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[
1
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R
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5
ill
u
s
tr
ates
t
h
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t
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m
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m
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lat
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r
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r
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w
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.
2.
RT
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L
AB
CO
NF
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G
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ial
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m
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lat
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tr
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d
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ap
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m
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++
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m
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p
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r
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[1
]
,
[
4
]
-
[
6]
.
2
.
1
.
H
a
rdw
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re
Co
nfig
ura
t
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RT
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B
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2
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1
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1
.
T
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Co
mm
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d St
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t
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h
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m
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2
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les
[8
]
,
[
9]
;
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I
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7
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2
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2
.
So
f
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Fo
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th
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_
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el
[
1
0
]
-
[
12]
.
2
.
3
.
O
pco
mm
Co
mm
u
nica
t
io
n B
lo
ck
s
On
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Si
m
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li
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n
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y
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ild
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u
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it is
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A
B
[
1
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.
2
.
4
.
Rec
o
rding
Da
t
a
w
it
h O
pWrit
eF
ile
T
o
o
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tain
all
d
ata
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o
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an
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ar
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icu
lar
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al,
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s
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e
Op
W
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iteFil
e
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ck
d
ata
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ec
o
r
d
ed
w
it
h
th
is
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lo
c
k
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s
to
r
ed
o
n
th
e
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g
et
r
ea
l
-
ti
m
e
n
o
d
e
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s
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ar
d
d
r
iv
e.
th
e
d
ata
f
ile
i
s
au
to
m
atica
ll
y
tr
a
n
s
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er
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ed
to
th
e
co
m
m
an
d
s
tatio
n
w
h
e
n
th
e
m
o
d
el
is
r
ese
t
[
1
0
]
.
2
.
5
.
E
Xt
re
m
e
H
ig
h P
er
f
o
r
m
a
nc
e
(
XH
P
)
M
o
de
T
h
e
XHP
m
o
d
e
is
a
m
ea
n
s
f
o
r
th
e
r
ea
l
-
ti
m
e
o
p
er
atin
g
s
y
s
te
m
to
d
is
ab
le
in
ter
r
u
p
ts
.
th
is
is
d
o
n
e
o
n
a
p
er
-
s
u
b
s
y
s
te
m
(
t
h
u
s
p
er
-
C
P
U)
b
asic.n
o
t
allo
w
i
n
g
in
ter
r
u
p
ts
p
r
ev
en
ts
p
r
o
ce
s
s
s
w
itc
h
in
g
w
h
ic
h
r
e
m
o
v
es
laten
cie
s
ti
m
e
f
o
r
ad
d
itio
n
al
co
m
p
u
ta
tio
n
in
th
e
s
a
m
e
ti
m
e
s
lice.
T
h
e
XHP
m
o
d
e
is
ai
m
ed
a
t
r
ea
l
-
ti
m
e
ap
p
licatio
n
s
o
f
a
g
i
v
en
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as
e
s
a
m
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le
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m
e
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s
tep
f
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r
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I
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&
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ter
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ates
at
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s
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o
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e
C
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o
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er
atio
n
in
tr
o
d
u
ce
s
al
m
o
s
t
n
o
laten
c
y
[
1
0
]
.
3.
I
NDUC
T
I
O
N
M
O
T
O
R
M
O
DE
L
I
N
G
T
h
e
m
at
h
e
m
atica
l
m
o
d
els o
f
i
n
d
u
ctio
n
m
o
to
r
in
t
h
e
p
ar
k
f
r
a
m
e
ar
e
w
r
it
ten
a
s
f
o
llo
w
s
[
1
3
]
-
[
19]
.
V
sd
=
R
s
.
I
sd
+
d
ϕ
sd
dt
−
W
a
.
ϕ
sq
V
sq
=
R
s
.
I
sq
+
d
ϕ
sq
dt
−
W
a
.
ϕ
sd
V
sd
=
R
r
.
I
rd
+
d
ϕ
rd
dt
−
W
r
.
ϕ
rq
V
rq
=
R
r
.
I
rq
+
d
ϕ
rq
dt
−
W
r
.
ϕ
rd
(
1
)
T
h
e
s
tato
r
an
d
r
o
to
r
f
lu
x
es a
r
e
r
elate
d
to
th
e
cu
r
r
en
t b
y
:
ϕ
sd
=
L
s
.
I
sd
+
L
m
.
I
rd
ϕ
sq
=
L
s
.
I
sq
+
L
m
.
I
rq
ϕ
rd
=
L
s
.
I
rd
+
L
m
.
I
sd
ϕ
rq
=
L
s
.
I
rq
+
L
m
.
I
sq
(
2
)
T
h
e
s
tato
r
an
d
r
o
to
r
an
g
u
lar
v
elo
cities ar
e
lin
k
ed
b
y
th
e
f
o
ll
o
w
i
n
g
r
elatio
n
:
W
s
=
W
+
W
r
(
3
)
T
h
e
eq
u
atio
n
s
o
f
m
ec
h
a
n
ical
a
n
d
elec
tr
o
m
ag
n
etic
to
r
q
u
es a
r
e:
J
d
Ω
dt
=
T
e
−
T
m
−
f
Ω
(
4
)
T
e
=
P
(
ϕ
rq
I
rd
−
ϕ
rd
I
rq
)
,
Ω
=
W
P
(
5
)
w
h
er
e
:
R
s
is
s
tato
r
r
esis
tan
ce
,
R
r
is
r
o
to
r
r
esis
tan
ce
,
L
s
an
d
L
r
ar
e
r
esp
ec
tiv
e
l
y
s
ta
to
r
an
d
r
o
to
r
in
d
u
ct
an
ce
L
m
th
e
m
u
tu
al
in
d
u
ctan
ce
,
ϕ
sd
an
d
ϕ
sq
ar
e
th
e
d
ir
ec
t
an
d
q
u
ad
r
atu
r
e
s
t
ato
r
f
lu
x
,
ϕ
rd
an
d
ϕ
rq
ar
e
th
e
d
ir
ec
t
an
d
q
u
ad
r
atu
r
e
r
o
to
r
f
lu
x
,
I
sd
an
d
I
sq
ar
e
th
e
d
ir
ec
t
an
d
q
u
ad
r
atu
r
e
s
t
ato
r
cu
r
r
en
t,
I
rd
an
d
I
rq
ar
e
th
e
d
ir
e
ct
an
d
q
u
ad
r
atu
r
e
r
o
to
r
cu
r
r
en
t
,
P
is
th
e
n
u
m
b
er
o
f
p
air
p
o
les,
W
s
an
d
W
r
ar
e
th
e
as
y
n
ch
r
o
n
o
u
s
a
n
d
r
o
to
r
an
g
u
lar
f
r
eq
u
en
c
y
,
T
e
an
d
T
m
ar
e
th
e
elec
tr
o
m
a
g
n
etiq
u
e
a
n
d
m
ec
h
a
n
ical
t
o
r
q
u
e
,
an
d
F is
th
e
v
is
co
s
it
y
c
o
ef
f
icie
n
t.
T
o
g
et
a
m
o
d
el
s
tate
in
ter
m
s
o
f
th
e
r
o
to
r
s
izes
(
I
rd
,
I
rq
,
ϕ
rd
,
ϕ
rq
)
,
W
e
ex
p
r
ess
th
e
s
tato
r
s
izes
(
I
sd
,
I
sq
,
ϕ
sd
,
ϕ
sq
)
in
ter
m
s
o
f
r
o
to
r
s
izes
[
1
3
]
.
I
sd
=
ϕ
rd
L
m
−
L
r
L
m
I
rd
I
sq
=
ϕ
rq
L
m
−
L
r
L
m
I
rq
ϕ
sd
=
L
s
L
m
ϕ
rd
+
δ
L
m
I
rd
ϕ
sq
=
L
s
L
m
ϕ
rq
+
δ
L
m
I
rq
(
6
)
B
y
u
s
i
n
g
eq
u
atio
n
s
(
1
)
an
d
th
e
eq
u
atio
n
s
(
6
)
o
f
th
e
I
M,
w
e
o
b
tain
th
e
d
y
n
a
m
ic
m
o
d
el
o
f
in
d
u
ctio
n
m
o
to
r
h
av
i
n
g
as st
a
te
v
ec
to
r
(
I
rd
,
I
rq
,
ϕ
rd
,
ϕ
rq
,
w
):
d
I
rd
dt
=
(
R
s
L
r
+
R
r
L
s
)
L
m
I
rd
+
w
a
I
rq
−
R
s
δ
L
m
2
ϕ
rq
+
L
s
δ
L
m
2
w
ϕ
rq
+
V
sd
δ
L
m
−
L
s
δ
L
m
2
V
rd
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
I
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P
o
w
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&
Dr
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S
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s
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,
Vo
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9
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No
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4
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em
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er
2
0
1
8
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1476
–
1
4
8
5
1480
d
I
rq
dt
=
(
R
s
L
r
+
R
r
L
s
)
δ
L
m
2
I
rq
+
w
a
I
rd
−
R
s
δ
L
m
2
ϕ
rq
+
L
s
δ
L
m
2
w
ϕ
rd
+
V
sd
δ
L
m
−
L
s
δ
L
m
2
V
rd
d
ϕ
rd
dt
=
−
R
r
.
I
rd
+
w
a
ϕ
rq
−
w
ϕ
rq
+
V
rd
d
ϕ
rq
dt
=
−
R
r
.
I
rq
+
w
a
ϕ
rd
−
w
ϕ
rd
+
V
rq
dw
dt
=
P
2
J
(
ϕ
rq
I
rd
−
ϕ
rd
I
rq
)
+
P
J
(
T
m
−
fw
)
(
7
)
4.
M
O
DE
L
I
N
G
I
NDUC
T
I
O
N
M
O
T
O
R
I
N
RT
-
L
AB
I
n
R
T
-
L
A
B
all
to
p
-
le
v
el
s
u
b
s
y
s
te
m
s
m
u
s
t
b
e
n
a
m
ed
w
it
h
a
p
r
ef
ix
id
en
ti
f
y
i
n
g
th
eir
f
u
n
ctio
n
.
T
h
e
p
r
ef
ix
es
ar
e:
S
C
_
f
o
r
co
n
s
o
l s
y
b
s
y
s
te
m
an
d
SM_
f
o
r
m
aster
s
u
b
s
y
s
te
m
.
Dep
en
d
in
g
o
n
t
h
e
t
y
p
e
o
f
d
ata
ac
q
u
is
itio
n
,
w
e
p
r
o
p
o
s
e
t
w
o
R
T
-
L
A
B
m
o
d
el
s
;
i
n
th
e
f
ir
s
t
m
o
d
el
t
h
e
d
ata
tr
an
s
f
er
b
et
w
ee
n
t
h
e
tar
g
et
n
o
d
e
a
n
d
th
e
co
n
s
o
le
m
ac
h
in
e
is
d
u
r
in
g
t
h
e
s
i
m
u
lat
io
n
ta
s
k
,
h
o
w
ev
er
i
n
t
h
e
s
ec
o
n
d
o
n
e,
th
e
tr
an
s
f
er
w
ill b
e
d
o
n
e
af
ter
th
e
en
d
o
f
s
i
m
u
la
t
io
n
p
er
f
o
r
m
ed
.
4
.
1
.
Da
t
a
Acquis
it
io
n duri
ng
Si
mu
la
t
io
n
I
n
th
i
s
ca
s
e
RT
-
L
A
B
en
ab
le
s
s
ig
n
al
ac
q
u
is
itio
n
f
r
o
m
a
r
ea
l
-
ti
m
e
tar
g
e
t
d
u
r
in
g
s
i
m
u
la
tio
n
u
s
in
g
Op
C
o
m
m
b
lo
ck
f
o
r
s
y
n
c
h
r
o
n
i
za
tio
n
b
et
w
ee
n
tar
g
et
n
o
d
e
an
d
co
n
s
o
le.
Fig
u
r
e
3
.
R
T
-
L
ab
R
ea
l
-
T
i
m
e
s
i
m
u
latio
n
g
r
ap
h
ic
m
o
d
el
o
f
I
M
Fig
u
r
e
4
.
Ma
s
ter
s
u
b
s
y
s
te
m
o
f
in
d
u
ctio
n
m
to
r
w
it
h
o
p
co
m
m
b
lo
ck
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t
I
SS
N:
2
0
8
8
-
8
694
Mo
d
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g
a
n
d
R
ea
l
-
Time
S
imu
la
tio
n
o
f I
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d
u
ctio
n
Mo
to
r
Usi
n
g
R
T
-
LAB
(
A
.
Ha
med
)
1481
Fig
u
r
e
5
.
C
o
n
s
o
le
s
u
b
s
y
s
te
m
o
f
in
d
u
c
tio
n
m
o
to
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.
RE
F
E
R
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NC
E
S
[1
]
S
.
A
b
o
u
ri
d
a
,
e
t
a
l.
,
“
Ha
rd
w
a
re
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in
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th
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l
o
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p
sim
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o
f
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lem
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se
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o
r
d
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s
w
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h
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LAB
a
n
d
JMAG
,
”
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d
u
stria
l
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c
tro
n
ics
,
2
0
0
6
IEE
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ter
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ti
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y
m
p
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n
,
p
p
.
2
4
6
2
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4
6
6
,
2
0
0
6
.
[2
]
J.
Be
lan
g
e
r,
e
t
a
l.
,
“
T
h
e
w
h
a
t,
w
h
e
re
a
n
d
w
h
y
o
f
re
a
l
-
ti
m
e
si
m
u
lati
o
n
,
”
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la
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e
t
RT
,
v
o
l.
1
,
p
p
.
2
5
-
2
9
,
2
0
1
0
.
[3
]
M
.
O.
F
a
ru
q
u
e
,
e
t
a
l.
,
“
Re
a
l
-
ti
m
e
si
m
u
latio
n
tec
h
n
o
l
o
g
ies
f
o
r
p
o
w
e
r
s
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m
s
d
e
si
g
n
,
tes
ti
n
g
,
a
n
d
a
n
a
ly
sis,
”
IEE
E
Po
we
r a
n
d
E
n
e
rg
y
T
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c
h
n
o
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g
y
S
y
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ms
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o
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rn
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l
,
v
o
l.
2
,
p
p
.
6
3
-
7
3
,
2
0
1
5
.
[4
]
O.
Cră
c
iu
n
,
e
t
a
l.
,
“
Ha
rd
w
a
re
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in
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th
e
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l
o
o
p
tes
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n
g
o
f
P
V
c
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n
t
ro
l
sy
s
te
m
s
u
sin
g
RT
-
L
a
b
sim
u
lato
r,
”
Po
we
r
El
e
c
tro
n
ics
a
n
d
M
o
ti
o
n
Co
n
tro
l
Co
n
fer
e
n
c
e
(
EP
E/
PE
M
C),
2
0
1
0
1
4
th
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n
ter
n
a
ti
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n
a
l
,
p
p
.
S
2
-
1
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S2
-
6
,
2
0
1
0
.
[5
]
C.
Du
f
o
u
r,
e
t
a
l.
,
“
Ha
rd
w
a
re
-
in
-
th
e
-
lo
o
p
sim
u
latio
n
o
f
p
o
w
e
r
d
riv
e
s
w
it
h
RT
-
LAB,
”
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
s
S
y
ste
ms
,
2
0
0
5
.
PE
DS
2
0
0
5
.
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
,
p
p
.
1
6
4
6
-
1
6
5
1
,
2
0
0
5
.
[6
]
A
.
Id
ir
a
n
d
M
.
Kid
o
u
c
h
e
,
“
Rt
-
lab
a
n
d
d
sp
a
c
e
:
t
w
o
so
f
t
wa
re
s
f
o
r
r
e
a
l
ti
m
e
c
o
n
tro
l
o
f
in
d
u
c
ti
o
n
m
o
to
rs,
”
Rev
.
Ro
u
m.
S
c
i.
T
e
c
h
n
.
–
É
lec
tro
tec
h
n
.
e
t
Én
e
r
g
,
v
o
l.
5
9
,
p
p
.
2
0
5
-
2
1
4
,
2
0
1
4
.
[7
]
M
.
A
.
G
e
li
e
l,
“
Re
a
l
-
ti
m
e
i
m
p
lem
e
n
tatio
n
o
f
c
o
n
stra
i
n
e
d
c
o
n
tr
o
l
sy
st
e
m
o
n
e
x
p
e
rim
e
n
ta
l
h
y
b
rid
p
lan
t
u
sin
g
RT
-
L
a
b
,
”
Co
n
tro
l
a
n
d
A
u
t
o
ma
ti
o
n
,
2
0
0
8
1
6
th
M
e
d
it
e
rr
a
n
e
a
n
Co
n
fer
e
n
c
e
o
n
,
p
p
.
1
0
6
0
-
1
0
6
5
,
2
0
0
8
.
[8
]
X.
Y
.
X
u
a
n
d
L
.
W
a
n
g
,
“
RT
-
LAB
Ra
p
id
Co
n
tr
o
l
P
ro
t
o
ty
p
in
g
'
s
Ap
p
li
c
a
ti
o
n
in
S
e
rv
o
S
y
ste
m
,
”
J
o
u
rn
a
l
o
f
S
y
ste
m
S
imu
l
a
ti
o
n
,
v
o
l.
4
,
p
p
.
0
6
2
,
2
0
0
6
.
[9
]
H.
l.
Z
h
e
n
g
,
e
t
a
l.
,
“
RT
-
LA
B
b
a
se
d
re
a
l
-
ti
m
e
si
m
u
latio
n
o
f
p
h
o
to
v
o
l
taic
p
o
w
e
r
g
e
n
e
ra
ti
o
n
sy
ste
m
,
”
Ad
v
a
n
c
e
d
T
e
c
h
n
o
l
o
g
y
o
f
E
lec
trica
l
En
g
i
n
e
e
rin
g
a
n
d
E
n
e
rg
y
,
v
o
l.
4
,
p
p
.
0
1
4
,
2
0
1
0
.
[1
0
]
F
.
G
.
A
re
e
d
,
e
t
a
l.
,
“
A
d
a
p
ti
v
e
n
e
u
ro
-
f
u
z
z
y
c
o
n
tro
l
o
f
a
n
in
d
u
c
ti
o
n
m
o
to
r,
”
Ai
n
S
h
a
ms
En
g
in
e
e
rin
g
J
o
u
rn
a
l
,
v
o
l.
1
,
p
p
.
7
1
-
7
8
,
2
0
1
0
.
[1
1
]
C.
Du
f
o
u
r,
e
t
a
l.
,
“
RT
-
LA
B
re
a
l
ti
m
e
si
m
u
latio
n
o
f
e
lec
tri
c
d
ri
v
e
s
a
n
d
s
y
ste
m
s,
”
Na
ti
o
n
a
l
Po
we
r
El
e
c
tro
n
ics
Co
n
fer
e
n
c
e
–
NPE
C
,
2
0
0
5
.
[1
2
]
H.
G
u
o
,
e
t
a
l.
,
“
Re
a
l
-
ti
m
e
si
m
u
la
ti
o
n
o
f
BL
DC
-
b
a
se
d
w
in
d
tu
rb
i
n
e
e
m
u
lato
r
u
sin
g
RT
-
LA
B,
”
El
e
c
trica
l
M
a
c
h
in
e
s
a
n
d
S
y
ste
ms
,
2
0
0
9
.
ICEM
S
2
0
0
9
.
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ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
,
p
p
.
1
-
6
,
2
0
0
9
.
[1
3
]
A
.
M
.
F
ih
a
k
h
ir
a
n
d
M
.
Bo
u
h
a
m
id
a
,
“
No
n
li
n
e
a
r
Co
n
tr
o
l
o
f
a
Do
u
b
ly
F
e
d
In
d
u
c
ti
o
n
G
e
n
e
ra
to
r
Driv
e
n
W
in
d
T
u
rb
in
e
,
”
El
e
c
tro
teh
n
ica
,
El
e
c
tro
n
ica
,
Au
t
o
ma
ti
c
a
,
v
o
l.
6
4
,
p
p
.
2
3
,
2
0
1
6
.
[1
4
]
M
.
Ja
n
n
a
ti
,
e
t
a
l.
,
“
In
d
irec
t
ro
t
o
r
f
ield
-
o
rien
ted
c
o
n
tr
o
l
o
f
f
a
u
lt
-
to
lera
n
t
d
riv
e
s
y
ste
m
f
o
r
th
re
e
-
p
h
a
se
in
d
u
c
ti
o
n
m
o
to
r
w
it
h
ro
t
o
r
r
e
sista
n
c
e
e
s
ti
m
a
ti
o
n
u
sin
g
EKF
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
E
lec
trica
l
E
n
g
i
n
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
v
o
l.
1
2
,
p
p
.
6
6
3
3
-
6
6
4
3
,
2
0
1
4
.
[1
5
]
M
.
Ja
n
n
a
ti
,
e
t
a
l.
,
“
S
p
e
e
d
se
n
s
o
rles
s
f
a
u
lt
-
to
lera
n
t
d
riv
e
sy
ste
m
o
f
3
-
p
h
a
se
in
d
u
c
ti
o
n
m
o
to
r
u
sin
g
sw
it
c
h
in
g
e
x
ten
d
e
d
k
a
l
m
a
n
f
il
ter,
”
In
d
o
n
e
s
ia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
E
n
g
i
n
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
v
o
l
.
1
2
,
p
p
.
7
6
4
0
-
7
6
4
9
,
2
0
1
4
.
[1
6
]
V
.
Ku
m
a
r,
e
t
a
l.
,
“
I
m
p
le
m
e
n
tati
o
n
o
f
S
c
a
lar
Co
n
tro
l
T
e
c
h
n
iq
u
e
in
S
VP
W
M
S
w
it
c
h
e
d
T
h
re
e
-
Lev
e
l
In
v
e
rter
F
e
d
In
d
u
c
ti
o
n
M
o
t
o
r
Us
in
g
DS
P
Co
n
t
ro
ll
e
r,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
,
v
o
l.
1
,
p
p
.
8
3
,
2
0
1
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
P
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&
Dr
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Mo
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n
g
R
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LAB
(
A
.
Ha
med
)
1485
[1
7
]
L
.
L
a
h
c
e
n
,
“
F
u
z
z
y
S
li
d
in
g
M
o
d
e
Co
n
tr
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ll
e
r
f
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r
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d
u
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M
a
c
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e
F
e
e
d
b
y
T
h
re
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L
e
v
e
l
In
v
e
rter,
”
In
ter
n
a
ti
o
n
a
l
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o
u
rn
a
l
o
f
P
o
we
r E
lec
tro
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ics
a
n
d
Dr
ive
S
y
ste
ms
(
I
J
PE
DS
)
,
v
o
l.
9
,
2
0
1
8
.
[1
8
]
H.
Oth
m
a
n
i
,
e
t
a
l.
,
“
F
u
z
z
y
Ga
in
-
S
c
h
e
d
u
l
in
g
P
r
o
p
o
rti
o
n
a
l
-
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n
teg
ra
l
c
o
n
tr
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l
f
o
r
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p
ro
v
in
g
th
e
s
p
e
e
d
b
e
h
a
v
io
r
o
f
a
th
re
e
-
p
h
a
se
s in
d
u
c
ti
o
n
m
o
to
r,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Po
we
r E
le
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
,
v
o
l.
7
,
2
0
1
6
.
[1
9
]
E.
Ra
m
p
ra
sa
th
a
n
d
P
.
M
a
n
o
jk
u
m
a
r,
“
M
o
d
e
ll
in
g
a
n
d
a
n
a
ly
sis
o
f
in
d
u
c
ti
o
n
m
o
to
r
u
sin
g
L
a
b
V
IE
W
,
”
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ter
n
a
ti
o
n
a
l
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u
rn
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o
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n
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n
d
Dr
ive
S
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ste
ms
,
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o
l.
5
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p
.
3
4
4
,
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0
1
5
.
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G
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AUTH
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RS
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m
e
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1
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r
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r,
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lg
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e
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S
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se
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tere
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s
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lu
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p
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w
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telli
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t
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ti
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n
s.
Evaluation Warning : The document was created with Spire.PDF for Python.