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Adv
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Vo
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Dec
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201
5
,
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.
135
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I
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I
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2
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8814
IJ
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Vo
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4
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No
.
4
,
Dec
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b
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201
5
:
1
3
5
–
1
4
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136
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MP
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v
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s
[
1
7
]
.
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[
4
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P
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n
t
h
e
co
n
tr
o
l
s
y
s
te
m
a
n
d
th
e
p
r
o
ce
s
s
f
ield
d
e
v
i
ce
s
u
s
i
n
g
p
r
o
f
ib
u
s
-
P
A
a
n
d
p
r
o
f
ib
u
s
-
DP
.
A
P
L
C
w
a
s
u
s
ed
to
co
n
tr
o
l th
e
p
lan
t [
5
]
.
A
co
n
tr
o
l stra
te
g
y
w
as d
e
v
elo
p
ed
to
co
n
tr
o
l a
co
n
tin
u
o
u
s
p
o
l
y
m
er
izatio
n
r
ea
cto
r
an
d
i
ts
p
e
r
f
o
r
m
an
c
e
w
a
s
ev
al
u
ated
u
s
i
n
g
s
i
m
u
latio
n
s
[
6
]
.
Dan
A
lte
n
a
et
al.
,
ap
p
lied
ad
v
an
ce
d
m
u
l
ti
v
ar
iab
le
co
n
tr
o
l
o
n
a
n
atu
r
al
g
as
p
la
n
t
a
n
d
it
s
p
er
f
o
r
m
a
n
c
e
w
a
s
co
m
p
ar
ed
w
i
th
th
e
co
n
v
e
n
tio
n
al
f
ee
d
b
ac
k
co
n
tr
o
ller
s
.
T
h
is
p
ap
er
also
f
o
cu
s
ed
o
n
co
n
tr
o
l stra
teg
y
f
o
r
co
m
p
le
x
tu
r
b
o
ex
p
an
d
er
p
r
o
ce
s
s
[
7
]
.
D
y
n
a
m
ic
m
atr
i
x
co
n
tr
o
l
(
DM
C
)
s
ch
e
m
e
w
as
u
s
ed
f
o
r
a
d
r
u
m
b
o
iler
tu
r
b
in
e.
An
in
te
lli
g
en
ce
b
ased
d
ec
is
io
n
m
ec
h
an
is
m
(
I
B
DM
)
w
a
s
i
m
p
le
m
en
ted
w
h
ich
s
u
p
p
o
r
ted
b
o
th
m
o
d
el
ap
p
r
o
ac
h
a
n
d
co
n
tr
o
l
s
ch
e
m
e
[
8
]
.
R
.
Han
u
m
a
Naik
et
al.
,
[
9
]
d
ev
elo
p
e
d
d
ec
en
tr
alize
d
c
o
n
tr
o
ller
f
o
r
m
u
lti
v
ar
iab
le
p
r
o
c
ess
b
ased
o
n
R
G
A
an
d
Neid
er
li
n
s
k
i
i
n
d
ex
a
n
al
y
s
is
.
An
alg
o
r
it
h
m
w
a
s
d
ev
el
o
p
ed
b
y
i
n
te
g
r
atio
n
o
f
m
u
lti
r
eso
lu
tio
n
a
n
al
y
s
i
s
(
MR
A
)
an
d
p
r
in
cip
al
cu
r
v
es (
P
C
)
f
o
r
co
n
tr
o
llin
g
m
u
lti
v
ar
ia
b
le
p
r
o
ce
s
s
es [
1
0
]
.
2.
P
L
ANT M
O
DE
L
AN
D
I
T
S
M
UL
T
I
VARI
AB
L
E
A
NAL
YSI
S
T
h
e
tr
an
s
f
er
f
u
n
ctio
n
m
o
d
el
o
f
th
e
co
n
s
id
er
ed
cr
u
s
h
i
n
g
m
ill
i
n
g
p
la
n
t is
s
h
o
w
n
in
F
ig
u
r
e
2
.
*
τ
+
[
-
-
-
-
]
*
+
Fig
u
r
e
2
.
T
r
an
s
f
er
f
u
n
ctio
n
o
f
cr
u
s
h
in
g
m
ill
[
1
1
]
W
h
er
e
th
e
co
n
tr
o
lled
v
ar
iab
le
s
τ
(
t)
an
d
h
(
t)
ar
e
t
h
e
m
ill
to
r
q
u
e
an
d
b
u
f
f
er
c
h
u
te
h
ei
g
h
t
r
esp
ec
tiv
el
y
an
d
t
h
e
m
an
ip
u
lated
v
ar
iab
les
f
(
t)
an
d
Ω
(
t)
a
r
e
f
lap
p
o
s
itio
n
an
d
tu
r
b
in
e
s
p
ee
d
s
et
p
o
in
t
r
esp
ec
tiv
el
y
.
T
h
e
o
p
en
lo
o
p
s
tep
r
esp
o
n
s
e
o
f
t
h
is
m
o
d
el
is
s
h
o
w
n
in
F
ig
u
r
e
3
.
I
t
s
h
o
w
s
t
h
at
t
h
e
p
air
in
g
s
t
u
r
b
in
e
s
p
ee
d
-
m
il
l
to
r
q
u
e
an
d
tu
r
b
in
e
s
p
ee
d
-
b
u
f
f
er
ch
u
te
h
ei
g
h
t
ex
h
ib
it
a
n
in
v
er
s
e
r
esp
o
n
s
e.
T
h
is
f
ea
t
u
r
e
m
ak
e
s
it
d
i
f
f
ic
u
lt
to
ac
h
ie
v
e
ac
cu
r
ate,
in
d
ep
en
d
en
t
co
n
tr
o
l
o
f
th
e
t
w
o
co
n
tr
o
lled
v
ar
iab
les.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Mu
ltil
o
o
p
a
n
d
P
r
ed
ictio
n
B
a
s
ed
C
o
n
tr
o
ller
Desig
n
fo
r
S
u
g
a
r
ca
n
e
C
r
u
s
h
in
g
Mil
l…
(
S
a
n
d
ee
p
K
u
ma
r
S
u
n
o
r
i
)
137
Fig
u
r
e
3
.
Op
en
lo
o
p
s
tep
r
esp
o
n
s
e
o
f
cr
u
s
h
in
g
m
ill
m
o
d
el
B
ef
o
r
e
d
esig
n
i
n
g
th
e
m
u
l
tilo
o
p
co
n
tr
o
ller
f
o
r
th
e
co
n
s
id
er
ed
p
lan
t
th
e
s
u
itab
le
p
air
in
g
b
et
w
ee
n
m
an
ip
u
lated
an
d
co
n
tr
o
l
v
ar
ia
b
les
is
d
o
n
e
b
y
d
eter
m
i
n
i
n
g
t
h
e
r
elativ
e
g
a
in
ar
r
a
y
(
R
G
A
)
[
1
4
]
.
C
o
n
s
id
er
th
e
s
tead
y
s
tate
m
o
d
el
o
f
a
2
x
2
MI
MO
p
lan
t.
*
+
[
]
*
+
(
1
)
W
h
er
e
u
1
,
u
2
ar
e
m
a
n
ip
u
lated
v
ar
iab
les
a
n
d
y
1
,
y
2
ar
e
co
n
t
r
o
lled
v
ar
iab
les
.
T
h
e
s
tead
y
s
tate
g
ai
n
m
atr
i
x
i
s
g
iv
e
n
b
y
:
[
]
(
2
)
No
w
t
h
e
R
G
A
i
s
ex
p
r
es
s
ed
as:
R
G
A
=
[
]
(
3
)
W
h
er
e
λ
12
= λ
21
= 1
-
λ
11
a
n
d
λ
22
=
λ
11
an
d
,
(
4
)
I
f
λ
12
< λ
11
th
e
n
s
u
itab
le
p
air
in
g
i
s
u
1
-
y
1
an
d
u
2
-
y
2
else it
is
u
1
-
y
2
a
n
d
u
2
-
y
1.
Usi
n
g
E
q
u
at
io
n
(
1
)
-
(
4
)
lets
f
i
n
d
o
u
t
R
G
A
f
o
r
th
e
co
n
s
id
er
ed
p
lan
t.Fo
r
th
i
s
p
lan
t
t
h
e
s
tead
y
s
tate
g
ai
n
m
atr
i
x
is
g
iv
e
n
b
elo
w
:
*
+
(
5
)
Usi
n
g
r
elatio
n
s
(
3
)
,
(
4
)
an
d
(
5
)
,
th
e
R
G
A
i
s
d
eter
m
i
n
ed
as:
*
+
(
6
)
T
h
is
R
G
A
s
u
g
g
es
ts
t
h
at
t
h
e
s
u
itab
le
p
air
in
g
is
u
1
-
y
1
a
n
d
u
2
-
y
2.
T
h
e
s
ec
o
n
d
p
ar
a
m
eter
is
th
e
Nied
er
lin
s
k
i
i
n
d
ex
[
1
2
]
w
h
ic
h
d
eter
m
i
n
e
s
t
h
e
clo
s
ed
lo
o
p
s
tab
ilit
y
o
f
th
e
co
n
tr
o
l s
y
s
te
m
.
I
t is ca
lc
u
l
ated
u
s
i
n
g
t
h
e
f
o
llo
w
i
n
g
r
elati
o
n
(
7
)
Th
e
MI
MO
s
y
s
te
m
w
ill b
e
u
n
s
tab
le
f
o
r
all
p
o
s
s
ib
le
v
al
u
es o
f
co
n
tr
o
ller
p
ar
a
m
eter
s
i
f
N
<
0
[
1
2
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8814
IJ
AA
S
Vo
l.
4
,
No
.
4
,
Dec
em
b
er
201
5
:
1
3
5
–
1
4
5
138
No
w
u
s
i
n
g
E
q
u
atio
n
(
7
)
,
th
e
Neid
er
lin
s
k
i i
n
d
ex
f
o
r
th
is
p
la
n
t is d
eter
m
in
ed
as:
|
|
(
8
)
Hen
ce
f
o
r
th
is
p
lan
t N
>
0
w
h
i
ch
in
d
icate
s
th
a
t th
e
s
y
s
te
m
i
s
clo
s
ed
lo
o
p
s
tab
le.
3.
CO
NT
RO
L
L
E
R
DE
SI
G
N
No
w
t
h
e
m
u
ltil
o
o
p
co
n
tr
o
ller
f
o
r
th
i
s
p
lan
t
w
ill b
e
d
esi
g
n
ed
u
s
i
n
g
Mc
Av
o
y
p
r
o
ce
d
u
r
e
[
1
5
]
f
o
r
a
2
x
2
s
y
s
te
m
.
A
s
p
er
t
h
i
s
m
eth
o
d
a
n
y
o
f
s
i
n
g
le
lo
o
p
tu
n
in
g
r
u
le
s
eg
.,
Z
ie
g
ler
-
Nic
h
o
les,
C
o
h
e
n
-
C
o
o
n
,
etc
ca
n
b
e
f
ir
s
t
u
s
ed
to
o
b
tain
th
e
in
itial
K
p
an
d
K
i
v
al
u
es
o
f
t
h
e
t
w
o
P
I
co
n
tr
o
ller
s
f
o
r
u
1
-
y
1
lo
o
p
(
a
s
s
u
m
in
g
u
2
=0
)
an
d
u
2
-
y
2
lo
o
p
(
ass
u
m
in
g
u
1
=0
)
.
As
s
u
m
e,
a
f
ter
th
i
s
t
u
n
in
g
t
h
e
v
a
lu
e
o
f
K
p
co
m
e
s
o
u
t
to
b
e
K
p
*.
.
No
w
th
e
t
w
o
P
I
co
n
tr
o
ller
s
f
o
r
th
e
co
n
s
id
er
ed
2
x
2
MI
MO
s
y
s
te
m
w
i
ll b
e
tu
n
ed
u
s
in
g
t
h
e
f
o
llo
w
i
n
g
r
elatio
n
[
1
6
]
,
{
(
√
(
)
)
|
√
(
)
|
(
9
)
Her
e,
λ
b
ein
g
t
h
e
r
elativ
e
g
ai
n
p
ar
am
eter
w
h
ich
i
s
λ
11
ele
m
e
n
t o
f
t
h
e
R
G
A
.
T
h
e
r
esp
o
n
s
e
co
u
ld
b
e
f
ir
s
t
i
m
p
r
o
v
ed
b
y
t
h
e
co
n
t
in
u
ed
ad
j
u
s
t
m
e
n
t
o
n
t
h
e
tu
n
i
n
g
p
ar
a
m
et
er
.
No
w
f
o
r
th
e
co
n
s
id
er
ed
p
lan
t
,
t
h
e
t
u
n
e
d
v
alu
e
s
o
f
K
p
a
n
d
Ki
f
o
r
u
1
-
y
1
lo
o
p
(
SISO1
)
an
d
u
2
-
y
2
lo
o
p
(
SISO2
)
ar
e
f
o
u
n
d
to
b
e
(
K
p1
*
=
-
0
.
0
9
4
6
,
K
i1
=
-
0
.
0
1
2
8
)
an
d
(
K
p2
*
=
-
3
7
6
.
5
3
2
8
,
K
i2
=
-
2
1
7
.
3
9
1
3
)
r
esp
ec
tiv
ely
.
T
h
e
clo
s
ed
lo
o
p
s
tep
r
esp
o
n
s
e
o
f
SISO1
s
y
s
te
m
is
s
h
o
w
n
i
n
F
i
g
u
r
e
4
.
T
h
e
ch
ar
ac
ter
s
tics
o
f
t
h
is
r
e
s
p
o
n
s
e
ar
e
p
r
esen
ted
in
T
ab
le
1
.
Fig
u
r
e
4
.
C
lo
s
ed
lo
o
p
s
tep
r
es
p
o
n
s
e
o
f
SISO1
s
y
s
te
m
T
ab
le
1
.
C
lo
s
ed
lo
o
p
s
tep
r
esp
o
n
s
e
ch
ar
ac
ter
s
t
ics o
f
SI
SO1
s
y
s
te
m
Pa
r
a
m
e
t
e
r
V
a
l
u
e
R
i
se
t
i
me
(
se
c
)
3
2
.
5
S
e
t
t
e
l
i
n
g
t
i
me
(
se
c
)
1
0
8
O
v
e
r
sh
o
o
t
(
%)
1
1
.
6
P
e
a
k
a
m
p
l
i
t
u
d
e
1
.
1
2
T
h
e
clo
s
ed
lo
o
p
s
tep
r
esp
o
n
s
e
o
f
SISO2
s
y
s
te
m
i
s
s
h
o
w
n
in
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s
r
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e
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r
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ted
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2
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Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Mu
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n
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2
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e
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4
3
O
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k
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e
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u
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e
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m
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li
n
k
m
o
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el
o
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ltil
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o
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n
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ller
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ith
t
h
ese
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itia
l
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al
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e
s
f
o
r
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I
co
n
tr
o
ller
s
,
th
e
m
u
lti
lo
o
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co
n
tr
o
l
s
y
s
te
m
u
s
i
n
g
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Av
o
y
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r
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ce
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e
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n
o
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m
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u
s
i
n
g
M
A
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L
A
B
s
i
m
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lin
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h
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co
r
r
esp
o
n
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in
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m
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li
n
k
m
o
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el
is
s
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o
w
n
i
n
F
i
g
u
r
e
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.
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w
u
s
i
n
g
t
h
e
Mc
Av
o
y
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le
o
f
d
etu
n
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n
g
g
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en
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y
E
q
u
atio
n
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9
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o
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ly
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n
e
ti
m
e
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t
h
th
e
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eter
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ted
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3
o
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ly
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ti
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e
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e
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to
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e
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al
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0
7
8
6
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d
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3
1
2
.
7
5
2
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w
h
ic
h
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v
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e
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n
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e
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it
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ep
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as sh
o
w
n
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n
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g
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r
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T
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le
3
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ar
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o
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e
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l
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6
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0
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2
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3
7
6
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5
3
2
8
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2
1
7
.
3
9
1
3
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8814
IJ
AA
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4
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5
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3
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Fig
u
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esp
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n
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t)
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d
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er
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r
ig
h
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o
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g
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h
e
co
n
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n
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ed
Mc
Av
o
y
ad
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en
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m
e
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h
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al
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e
o
f
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0
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0
3
7
4
an
d
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1
4
8
.
8
5
4
.
T
h
is
r
esu
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n
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i
m
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r
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ep
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le
r
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e
as
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ig
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r
e
8
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Fig
u
r
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m
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r
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r
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f
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n
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ig
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v
e
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et
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e
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Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Mu
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ig
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r
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el
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th
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m
o
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in
F
ig
u
r
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.
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)
]
(
)
[
(
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(
1
4
)
[
(
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)
[
(
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(
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]
(
1
5
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e
v
1
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s
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d
v
2
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ar
e
th
e
o
u
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o
f
t
h
e
t
w
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n
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o
f
F
ig
u
r
e
9
.
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o
m
b
i
n
in
g
E
q
u
atio
n
(
1
4
)
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d
(
1
5
)
w
e
g
e
t:
[
(
)
(
)
]
(
)
(
)
[
(
)
(
)
]
(
1
6
)
Wh
ich
g
iv
e
s
t
h
e
f
o
llo
w
i
n
g
r
es
u
lts
:
(
)
*
(
)
(
)
(
)
(
)
+
(
)
(
1
7
)
(
)
*
(
)
(
)
(
)
(
)
+
(
)
(
1
8
)
T
h
u
s
w
e
g
e
t
t
w
o
in
d
ep
en
d
en
t
d
ec
o
u
p
led
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y
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te
m
s
v
1
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led
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d
v
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y
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u
p
led
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)
w
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h
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ai
n
s
G
1
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d
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2
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.
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h
e
ex
p
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n
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r
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1
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d
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2
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eter
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ed
u
s
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n
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E
q
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atio
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d
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e
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:
(
)
(
1
9
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(
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(
2
0
)
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h
e
o
p
en
lo
o
p
s
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r
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o
n
s
es o
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th
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e
t
w
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p
led
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y
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te
m
s
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e
s
h
o
w
n
i
n
F
i
g
u
r
e
1
0
an
d
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ig
u
r
e
1
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8814
IJ
AA
S
Vo
l.
4
,
No
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4
,
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b
er
201
5
:
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3
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1
4
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u
r
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led
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u
r
e
1
1
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led
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led
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te
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s
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I
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th
th
e
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n
e
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s
s
p
ec
if
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in
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ab
le
4
is
s
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o
w
n
in
F
i
g
u
r
e
1
2
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d
F
ig
u
r
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1
3
w
h
ich
i
n
d
icate
th
at
t
h
e
s
et
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o
in
t
tr
ac
k
in
g
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er
f
o
r
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a
n
ce
h
a
s
g
o
t
i
m
p
r
o
v
ed
as
co
m
p
ar
ed
to
th
at
o
f
co
m
p
o
s
i
te
2
x
2
s
y
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te
m
(
F
i
g
u
r
e
8
)
as
th
e
lo
o
p
in
ter
ac
tio
n
s
ar
e
m
i
n
i
m
ized
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y
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o
u
p
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g
.
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le
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ar
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eter
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o
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n
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I
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n
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ller
s
f
o
r
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ec
o
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led
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y
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te
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Pa
r
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m
e
t
e
r
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a
l
u
e
K
p1
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0
.
0
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0
1
0
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i1
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0
.
0
0
3
6
6
8
2
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p2
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1
.
4
6
8
1
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i2
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0
.
0
0
4
9
6
5
4
Fig
u
r
e
1
2
.
C
lo
s
ed
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o
p
s
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r
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s
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o
n
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e
o
f
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o
u
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led
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Fig
u
r
e
1
3
.
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ed
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s
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o
n
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e
o
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o
u
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led
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2
T
h
e
ch
ar
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ter
s
tics
o
f
t
h
e
r
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o
n
s
e
s
in
F
ig
u
r
e
1
2
an
d
F
ig
u
r
e
1
3
ar
e
p
r
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ted
in
T
ab
le
5
an
d
T
a
b
le
6
r
esp
ec
tiv
el
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Mu
ltil
o
o
p
a
n
d
P
r
ed
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n
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a
s
ed
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g
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n
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ee
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ma
r
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n
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r
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143
T
ab
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5
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y
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r
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e
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e
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5
9
.
7
S
e
t
t
e
l
i
n
g
t
i
me
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s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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IJ
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4
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4
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Dec
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b
er
201
5
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1
3
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–
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4
5
144
4.
CO
NCLU
SI
O
N
I
n
th
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p
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ese
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t
w
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ill
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y
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eter
m
in
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R
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w
h
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ested
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tab
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p
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lcu
lated
v
a
lu
e
o
f
Nied
er
lin
s
k
i i
n
d
ex
i
n
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icate
d
th
at
th
is
s
y
s
te
m
h
as
g
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o
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clo
s
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o
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s
tab
ilit
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.
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e
m
u
lti
lo
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as
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esig
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s
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Av
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p
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p
tab
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s
etp
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in
t
tr
ac
k
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p
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f
o
r
m
a
n
ce
w
as
o
b
s
er
v
ed
.
Af
ter
d
ec
o
u
p
li
n
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,
th
e
co
n
tr
o
ller
p
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m
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a
s
b
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s
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v
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to
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etter
th
an
th
e
m
u
ltil
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o
p
co
n
tr
o
ller
f
o
r
th
e
co
m
p
o
s
ite
s
y
s
t
e
m
.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
p
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ed
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o
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ased
co
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tr
o
ller
is
o
b
s
er
v
ed
to
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e
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x
ce
lle
n
t
w
it
h
a
v
er
y
s
m
al
l
s
etteli
n
g
ti
m
e.
A
n
i
n
cr
ea
s
e
i
n
t
h
e
v
alu
e
o
f
s
a
m
p
l
in
g
i
n
ter
v
al
f
o
r
MP
C
h
as r
es
u
lted
in
a
n
in
cr
ea
s
e
in
t
h
e
s
et
tli
n
g
ti
m
e
o
f
t
h
e
r
esp
o
n
s
e.
RE
F
E
R
E
NC
E
S
[1
]
R.
S
iv
a
k
u
m
a
r,
K.
S
u
re
sh
M
a
n
ic,
V
.
Ne
rth
ig
a
,
R.
A
k
il
a
,
K.
Ba
lu
,
”
A
p
p
li
c
a
ti
o
n
o
f
F
u
z
z
y
M
o
d
e
l
P
re
d
ictiv
e
Co
n
tro
l
i
n
M
u
lt
iv
a
riab
le
Co
n
tro
l
o
f
Distil
latio
n
C
o
lu
m
n
”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Ch
e
mic
a
l
En
g
in
e
e
rin
g
a
n
d
Ap
p
li
c
a
t
io
n
s
,
V
o
l
.
1
,
No
.
1
,
Ju
n
e
2
0
1
0
.
[2
]
M
ich
a
ł
Ro
g
a
lew
icz
,
P
o
li
tec
h
n
ik
a
P
o
z
n
a
ń
sk
a
,
P
i
o
tr
o
w
o
a
n
d
P
o
z
n
a
ń
,
“
T
h
e
M
e
th
o
d
o
lo
g
y
o
f
Co
n
tr
o
ll
i
n
g
M
a
n
u
f
a
c
tu
rin
g
P
r
o
c
e
ss
e
s
w
it
h
th
e
Us
e
o
f
M
u
lt
iv
a
riate
S
tatisti
c
a
l
P
r
o
c
e
ss
Co
n
tr
o
l
T
o
o
ls”
,
J
o
u
rn
a
l
o
f
T
re
n
d
s
in
th
e
De
v
e
lo
p
me
n
t
o
f
M
a
c
h
in
e
ry
a
n
d
A
ss
o
c
ia
ted
T
e
c
h
n
o
l
o
g
y
,
Vo
l.
1
7
,
N
o
.
1
,
p
p
.
8
9
-
9
3
,
2
0
1
3
.
[3
]
M
o
h
a
m
m
e
d
A
.
Ra
h
i
m
,
Y
a
sir
A
.
S
id
d
iq
u
i
a
n
d
M
o
u
sta
f
a
El
sh
a
f
e
i,
”
In
teg
ra
ti
o
n
o
f
M
u
lt
iva
ria
te
S
t
a
ti
stica
l
Pro
c
e
ss
Co
n
tro
l
a
n
d
En
g
in
e
e
rin
g
Pro
c
e
ss
Co
n
tro
l
”
,
P
r
o
c
e
e
d
in
g
s
o
f
th
e
2
0
1
4
I
n
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
In
d
u
strial
En
g
in
e
e
rin
g
a
n
d
Op
e
ra
ti
o
n
s M
a
n
a
g
e
m
e
n
t
,
Ba
li
,
In
d
o
n
e
sia
,
2
0
1
4
.
[4
]
T
a
e
ib
A
d
e
l,
L
ta
e
if
A
li
a
n
d
Ch
a
a
ri
A
b
d
e
lk
a
d
e
r,
”
A
PS
O
Ap
p
ro
a
c
h
fo
r
O
p
ti
mu
m
De
sig
n
o
f
M
u
lt
iva
ria
b
le
PID
Co
n
tro
ll
e
r
fo
r
n
o
n
li
n
e
a
r
sy
ste
ms
”,
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
C
o
n
t
r
o
l,
En
g
in
e
e
rin
g
&
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
(CEIT
'
1
3
)
P
r
o
c
e
e
d
in
g
s E
n
g
i
n
e
e
rin
g
&
T
e
c
h
n
o
lo
g
y
,
V
o
l.
2
,
p
p
.
2
0
6
-
2
1
0
,
2
0
1
3
.
[5
]
P
.
Na
id
o
o
,
D.
T.
P
.
G
o
v
e
n
d
e
r
a
n
d
T
.
I.
v
a
n
Nie
k
e
rk
,
”
S
y
ste
m
In
teg
ra
ti
o
n
o
f
a
M
u
lt
iv
a
riab
le
P
r
o
c
e
ss
P
lan
t
Uti
li
sin
g
a
n
In
telli
g
e
n
t
Co
n
tro
l
T
e
c
h
n
iq
u
e
”
,
J
o
u
rn
a
l
o
f
Ach
iev
e
me
n
ts
in
M
a
t
e
ria
ls
a
n
d
M
a
n
u
f
a
c
tu
ri
n
g
E
n
g
i
n
e
e
rin
g
,
Vo
l.
3
1
,
No
.
2,
p
p
.
5
4
0
-
5
4
6
,
2
0
0
8
.
[6
]
Da
o
u
ti
d
is,
P
r
o
d
r
o
m
o
s,
S
o
ro
u
s
h
,
M
a
so
u
d
,
Kra
v
a
ris
a
n
d
Co
sta
s,
”
F
e
e
d
f
o
rwa
rd
/F
e
e
d
b
a
c
k
Co
n
tro
l
o
f
M
u
lt
iv
a
riab
le
No
n
li
n
e
a
r
P
ro
c
e
ss
e
s”
,
AICh
E
J
o
u
rn
a
l
,
Vo
l.
3
6
,
No
.
1
0
,
p
p
.
1
4
7
1
-
1
4
8
4
,
Oc
to
b
e
r
1
9
9
0
.
[7
]
Da
n
A
lt
e
n
a
,
M
ich
a
e
l
Ho
wa
rd
,
Ke
it
h
Bu
ll
in
a
n
d
Jo
e
l
Ca
n
t
re
ll
,
“
Ad
v
a
n
c
e
d
M
u
lt
iva
ri
a
b
le
Co
n
tro
l
o
f
a
T
u
rb
o
e
x
p
a
n
d
e
r P
l
a
n
t
”,
P
ro
c
e
e
d
i
n
g
s o
f
th
e
S
e
v
e
n
t
y
-
S
e
v
e
n
th
G
P
A
A
n
n
u
a
l
Co
n
v
e
n
ti
o
n
,
T
u
lsa
,
1
9
9
8
.
[8
]
A
.
H.
M
a
z
in
a
n
,
”
A
n
In
telli
g
e
n
t
M
u
lt
i
-
m
u
lt
iv
a
riab
le
Dy
n
a
m
ic
M
a
tri
x
Co
n
tr
o
l
S
c
h
e
m
e
f
o
r
a
1
6
0
M
W
Dru
m
-
t
y
p
e
Bo
il
e
r
-
T
u
rb
in
e
S
y
ste
m
”
,
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
&
T
e
c
h
n
o
l
o
g
y
,
Vo
l.
7
,
N
o
.
2
,
p
p
.
2
4
0
-
2
4
5
,
2
0
1
2
.
[9
]
R.
Ha
n
u
m
a
Na
ik
,
D.
V
.
A
sh
o
k
Ku
m
a
r
a
n
d
K.
S
.
R.
A
n
jan
e
y
u
lu
,
”
Co
n
tro
l
Co
n
f
ig
u
ra
ti
o
n
S
e
lec
ti
o
n
a
n
d
Co
n
tro
l
ler
De
sig
n
f
o
r
M
u
lt
iv
a
riab
le
P
ro
c
e
ss
e
s
Us
in
g
No
rm
a
li
z
e
d
Ga
in
”
,
W
o
rld
Ac
a
d
e
my
o
f
S
c
ien
c
e
,
En
g
g
.
,
a
n
d
T
e
c
h
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ter
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1
.
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2
]
A
.
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s”
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a
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p
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6
9
1
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1
.
[1
3
]
D.
D.
Bru
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.
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in
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V
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e
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n
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o
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tru
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V
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8
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l.
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p
p
.
1
0
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3
,
1
9
7
9
.
[1
4
]
E.
H.
Bristo
l,
“
On
a
Ne
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M
e
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re
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f
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tera
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f
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P
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IEE
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ti
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Au
to
.
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n
t.
,
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o
l
.
1
1
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p
p
.
1
3
3
,
1
9
9
6
.
[1
5
]
T.
J.
M
c
A
v
o
y
,
“
In
tera
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ti
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n
a
l
y
sis T
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n
d
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p
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ti
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n
”
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I
S
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Res
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le P
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rk
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,
1
9
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3
.
[1
6
]
Ba
b
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tu
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n
d
W.
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r
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Ra
y
,
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ro
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Dy
n
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m
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c
s,
M
o
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Co
n
tro
l”,
Ox
f
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rd
Un
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e
rsity
P
re
ss
,
1
9
9
4
.
[1
7
]
Re
k
h
a
Ra
j
a
n
,
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u
h
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m
m
e
d
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a
li
h
P
.,
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n
d
N.
A
n
il
Ku
m
a
r,
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p
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n
tr
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ll
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r
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sig
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f
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r
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tea
m
T
u
rb
in
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”
,
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ter
n
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l
J
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n
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d
Res
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rc
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in
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trica
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c
tr
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ics
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n
d
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n
stru
me
n
t
a
ti
o
n
E
n
g
i
n
e
e
rin
g
”
,
Vo
l.
2
,
No
.
9
,
2
0
1
3
.
[1
8
]
Ju
n
x
ia
M
u
a
n
d
Da
v
id
Re
e
s,
“
Ap
p
ro
x
ima
te
M
o
d
e
l
Pre
d
ictive
Co
n
t
ro
l
fo
r
G
a
s
T
u
r
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in
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E
n
g
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n
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s
”
,
P
r
o
c
e
e
d
in
g
o
f
th
e
2
0
0
4
A
m
e
rica
n
Co
n
tro
l
Co
n
f
e
re
n
c
e
,
Bo
sto
n
,
M
a
ss
a
c
h
u
se
tt
s,
2
0
0
4
.
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