
a
t
or
is
a
r
obus
t
c
ont
r
ol
m
e
t
hod
to
e
n
ha
nc
e
t
h
e
s
t
a
bi
l
i
t
y
a
nd
pe
r
f
or
m
a
n
c
e
of
PS.
F
i
r
s
t
s
t
e
p
is
to
de
t
e
r
m
i
ne
t
he
i
nt
e
gr
a
l
s
l
i
di
ng
s
ur
f
a
c
e
(
I
S
S
)
.
T
he
ne
xt
s
t
e
p
is
t
he
c
ons
t
r
uc
t
i
on of
a
n e
qui
v
a
l
e
nt
c
ont
r
ol
l
a
w
a
nd
a
s
w
i
t
c
hi
ng
l
a
w
. F
i
na
l
l
y
, s
t
a
bi
l
i
t
y
a
na
l
y
s
i
s
of
t
he
c
ont
r
ol
s
i
g
na
l
.
T
he
I
S
S
w
i
t
h
e
s
t
i
m
a
t
e
d
s
t
a
t
e
is
g
i
v
e
n
a
s
:
[
̂
(
)
]
=
̂
(
)
−
∫
0
(
−
)
̂
(
)
(
39)
W
i
t
h,
m
a
t
r
i
c
e
s
i
s
c
hos
e
n
a
c
c
or
di
ng
l
y
t
o
e
ns
ur
e
t
ha
t
t
he
m
a
t
r
i
x
i
s
nons
i
ng
ul
a
r
or
i
nv
e
r
t
i
bl
e
.
T
he
r
e
f
o
r
e
,
m
a
t
r
i
x
c
a
n
b
e
c
ho
s
e
n
a
s
=
−
1
T
he
g
e
n
e
r
a
l
c
ont
r
ol
s
i
g
na
l
is
g
i
v
e
n
(
40)
.
(
)
(
)
(
)
e
q
sw
i
i
i
u
t
u
t
u
t
(
4
0
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
om
p S
c
i
,
V
ol
.
3
9
, N
o.
3
,
S
e
p
t
e
m
b
e
r
20
25
:
1
449
-
1
458
1454
W
i
t
h,
(
)
is
t
he
e
qu
i
v
a
l
e
nt
c
ont
r
ol
e
qua
t
i
o
n
(
E
C
E
)
to
e
ns
ur
e
t
ha
t
t
he
s
y
s
t
e
m
is
in
t
he
s
l
i
di
ng
s
ur
f
a
c
e
a
n
d
(
)
i
s
t
h
e
s
w
i
t
c
hi
ng
c
ont
r
ol
e
qua
t
i
on
t
ha
t
e
ns
ur
e
s
t
he
s
y
s
t
e
m
w
i
l
l
he
a
ds
t
ow
a
r
ds
a
nd
r
e
m
a
i
ns
on
t
he
s
l
i
di
ng
s
ur
f
a
c
e
.
F
r
om
(
39
)
w
h
e
n
(
)
=
̇
(
)
=
0
,
t
h
e
E
C
E
b
e
c
o
m
e
s
:
(
)
=
−
(
)
−
1
[
∑
̂
(
)
+
[
(
)
−
̂
(
)
]
=
1
≠
1
+
̂
(
)
]
(
41)
T
he
s
w
i
t
c
hi
ng
c
ont
r
ol
oc
c
ur
s
w
he
n:
(
)
=
−
[
[
̂
(
)
]
]
(
42)
:
p
os
i
t
i
v
e
c
ons
t
a
nt
(
>
0
)
.
T
hi
s
f
a
c
t
or
he
l
ps
t
o
a
dj
us
t
t
he
c
onv
e
r
ge
nc
e
s
pe
e
d
of
t
he
s
y
s
t
e
m
.
T
h
e
s
a
t
ur
a
t
i
on c
ondi
t
i
on t
ha
t
he
l
ps
r
e
duc
e
c
ha
t
t
e
r
i
ng
e
f
f
e
c
t
i
s
g
i
v
e
n
(
43)
.
[
[
̂
(
)
]
]
=
{
−
1
[
̂
(
)
]
<
(
−
1
)
[
̂
(
)
]
(
−
1
)
<
[
̂
(
)
]
<
1
1
[
̂
(
)
]
>
1
(
43)
S
ubs
t
i
t
ut
e
(
43)
a
nd
(
44)
i
nt
o
(
42)
,
we
w
i
l
l
ha
v
e
t
he
g
e
ne
r
a
l
c
ont
r
ol
s
i
g
na
l
is
g
i
v
e
n
be
l
ow
:
(
)
=
−
(
)
−
1
[
∑
̂
(
)
+
[
(
)
−
̂
(
)
]
=
1
≠
1
+
̂
(
)
+
(
[
̂
(
)
]
]
(
44)
U
s
i
ng
(
44)
w
e
w
i
l
l
ha
v
e
(
)
̇
(
)
<
0
.
T
hi
s
c
ondi
t
i
on
w
i
l
l
e
ns
ur
e
t
ha
t
t
he
v
a
l
ue
of
(
)
w
i
l
l
de
c
r
e
a
s
e
o
v
e
r
t
i
m
e
, t
he
r
e
b
y
e
ns
ur
i
ng
t
ha
t
t
he
s
l
i
di
ng
m
ot
i
on w
i
l
l
be
a
s
ym
pt
ot
i
c
a
l
l
y
s
t
a
bl
e
o
v
e
r
t
i
m
e
.
5.
S
I
M
U
L
A
T
I
O
N
R
E
S
U
L
T
S
A
N
D
D
I
S
C
U
S
S
I
O
N
T
he
s
i
m
ul
a
t
i
on
w
i
l
l
pr
o
v
i
de
t
he
pr
opos
e
d
c
ont
r
ol
l
e
r
s
’
r
e
s
pons
e
w
i
t
h
a
c
o
m
pa
r
i
s
on
of
ot
he
r
c
ont
r
ol
l
e
r
s
s
uc
h
a
s
P
I
D
a
nd
I
S
M
C
.
A
r
e
a
s
of
P
S
m
ode
l
a
r
e
i
nt
r
oduc
e
d
t
o
a
l
oa
d
di
s
t
ur
ba
nc
e
of
f
ol
l
ow
s
:
1
=
0
.
02
(
p.u.M
W
)
,
2
=
0
.
04
(
p.u.M
W
)
,
3
=
0
.
03
(
p.u.M
W
)
at
t
he
t
i
m
e
=
0
.
F
i
g
ur
e
s
2
t
o
4
s
how
t
he
c
ha
nge
in
f
r
e
que
nc
y
of
a
r
e
a
s
r
e
s
pe
c
t
i
v
e
l
y
to
t
hr
e
e
a
r
e
a
s
.
F
i
g
ur
e
s
5
t
o
7
s
how
t
he
c
ha
ng
e
i
n
t
i
e
-
l
i
ne
pow
e
r
of
t
he
a
r
e
a
s
.
I
t
c
a
n
be
s
e
e
n
t
ha
t
t
he
f
r
e
que
nc
y
de
v
i
a
t
i
on
of
t
he
T
S
M
A
P
S
us
i
ng
t
he
S
O
I
S
M
C
c
ont
r
o
l
l
e
r
,
I
S
M
C
,
a
nd
t
he
L
Q
R
m
e
t
hod
i
s
w
i
t
hi
n
t
he
a
l
l
ow
a
bl
e
r
a
ng
e
a
nd
a
c
hi
e
v
e
s
opt
i
m
a
l
c
ont
r
ol
e
f
f
i
c
i
e
nc
y
.
T
h
e
d
i
f
f
e
r
e
n
c
e
m
a
i
nl
y
f
ol
l
ow
s
t
he
t
r
e
nd:
T
he
P
I
D
c
ont
r
ol
l
e
r
c
onv
e
r
g
e
s
to
z
e
r
o.
T
he
I
S
M
C
a
nd
S
O
I
S
M
C
g
i
v
e
out
a
l
a
r
g
e
r
s
pi
ke
t
ha
n
P
I
D
i
n
a
r
e
a
s
1
a
nd
3
(
m
a
x
of
P
I
D
i
s
a
t
-
0.14
H
z
i
n
a
r
e
a
2)
i
n
t
he
i
ns
t
a
nc
e
l
oa
d
di
s
t
ur
ba
nc
e
i
s
i
nt
r
oduc
e
d.
N
e
v
e
r
t
he
l
e
s
s
, t
he
S
M
C
c
ont
r
ol
l
e
r
s
os
c
i
l
l
a
t
e
l
e
s
s
i
n t
hr
e
e
a
r
e
a
s
, r
e
a
c
h
t
he
s
t
a
bi
l
i
z
e
d s
t
a
t
e
,
a
nd s
t
a
y
t
he
r
e
m
or
e
s
t
a
bl
e
t
ha
n P
I
D
.
F
i
g
ur
e
2.
A
r
e
a
1’
s
f
r
e
que
nc
y
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
om
p S
c
i
I
S
S
N
:
2502
-
4752
L
oa
d
f
r
e
que
nc
y
c
ont
r
ol
f
or
m
ul
t
i
-
ar
e
a pow
e
r
s
y
s
t
e
m
w
i
t
h t
w
o
-
s
our
c
e
…
(
Q
uoc
T
hai
P
han
)
1455
T
he
c
ha
n
g
e
i
n t
i
e
-
l
i
ne
pow
e
r
o
f
t
hr
e
e
a
r
e
a
s
g
i
v
e
s
out
i
nt
e
r
e
s
t
i
ng f
e
a
t
ur
e
s
. D
e
s
pi
t
e
t
he
r
obus
t
ne
s
s
a
nd
f
a
s
t
r
e
a
c
t
i
v
i
t
y
of
S
M
C
,
P
I
D
s
t
a
bi
l
i
z
e
s
a
nd
r
e
a
c
he
s
s
t
a
bi
l
i
t
y
of
t
i
e
-
l
i
ne
f
a
s
t
e
r
w
i
t
h
f
e
w
e
r
os
c
i
l
l
a
t
i
o
n
s
(
20
s
of
P
I
D
c
o
m
pa
r
e
d
w
i
t
h 40
s
of
S
M
C
s
)
. T
he
a
r
e
a
o
f
hi
g
hl
y
c
o
m
pl
e
x pl
a
nt
s
(
a
r
e
a
3)
g
i
v
e
s
out
m
uc
h
m
or
e
v
i
g
or
ous
s
t
a
bi
l
i
z
a
t
i
on of
t
he
t
i
e
-
l
i
ne
, m
a
ki
ng
S
M
C
c
ont
r
ol
l
e
r
s
o
v
e
r
s
hoot
a
nd unde
r
s
hoot
r
e
a
c
hi
ng
s
t
a
bi
l
i
t
y
.
F
i
g
ur
e
3.
A
r
e
a
2’
s
f
r
e
que
nc
y
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
F
i
g
ur
e
4.
A
r
e
a
3’
s
f
r
e
que
nc
y
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
F
i
g
ur
e
5
.
A
r
e
a
1
’s
tie
-
l
i
ne
po
w
e
r
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
ndone
s
i
a
n J
E
l
e
c
E
n
g
&
C
om
p S
c
i
,
V
ol
.
3
9
, N
o.
3
,
S
e
p
t
e
m
b
e
r
20
25
:
1
449
-
1
458
1456
F
i
g
ur
e
6.
A
r
e
a
2’
s
tie
-
l
i
ne
pow
e
r
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
F
i
g
ur
e
7
.
A
r
e
a
3
’s
tie
-
l
i
ne
po
w
e
r
de
v
i
a
t
i
on
us
i
ng
t
hr
e
e
c
ont
r
o
l
l
e
r
s
6.
C
O
N
C
L
U
S
I
O
N
T
hi
s
a
r
t
i
c
l
e
of
f
e
r
s
a
de
t
a
i
l
e
d
e
xa
m
i
n
a
t
i
on
of
S
M
C
us
e
d
f
or
L
F
C
i
n
a
c
om
bi
ne
d
m
ul
t
i
-
s
our
c
e
s
pow
e
r
s
y
s
t
e
m
.
T
h
r
oug
h t
hor
ou
g
h s
i
m
ul
a
t
i
ons
a
nd e
v
a
l
ua
t
i
ons
of
pe
r
f
or
m
a
nc
e
,
nu
m
e
r
ous
i
m
por
t
a
n
t
di
s
c
o
v
e
r
i
e
s
ha
v
e
hi
g
hl
i
g
ht
e
d
t
he
e
f
f
e
c
t
i
v
e
ne
s
s
of
S
O
I
S
M
C
.
F
i
r
s
t
l
y
,
S
O
I
S
M
C
s
how
e
d
be
t
t
e
r
r
e
s
i
l
i
e
nc
e
i
n
pr
e
s
e
r
v
i
n
g
s
y
s
t
e
m
f
r
e
que
nc
y
s
t
a
bi
l
i
t
y
t
ha
n
t
r
a
di
t
i
o
na
l
c
ont
r
ol
a
ppr
oa
c
he
s
.
F
ur
t
he
r
m
o
r
e
,
t
he
S
O
I
S
M
C
a
ppr
oa
c
h
s
uc
c
e
s
s
f
ul
l
y
i
nt
e
g
r
a
t
e
d
h
y
dr
o
a
nd
t
he
r
m
a
l
po
w
e
r
pl
a
nt
s
i
n
a
s
i
ng
l
e
c
ont
r
ol
f
r
a
m
e
w
or
k.
T
hi
s
c
o
m
bi
na
t
i
on,
a
l
ong
w
i
t
h
t
he
s
i
m
ul
a
t
i
on s
how
s
t
ha
t
t
he
s
ugg
e
s
t
e
d c
ont
r
ol
a
ppr
oa
c
h s
uc
c
e
s
s
f
ul
l
y
m
i
ni
m
i
z
e
s
t
he
f
r
e
que
nc
y
v
a
r
i
a
t
i
ons
de
s
pi
t
e
c
ha
ng
i
n
g
l
oa
d c
ondi
t
i
ons
a
nd di
s
t
ur
ba
nc
e
s
, a
nd
g
ua
r
a
nt
e
e
s
t
ha
t
bot
h ki
nds
of
pow
e
r
pl
a
nt
s
c
a
n e
f
f
e
c
t
i
v
e
l
y
a
i
d
i
n
f
r
e
que
n
c
y
r
e
g
ul
a
t
i
on,
e
nha
nc
i
ng
t
he
s
y
s
t
e
m
’
s
o
v
e
r
a
l
l
pe
r
f
or
m
a
nc
e
.
T
o
s
u
m
up,
t
he
S
O
I
S
M
C
t
e
c
hni
que
i
s
s
how
n
t
o
be
a
s
t
r
ong
a
nd
de
pe
nda
bl
e
a
ppr
oa
c
h
f
or
r
e
g
ul
a
t
i
ng
t
he
be
ha
v
i
or
of
po
w
e
r
s
y
s
t
e
m
s
t
ha
t
i
nc
l
ude
s
hy
dr
o
a
nd
t
he
r
m
a
l
pow
e
r
pl
a
nt
s
.
T
hi
s
s
t
udy
of
f
e
r
s
v
a
l
ua
bl
e
pe
r
s
pe
c
t
i
v
e
s
on
i
m
pr
o
v
i
ng
t
he
s
t
a
bi
l
i
t
y
a
nd
e
f
f
i
c
i
e
nc
y
of
S
M
C
-
ba
s
e
d
c
ont
r
ol
l
e
r
s
,
w
hi
c
h
w
i
l
l
r
e
s
ul
t
i
n
m
or
e
r
obus
t
a
nd
f
l
e
xi
bl
e
e
n
e
r
gy
m
a
na
g
e
m
e
n
t
t
a
c
t
i
c
s
i
n
t
he
f
ut
ur
e
.
P
os
s
i
bl
e
f
ur
t
he
r
w
o
r
k
s
houl
d
i
nc
l
ude
i
m
pl
e
m
e
nt
a
t
i
on
of
ha
r
d
w
a
r
e
-
r
e
l
a
t
e
d
S
M
C
-
ba
s
e
d
c
ont
r
ol
l
e
r
s
s
o a
s
t
o pr
e
c
i
s
e
l
y
t
e
s
t
a
nd
v
e
r
i
f
y
t
he
de
s
i
g
n
e
d c
ont
r
ol
l
e
r
s
.
F
U
N
D
I
N
G
I
N
F
O
R
M
A
T
I
O
N
A
ut
hor
s
s
t
a
t
e
no f
undi
ng
i
n
v
ol
v
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opt
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d
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c
y
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ont
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r
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nn
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de
c
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t
r
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l
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z
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d
f
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c
y
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on
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r
ol
of
m
ul
t
i
-
m
i
c
r
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g
r
i
d
s
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SE
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J
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nal
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y
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on
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r
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n
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on
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I
+
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O
P
D
c
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n
t
r
ol
l
e
r
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”
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nt
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r
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f
r
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c
y
c
o
n
t
r
ol
of
a
m
ul
t
i
-
a
r
e
a
pow
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r
s
ys
t
e
m
:
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n
a
da
pt
i
ve
f
u
z
z
y
l
o
g
i
c
a
ppr
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t
r
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but
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d
m
ode
l
pr
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di
c
t
i
ve
l
oa
d
f
r
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que
n
c
y
c
o
n
t
r
ol
of
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h
e
m
ul
t
i
-
a
r
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a
po
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s
ys
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m
a
f
t
e
r
de
r
e
g
u
l
a
t
i
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n,
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E
E
T
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l
oa
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f
r
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que
n
c
y
c
o
n
t
r
ol
l
e
r
f
or
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n
t
e
r
c
o
nne
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t
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d
po
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f
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ul
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t
i
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of
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gh
-
pe
n
e
t
r
a
t
i
o
n
r
e
n
e
w
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bl
e
e
n
e
r
g
y
m
i
c
r
o
g
r
i
ds
us
i
ng
a
da
pt
i
ve
m
ode
l
pr
e
di
c
t
i
ve
c
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r
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M
I
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f
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y
c
ont
r
ol
f
o
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t
i
m
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de
l
a
ye
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po
w
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s
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m
vi
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de
l
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y
m
a
r
g
i
n
e
s
t
i
m
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”
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r
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T
r
i
gg
e
r
i
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oa
d
f
r
e
q
ue
n
c
y
c
o
nt
r
ol
f
or
m
u
l
t
i
a
r
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a
po
w
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r
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m
s
w
i
t
h
c
om
m
u
n
i
c
a
t
i
o
n
de
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ys
,
”
I
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E
E
T
r
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A
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Sl
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ont
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ol
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obs
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r
v
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on
.
N
e
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Y
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l
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f
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n
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t
r
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c
h
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di
s
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ur
ba
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obs
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ve
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E
T
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r
ol
f
or
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ul
t
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t
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m
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l
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y
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m
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h
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d
po
w
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r
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n
t
e
gr
a
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ont
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f
o
r
f
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e
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n
c
y
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ul
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t
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o
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pe
e
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d
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I
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nat
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o
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s
l
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di
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ode
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o
n
t
r
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i
gn
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y
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m
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ol
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y
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l
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ode
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our
nal
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n
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A
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s
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s
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ol
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