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I
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IJ
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6
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1950
2.
TO
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TIM
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N
2.
1.
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T
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F
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3
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4
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M
.
U
lti
m
a
te
l
y
,
t
h
e
m
e
t
h
odol
ogy
di
s
c
u
s
s
e
d i
n
t
hi
s
pa
pe
r
i
s
ba
s
e
d
on
c
on
t
r
ol
l
e
r
o
pt
i
m
i
z
a
t
i
o
n
t
e
c
h
ni
q
ue
s
.
3.
CURRE
NT
CO
M
P
E
NS
AT
I
O
N S
T
RA
T
E
G
Y
T
h
e
C
u
r
r
e
n
t P
r
o
f
ilin
g
s
tr
a
te
g
y
e
x
p
la
in
e
d
in
[
10]
i
s
b
as
ed
o
n
p
h
as
e cu
r
r
en
t
r
es
h
ap
e
w
h
i
ch
i
s
t
h
e
m
aj
o
r
cau
s
e o
f
t
o
t
o
r
q
u
e r
i
p
p
l
e.
T
h
i
s
t
ech
n
i
q
u
e r
eq
u
i
r
es
t
h
e
k
n
o
w
l
ed
g
e o
f
t
h
e
n
o
n
-
l
i
ne
a
r
m
a
gne
t
i
c
ch
ar
act
er
i
s
t
i
c
s
o
f
t
h
e
S
R
M
T
(i
,
ѳ
)
a
s
di
s
c
us
s
e
d pr
e
v
i
ou
s
l
y
.
A
c
c
or
di
ng
t
o
t
h
e
pa
s
t
s
t
u
di
e
s
a
s
D
.
S
c
h
r
a
m
m
,
B
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
E
C
E
I
SSN
:
2088
-
8708
A
N
e
w
P
has
e
C
ur
r
e
nt
P
r
of
i
l
i
ng w
i
t
h F
L
C
f
or
T
or
que
O
pt
i
m
i
z
at
i
on
of
12/
8 SR
M
(
Si
he
m
Sai
dani
)
1951
W
i
l
l
i
a
m
s
,
a
n
d T
.
G
r
e
e
n
i
n 1993 a
n
d I
qba
l
H
u
s
a
i
n
,
M
e
h
r
da
d E
h
s
a
n
i
i
n
1996,
i
t
i
s
pos
s
i
b
l
e
t
o opt
i
m
i
z
e
t
he
o
ve
r
l
a
p
p
i
ng
c
ur
r
e
nt
d
ur
i
n
g t
h
e
c
o
m
m
u
t
a
t
i
o
n
a
nd
t
he
n
t
hr
o
ug
h
r
e
c
o
gni
z
i
n
g a
c
e
n
t
r
a
l
p
o
i
nt
w
h
e
r
e
t
he
ne
xt
i
nc
o
m
i
n
g a
nd
o
ut
p
ut
t
i
ng p
ha
s
e
s
c
o
ul
d
b
e
e
q
ua
l
.
3.
1.
SR
M
s
t
a
t
i
c
m
o
de
l
T
h
e
el
ect
r
i
cal
eq
u
at
i
o
n
s
g
o
v
e
r
n
i
n
g
t
h
e
S
R
M
b
e
h
av
i
o
r
ar
e
ci
t
ed
i
n
(
1
)
,
(
2
)
an
d
(
3
)
.
M
o
r
eo
v
er
,
t
h
e
f
l
u
x
ch
ar
act
er
i
s
t
i
c h
as
b
een
ca
l
cu
l
at
ed
u
s
i
n
g
a
2
D
f
i
n
i
t
e
el
e
m
en
t
m
a
g
n
et
i
c m
et
h
o
d
w
i
t
h
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E
M
M w
i
t
h
v
ar
y
i
n
g
t
h
e
r
ot
or
pos
i
t
i
on
f
r
o
m
(
0°
t
o
45)
w
i
t
h
a
s
t
e
p of
0.
5°
i
n
or
de
r
t
o f
u
l
f
i
l
l
t
h
e
m
ot
or
i
ng
a
n
d
g
e
n
e
r
a
t
i
n
g
m
o
d
e (
s
ee
F
i
g
u
re
7
).
I
n
o
r
d
er
t
o
r
eal
i
z
e t
h
e n
o
n
l
i
n
ear
m
o
d
el
ex
p
l
ai
n
ed
n
ex
t
w
e n
eed
t
o
u
s
e t
h
e i
n
v
er
s
i
o
n
o
f
t
h
e
ch
ar
act
er
i
s
t
i
c (
s
ee
F
i
g
u
r
e
5
)
.
A
f
te
r
a
c
u
b
ic
,
s
p
li
n
e
o
r
p
o
ly
n
o
m
ia
l i
n
te
r
p
o
la
tio
n
,
th
e
f
l
u
x
l
in
k
a
g
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v
e
r
s
e
r
e
s
u
lte
d
is
c
a
lle
d
i
(
Ѱ,
ѳ
)
as
r
ep
r
e
s
e
nt
e
d
i
n F
i
g
ur
e
6.
F
i
gur
e
5
.
A
3
D
m
a
g
ne
t
i
c
f
l
u
x l
i
n
ka
ge
F
i
g
ur
e
6
.
T
h
e
i
(
Ѱ
,
ѳ
)
ch
ar
act
er
i
s
t
i
c
(
3
D
)
3.
2.
T
he
c
o
m
pe
ns
a
t
i
o
n pr
o
c
e
dur
e
T
he
b
a
s
i
c
p
r
i
nc
i
p
l
e
s
o
f
t
he
c
o
m
p
e
ns
a
t
i
o
n t
he
o
r
y
ha
ve
b
e
e
n d
i
s
c
us
s
e
d
i
n
d
i
f
f
e
r
e
nt
i
s
s
ue
s
a
s
i
n
[
11]
a
nd
[
12]
.
A
c
t
ua
l
l
y,
t
he
S
R
M
d
r
i
vi
n
g s
ys
t
e
m
a
s
s
ho
w
n i
n F
i
g
ur
e
7
is
r
un
ni
ng
i
n
a
s
pe
e
d c
ont
r
ol
m
ode
.
T
he
F
i
gur
e
9 s
h
o
w
s
,
t
h
e
s
c
h
e
m
e
bl
oc
k
o
f
t
h
e
pr
opos
e
d c
om
pe
ns
a
t
i
on
t
h
e
or
y
.
E
v
e
n
t
u
a
l
l
y
,
t
h
e
o
u
t
put
s
i
g
n
al
n
a
m
ed
∆i
co
m
i
s
ad
d
ed
t
o
t
h
e
i
n
p
u
t
o
f
t
h
e
cl
as
s
i
c
co
n
t
r
o
l
l
er
P
I
i
n
o
r
d
er
t
o
r
eg
u
l
at
e
t
h
e
s
i
g
n
al
co
m
m
a
n
d
cau
s
i
n
g
t
h
e r
i
p
p
l
e an
d
i
n
t
h
a
t
cas
e i
s
t
h
e cu
r
r
en
t
.
T
h
e r
eg
u
l
a
t
ed
s
i
g
n
al
can
b
e a
f
u
n
ct
i
o
n
as
d
es
cr
i
b
ed
b
el
o
w
i
n
r
e
l
a
t
i
on
(
5)
of
a
r
ot
or
pos
i
t
i
on,
t
h
e
t
or
qu
e
l
oa
d,
t
h
e
s
pe
e
d
a
n
d
t
h
e
ph
a
s
e
c
u
r
r
e
n
t
.
S
u
bs
e
que
n
t
l
y
,
∆
i
c
o
m
i
s
t
he
n
i
nj
e
c
t
e
d
i
n t
he
S
R
M
d
r
i
vi
n
g s
ys
t
e
m
[
13]
.
F
i
g
ur
e
7
.
B
l
o
ck
s
ch
e
m
e o
f
co
m
p
e
n
s
at
i
o
n
s
t
r
at
eg
y
∆
=
(
,
,
,
)
(5
)
A
s
m
e
n
t
i
o
n
ed
i
n
(
5
)
t
h
e co
m
p
en
s
at
o
r
i
s
a f
u
n
ct
i
o
n
o
f
i
n
h
e
r
en
t
v
ar
i
ab
l
e.
H
en
ce,
i
n
o
r
d
er
r
ed
u
ce t
h
e
c
o
m
p
l
e
xi
t
y o
f
r
e
s
o
l
ut
i
o
n,
t
he
w
e
ca
n
d
ecr
eas
e
t
h
es
e
v
ar
i
ab
l
e
i
n
t
o
o
n
l
y
t
w
o
ѳ
t
he
r
ot
or
pos
i
t
i
on
a
n
d t
h
e
ou
t
pu
t
c
ur
r
e
nt
c
o
m
i
n
g f
r
o
m
t
he
P
I
s
p
e
e
d
c
o
nt
r
o
l
l
e
r
.
T
he
(
5
)
w
i
l
l
b
e
w
r
i
t
t
e
n t
he
n a
s
gi
ve
n ne
xt
:
∆
=
(
,
)
(6
)
3.
3.
I
n
t
el
l
i
g
en
t
f
u
zzy
co
n
t
ro
l
l
er
I
n
r
e
c
e
n
t
s
t
u
d
ie
s
,
t
h
e
in
te
lli
g
e
n
t c
o
n
tr
o
lle
r
s
a
s
th
e
f
u
z
z
y
l
o
g
ic
c
o
n
tr
o
lle
r
(
F
L
C
)
a
n
d
th
e
a
d
a
p
tiv
e
F
uz
z
y ne
u
ro
-
f
u
zz
y
i
n
f
er
en
ce
s
y
s
t
e
m
ar
e d
es
i
g
n
ed
f
o
r
n
o
n
l
i
n
ear
co
n
t
r
o
l
.
T
h
er
ef
o
r
e,
f
i
t
t
i
n
g
t
h
e d
i
s
cr
et
e S
R
M
m
o
d
el
,
i
s
ap
p
r
o
p
r
i
at
e t
o
u
s
e b
o
t
h
o
r
o
n
e o
f
t
h
e
m
t
o
r
ed
u
ce t
h
e t
o
r
q
u
e r
i
p
p
l
e.
H
en
ce,
t
h
e F
L
C
i
s
eas
y
t
o
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
20
88
-
8708
IJ
E
C
E
V
o
l.
6
, N
o
.
5
,
O
ct
o
b
er
201
6
:
19
48
–
19
55
1952
i
m
p
l
e
m
en
t
b
ecau
s
e i
t
es
t
i
m
a
t
es
r
el
at
i
o
n
s
b
et
w
een
ch
o
s
e
n
v
ar
i
ab
l
e d
es
p
i
t
e
t
h
ei
r
a
n
al
y
t
i
cal
d
ep
en
d
en
c
y
.
C
o
n
s
eq
u
en
t
l
y
,
t
h
e
cu
r
r
en
t
co
m
p
e
n
s
at
ed
cal
l
ed
I
c
o
mp
w
h
ic
h
is
th
e
r
e
s
u
lt
o
f
I
ph
t
he
p
ha
s
e
c
ur
r
e
n
t
o
f
S
R
M
d
r
i
ve
s
y
s
t
e
m
de
s
c
r
i
be
d pr
e
v
i
ous
l
y
s
o t
h
e
n
I
ref
t
h
e
out
pu
t
of
t
h
e
s
pe
e
d c
on
t
r
ol
l
e
r
c
a
n
be
i
n
j
ect
ed
i
n
ea
c
h p
ha
s
e
u
s
i
ng
F
L
C
o
u
t
p
u
t
es
t
i
m
at
ed
f
r
o
m
i
t
s
n
o
m
i
n
al
m
e
m
b
er
s
h
i
p
f
u
n
ct
i
o
n
s
c
h
o
s
en
acco
r
d
i
n
g
t
o
t
h
e
p
ar
am
et
er
s
o
f
t
h
e
dy
n
a
m
i
c
m
ot
or
be
h
a
v
i
or
.
T
h
e f
u
zz
y
co
n
t
r
o
l
o
f
S
R
M
u
s
i
n
g
F
L
C
o
r
al
s
o
n
a
m
ed
M
a
m
d
an
i
co
n
t
r
o
l
l
er
,
u
t
i
l
i
zes
as
i
n
p
u
t
t
h
e r
o
t
o
r
pos
i
t
i
on
ѳ
a
n
d
t
h
e
cu
r
r
en
t
co
m
i
n
g
f
r
o
m
t
h
e s
p
eed
co
n
t
r
o
l
l
er
(
g
en
er
al
l
y
a P
I
i
s
u
s
ed
)
an
d
t
h
en
p
r
o
d
u
ces
t
h
e
c
om
pe
n
s
a
t
i
ng
c
u
r
r
e
n
t
a
s
t
h
e
o
u
t
pu
t
.
T
h
e
i
n
t
e
g
r
a
t
i
on of
F
L
C
i
n
bl
oc
k s
c
h
e
m
e
of
s
pe
e
d c
on
t
r
ol
i
s
gi
v
e
n
n
e
xt
i
n
F
i
g
ur
e
8.
F
i
g
ur
e
8
.
B
lo
c
k
S
R
M
d
r
iv
e
s
c
h
e
m
e
w
i
th
c
o
n
tr
o
lle
r
4.
S
I
M
U
LA
TIO
N
R
ES
U
L
TS
AND
DI
S
CUS
S
I
O
N
T
he
no
n
-
l
i
n
ear
1
2
/
8
S
R
M
m
o
d
el
i
s
r
ep
r
es
en
t
ed
i
n
F
i
g
u
r
e 9
.
T
h
e s
t
at
i
c ch
ar
act
er
i
s
t
i
c
w
as
es
t
i
m
at
ed
u
s
i
n
g
t
h
e F
i
n
i
t
e E
l
e
m
e
n
t
Met
h
o
d
M
ag
n
et
i
c
s
(
F
E
M
M)
s
o
f
t
w
a
r
e
.
T
h
e
S
R
M
is
f
e
d
in
th
is
s
i
m
u
la
t
io
n
u
s
in
g
th
e
as
y
m
m
et
r
i
cal
p
o
w
er
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n
v
er
t
er
i
n
w
h
i
c
h
,
each
l
eg
co
n
s
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s
t
s
o
f
t
w
o
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G
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T
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d
t
w
o
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r
ee
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Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
E
C
E
I
SSN
:
2088
-
8708
A
N
e
w
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has
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C
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of
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m
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(
Si
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[
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p
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=
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(b
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(
=
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(c
) (
=
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(d
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(
=
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F
i
g
ur
e
11
.
T
h
e
to
ta
l to
r
q
u
e
w
it
h
a
n
d
w
it
h
o
u
t c
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m
p
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n
s
a
tio
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
20
88
-
8708
IJ
E
C
E
V
o
l.
6
, N
o
.
5
,
O
ct
o
b
er
201
6
:
19
48
–
19
55
1954
(a
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(
=
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(b
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(
=
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(c
)
(
=
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(d
)
(
=
5
0
0
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F
i
g
ur
e
12
.
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h
e p
h
as
e
c
ur
r
e
nt
w
i
t
h a
nd
w
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t
ho
ut
F
L
C
4.
CO
NCL
U
S
I
O
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I
n
t
h
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s
p
ap
er
w
e h
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v
e d
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el
o
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e
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t
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s
p
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o
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on
t
r
ol
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a
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on
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n
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t
h
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.
R
EF
ER
EN
C
ES
[
1]
V
. P
e
t
r
u
s
,
e
t a
l.
,
“
C
om
pa
r
a
t
i
v
e
s
t
udy
of
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f
f
e
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e
nt
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pha
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e
8/
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w
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ch
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el
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an
ce
m
ach
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e,
” v
o
l
/
i
ssu
e
:
4
(
1
),
p
p.
17
3
–
17
8,
20
11
.
[
2]
N.
H
.
P
huc
a
nd L
.
H
.
S
o
n,
“
T
or
q
ue
R
i
ppl
e
M
i
ni
m
i
z
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t
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on i
n a
S
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zzy
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ur
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e
nt
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om
pe
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t
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on
.
”
[
3]
L
. O
. P
. H
e
n
r
i
q
u
e
s
,
e
t a
l.
, “
N
eu
r
o
-
F
uz
z
y
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o
m
pe
ns
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t
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o
f
T
or
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i
n
a
S
w
i
t
ch
ed
R
el
u
ct
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ce D
r
i
v
e
.”
[
4]
J
.
U
m
a an
d
J
eev
an
an
d
h
am
A
.
,
“
I
n
v
e
s
tig
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tio
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s
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c
C
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e
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e
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s
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d R
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l
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nc
e
M
o
t
o
r
D
r
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v
e,
”
I
O
S
R
J
. E
l
e
c
t
r
.
E
l
e
c
t
r
o
n
. E
n
g
. V
e
r
. I
, v
o
l
/
i
ssu
e
:
11
(
1
)
,
p
p.
22
78
–
1
67
6.
[
5]
N
.
T
ha
nk
a
c
ha
n a
nd S
.
V
.
R
e
e
ba
,
“
T
une
d F
uz
z
y
L
og
i
c
C
ont
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w
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M
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r
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s
,
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pr
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r
N
e
w
Y
or
k
,
pp.
65
5
–
6
68
,
20
13
.
[
6]
K
.
B
oy
nov
a
nd E
.
L
om
onov
a
,
“
S
w
i
t
c
he
d R
e
l
uc
t
a
nc
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M
ot
or
D
r
i
v
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f
or
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ul
l
E
l
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t
r
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c
V
e
hi
c
l
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s
-
P
ar
t
I
:
A
n
al
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s
i
s
,
”
201
3.
[
7]
R
.
T
.
N
aa
y
a
g
i
an
d
V
.
K
am
ar
aj
,
“
O
p
t
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m
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m
P
o
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e A
r
cs
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o
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S
w
i
t
ch
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R
el
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ach
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i
t
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R
ed
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R
i
p
p
l
e,
” i
n
200
5 I
n
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er
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r
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d
D
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y
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s
, v
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l
. 1
,
p
p
. 7
6
1
–
76
4
,
20
05
.
[
8]
J
.
E
.
S
a
nd S
.
K
.
S
,
“
T
or
que
R
i
ppl
e
M
i
ni
m
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z
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t
i
on of
s
w
i
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d r
e
l
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nc
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dr
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v
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s
-
A su
r
v
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y
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”
P
o
w
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l
ect
r
o
n
.
M
ac
h.
D
r
i
v
e
s
(
P
E
M
D
2010)
,
5t
h
I
E
T
I
nt
.
C
o
nf
.
,
20
10
.
[
9]
K.
L
a
k
s
h
m
an
an
,
e
t a
l.
, “
A
r
ti
f
ic
ia
l I
n
te
llig
e
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c
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-
ba
s
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d c
ont
r
ol
f
or
t
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i
p
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m
i
ni
m
i
z
a
t
i
on i
n s
w
i
t
c
he
d r
e
l
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t
a
nc
e
m
ot
or
dr
i
v
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s
,”
A
ct
a
S
ci
.
T
ech
n
o
l
.
, v
o
l
/
i
ssu
e
:
36
(
1
)
,
p
p
. 3
3
–
40
,
2
01
3.
do
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4
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36
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1
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[
1
0]
L
.
H
e
nr
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s
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a
l.
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o
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or
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wi
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ch
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s
:
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d
Ex
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im
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ta
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Ev
a
lu
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.”
[
1
1]
H
. Z
h
a
n
g
,
e
t a
l.
,
“
A
N
ov
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l
M
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od of
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on
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2]
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.
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v
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d
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,
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t a
l.
,
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i
g
h p
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R
M
dr
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p
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l
.
1,
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p.
12
30
–
123
5
,
2
00
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[
1
3]
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. O
. D
. A
. P
. H
e
n
r
i
q
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e
s
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t
a
l.
,
“
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op
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t
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o
n of
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n of
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l
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ne
l
e
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ni
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ip
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w
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o
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.
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E
l
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t
r
on.
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vo
l
/
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ssu
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:
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(
3
)
,
pp.
66
5
–
67
6,
20
02
.
B
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h
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oup (
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1.
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n
19
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I
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I
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10
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14
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t
r
oni
c
s
a
nd T
e
l
e
c
o
m
m
uni
c
a
t
i
ons
of
S
f
a
x i
n T
uni
s
i
a
(
E
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E
T
’
c
o
m
)
.
S
i
nc
e
200
9 he
i
s
a
m
e
m
be
r
o
f
t
he
L
a
bor
a
t
or
y
of
E
l
e
c
t
r
oni
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s
a
nd
I
nf
or
m
a
t
i
on T
e
c
hnol
og
y
(
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E
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,
E
l
ect
r
i
c V
e
h
i
cl
e an
d
P
o
w
er
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l
ect
r
o
n
i
cs
G
r
o
u
p
(
V
E
E
P
)
.
Hi
s m
a
i
n
r
es
ear
ch
i
n
t
er
es
t
s
i
n
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u
d
e an
al
y
s
i
s
,
d
es
i
g
n
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an
d
co
n
t
r
o
l
o
f
el
ect
r
i
c m
ach
i
n
es
f
o
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V
a
p
p
l
i
cat
i
o
n
s
.
w
a
s
b
o
r
n
i
n
S
f
ax
,
T
u
n
i
s
i
a,
i
n
1
9
7
1
.
H
e r
ecei
v
ed
t
h
e B
.
S
c.
d
eg
r
ee
i
n
el
ect
r
i
cal
en
g
i
n
eer
i
n
g
f
r
o
m
t
h
e
N
at
i
o
n
al
S
ch
o
o
l
o
f
E
n
g
i
n
eer
s
o
f
S
f
a
x
,
i
n
1
9
9
6
,
t
h
e M
.
S
c.
d
eg
r
ee i
n
el
ect
r
i
cal
en
g
i
n
eer
i
n
g
f
r
o
m
t
h
e
N
a
t
i
ona
l
S
c
h
ool
of
E
ng
i
ne
e
r
s
of
S
f
a
x
,
i
n 1997
,
a
nd
t
he
P
h.
D
.
de
g
r
e
e
i
n e
l
e
c
t
r
i
c
a
l
e
ng
i
ne
e
r
i
ng
f
r
o
m
N
a
t
i
ona
l
S
c
h
ool
of
E
ng
i
ne
e
r
s
of
S
f
a
x
,
i
n 200
3,
he
r
ecei
v
ed
,
H
a
b
ilita
tio
n
U
n
iv
e
r
s
ita
ir
e
d
eg
r
ee
i
n
el
ect
r
i
cal
en
g
i
n
eer
i
n
g
f
r
o
m
t
h
e E
co
l
e N
at
i
o
n
al
e
d
’
I
n
g
én
i
eu
r
s
d
e S
f
a
x
-
T
uni
s
i
a
i
n 20
10
,
he
j
oi
ne
d
t
h
e
D
e
p
a
r
tm
e
n
t o
f
Ele
c
tr
ic
a
l En
g
in
e
e
r
in
g
in
I
n
te
r
n
a
tio
n
a
l S
c
h
o
o
l o
f
Ele
c
tr
o
n
ic
a
nd C
om
m
uni
c
a
t
i
on o
f
S
f
ax
(
I
S
E
C
S
)
,
U
n
i
v
er
s
i
t
y
o
f
S
f
ax
,
,
T
u
n
i
s
i
a,
w
h
er
e h
e i
s
an
A
s
s
o
ci
at
e P
r
o
f
es
s
o
r
.
H
e j
o
i
n
ed
t
h
e
L
a
bor
a
t
or
y
o
f
E
l
e
c
t
r
oni
c
s
a
nd I
nf
or
m
a
t
i
on T
e
c
hnol
og
y
(
L
E
T
I
)
,
E
l
e
c
t
r
i
c
V
e
hi
c
l
e
a
nd
P
ow
e
r
E
l
ect
r
o
n
i
cs
G
r
o
u
p
(
V
E
E
P
)
.
H
i
s
m
ai
n
r
es
ear
ch
i
n
t
er
es
t
s
i
nc
l
ude
a
na
l
y
s
i
s
,
de
s
i
g
n,
a
nd c
o
nt
r
o
l
o
f
el
ect
r
i
c
m
ach
i
n
es
f
o
r
E
V
ap
p
l
i
cat
i
o
n
s
.
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