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s
t
o
f
ac
t
u
ati
n
g
d
ev
ices.
B
asicall
y
,
t
h
er
e
ar
e
th
r
ee
ca
teg
o
r
ies
f
o
r
s
e
n
s
o
r
less
m
et
h
o
d
s
u
ch
as
f
u
n
d
a
m
en
tal
ex
ci
tatio
n
s
/
m
o
d
el
b
ased
m
et
h
o
d
,
s
alie
n
c
y
a
n
d
s
ig
n
al
i
n
j
ec
tio
n
an
d
ar
ti
f
ic
ial
i
n
telli
g
en
ce
.
He
n
ce
,
v
ar
io
u
s
m
et
h
o
d
s
an
d
tec
h
n
iq
u
es
ar
e
in
tr
o
d
u
ce
d
f
o
r
ea
c
h
ca
te
g
o
r
y
p
r
o
p
o
s
ed
b
y
t
h
e
r
e
s
ea
r
ch
er
s
t
o
co
n
tr
o
l
th
e
s
p
ee
d
an
d
p
o
s
iti
o
n
o
f
m
o
to
r
s
e
n
s
o
r
.
T
h
is
p
ap
er
p
r
esen
ts
th
e
r
e
v
ie
w
o
f
s
p
ee
d
an
d
p
o
s
itio
n
esti
m
atio
n
m
et
h
o
d
f
o
r
P
MSM
Dr
iv
es
b
ased
o
n
s
ev
er
al
m
et
h
o
d
s
.
B
asicall
y
,
t
h
is
p
ap
er
is
o
r
g
a
n
ized
as
f
o
llo
w
s
.
I
n
Sec
tio
n
I
I
,
t
h
e
th
r
ee
ca
te
g
o
r
ies
f
o
r
s
e
n
s
o
r
les
s
p
o
s
itio
n
esti
m
atio
n
o
f
P
MSM
is
ex
p
lain
ed
a
n
d
m
ac
h
in
e
m
o
d
el
o
f
P
MSM
is
p
r
esen
t
ed
in
Sectio
n
I
I
I
.
I
n
Sectio
n
I
V,
th
e
co
m
p
ar
is
o
n
a
m
o
n
g
th
e
ca
te
g
o
r
ies
is
s
h
o
wed
an
d
an
al
y
ze
d
b
ased
o
n
th
eir
ad
v
an
tag
e
s
an
d
d
is
ad
v
an
ta
g
es.
Fi
n
all
y
,
th
e
a
n
al
y
s
i
s
r
esu
lt
s
b
ased
o
n
r
esear
ch
an
d
o
b
s
er
v
atio
n
u
s
in
g
P
MSM
m
ac
h
i
n
e
ar
e
s
h
o
w
ed
in
Sec
tio
n
V.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
T
here
Ca
t
eg
o
ries f
o
r
Sens
o
rless
P
o
s
it
io
n E
s
t
i
m
a
t
io
n
T
h
e
f
lo
w
ch
ar
t
o
r
class
i
f
ic
atio
n
ab
o
v
e
s
h
o
w
s
t
h
e
th
r
ee
ca
teg
o
r
ies
o
f
s
en
s
o
r
les
s
p
o
s
itio
n
est
i
m
atio
n
o
f
P
MSM
w
h
ic
h
ar
e
ca
lled
Mo
d
el
B
ased
,
Salien
c
y
B
a
s
ed
Me
th
o
d
a
n
d
Si
g
n
al
I
n
j
ec
tio
n
a
n
d
A
r
ti
f
icial
I
n
telli
g
en
ce
(
A
I
)
[
1
]
-
[
5
]
.
Fig
u
r
e
1
.
C
lass
if
ica
tio
n
o
f
s
en
s
o
r
less
co
n
tr
o
l
m
e
th
o
d
o
f
P
MSM
2
.
1
.
1
.
M
o
del B
a
s
ed
M
et
ho
d
Fo
r
m
o
d
el
b
ased
ca
teg
o
r
ies,
th
er
e
ar
e
t
w
o
m
et
h
o
d
s
w
h
ic
h
ar
e
ca
lled
n
o
n
-
ad
ap
tiv
e
a
n
d
ad
ap
tiv
e
m
et
h
o
d
s
[
5
]
.
No
n
-
ad
ap
tiv
e
m
e
th
o
d
ca
n
b
e
d
iv
id
ed
in
to
th
r
ee
s
ec
tio
n
s
o
f
m
e
th
o
d
:
a.
E
s
ti
m
a
to
r
u
s
i
n
g
m
o
n
ito
r
ed
s
tat
o
r
v
o
ltag
es,
o
r
cu
r
r
en
ts
b.
Flu
x
b
ased
p
o
s
itio
n
esti
m
ato
r
c.
P
o
s
itio
n
esti
m
ato
r
b
ased
o
n
b
a
ck
-
E
M
F
As
f
o
r
ad
ap
tiv
e
m
e
th
o
d
,
it
is
d
iv
id
ed
in
to
t
w
o
ca
teg
o
r
ie
s
o
f
m
et
h
o
d
s
u
ch
as
Mo
d
el
R
ef
er
e
n
ce
A
d
ap
tiv
e
S
y
s
te
m
(
M
R
A
S)
a
n
d
Ob
s
er
v
er
-
b
ased
es
ti
m
ato
r
[
5
]
.
Fo
r
MR
A
S,
i
n
o
r
d
er
to
g
et
t
h
e
s
m
aller
v
al
u
e
o
f
er
r
o
r
,
th
e
o
u
tp
u
t
o
f
r
ef
er
e
n
c
e
m
o
d
el
m
u
s
t
b
e
co
m
p
ar
ed
w
it
h
t
h
e
o
u
tp
u
t
o
f
ad
j
u
s
tab
le
ad
ap
tiv
e
m
o
d
el.
B
asicall
y
,
th
i
s
m
et
h
o
d
is
u
s
ed
to
ad
j
u
s
t
th
e
s
tate
v
ar
iab
le
o
f
a
s
y
s
te
m
a
n
d
to
m
i
n
i
m
is
e
t
h
e
er
r
o
r
b
etw
ee
n
t
w
o
m
o
d
el
s
i
n
o
r
d
e
r
to
g
et
th
e
esti
m
atio
n
v
a
lu
e
o
f
q
u
an
t
it
y
.
T
h
e
n
ex
t
s
ec
t
io
n
i
s
o
b
s
er
v
er
-
b
ased
esti
m
ato
r
[
5
]
w
h
ic
h
it is
co
n
s
i
s
t o
f
:
a.
L
u
en
b
er
g
er
Ob
s
er
v
er
S
e
n
so
rles
s Co
n
tro
l
M
e
th
o
d
o
f
P
M
S
M
M
a
c
h
in
e
s
S
a
li
e
n
c
y
Ba
se
d
M
e
th
o
d
a
n
d
S
ig
n
a
l
In
jec
ti
o
n
M
o
d
e
l
Ba
se
d
M
e
th
o
d
A
rti
f
icia
l
In
telli
g
e
n
c
e
Ba
se
d
Esti
m
a
to
r
Ba
c
k
-
EM
F
b
a
se
d
m
e
th
o
d
F
lu
x
L
in
k
a
g
e
b
a
se
d
m
e
th
o
d
Ob
se
rv
e
r
b
a
se
d
m
e
th
o
d
Co
n
ti
n
u
o
u
s
sig
n
a
l
in
jec
ti
o
n
T
ra
n
sie
n
t
V
o
l
tag
e
V
e
c
to
r
W
it
h
o
u
t
a
d
d
it
io
n
a
l
In
jec
ti
o
n
Ro
tatin
g
In
jec
ti
o
n
P
u
lsa
ti
n
g
In
jec
ti
o
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
IJ
PEDS
Vo
l.
8
,
No
.
3
,
Sep
te
m
b
er
2
0
1
7
:
1
0
6
2
-
1069
1064
b.
R
ed
u
ce
d
Or
d
er
Ob
s
er
v
er
c.
Sli
d
in
g
Mo
d
e
Ob
s
er
v
er
d.
Kal
m
a
n
Fil
ter
L
u
en
b
er
g
er
Ob
s
er
v
er
an
d
E
x
t
en
d
ed
Kal
m
an
F
ilter
is
esti
m
a
to
r
th
at
u
s
es
p
lan
t
m
o
d
el
an
d
a
f
ee
d
b
ac
k
lo
o
p
w
ith
m
ea
s
u
r
ed
p
lan
t
v
a
r
iab
les.
B
asicall
y
,
t
h
e
L
u
en
b
er
g
er
Ob
s
er
v
er
i
s
a
d
eter
m
i
n
is
tic
o
b
s
er
v
er
t
h
at
p
r
o
d
u
ce
s
ze
r
o
n
o
is
e
co
m
p
ar
e
to
th
e
E
x
ten
d
ed
Kal
m
a
n
Fi
lt
er
w
h
er
e
its
s
i
g
n
a
l
is
co
r
r
u
p
t
ed
w
it
h
n
o
is
e.
T
h
e
n
o
is
e
p
r
o
d
u
ce
d
i
n
E
K
F
w
i
ll
b
e
co
n
s
id
er
ed
in
m
ea
s
u
r
e
m
e
n
t
an
d
m
o
d
eli
n
g
in
ac
c
u
r
ac
ies
i
n
o
r
d
er
to
g
e
t
t
h
e
d
esire
d
s
ig
n
a
l.
2
.
1
.
2
.
Sa
liency
B
a
s
ed
M
e
t
ho
d a
nd
Sig
na
l In
j
ec
t
io
n
Hig
h
s
i
g
n
al
i
n
j
ec
tio
n
is
also
a
s
en
s
o
r
les
s
m
et
h
o
d
to
g
et
th
e
p
o
s
itio
n
esti
m
atio
n
.
Ma
c
h
i
n
e
s
alien
c
y
o
r
s
ig
n
al
i
n
j
ec
tio
n
tech
n
iq
u
e
s
g
i
v
e
th
e
b
est
p
o
s
itio
n
esti
m
ato
r
f
r
o
m
s
ta
n
d
s
ti
ll
to
m
i
n
i
m
u
m
s
p
ee
d
[
6
]
.
Gen
er
all
y
,
s
alien
c
y
b
ased
m
et
h
o
d
ca
n
b
e
class
i
f
ied
in
to
th
r
ee
p
ar
ts
:
a.
C
o
n
ti
n
u
o
u
s
s
ig
n
al
i
n
j
ec
tio
n
b.
T
r
an
s
ien
t v
o
lta
g
e
v
ec
to
r
i
n
j
ec
tio
n
c.
W
ith
o
u
t a
d
d
itio
n
al
i
n
j
ec
tio
n
Fo
r
co
n
tin
u
o
u
s
s
i
g
n
a
l
in
j
ec
t
io
n
m
et
h
o
d
,
a
h
i
g
h
f
r
eq
u
e
n
c
y
s
i
g
n
al
s
ar
e
s
u
p
er
i
m
p
o
s
ed
o
n
th
e
f
u
n
d
a
m
en
ta
l
ex
citatio
n
.
An
o
b
s
er
v
er
is
r
eq
u
ir
ed
f
o
r
s
alien
c
y
tr
ac
k
i
n
g
w
h
e
n
u
s
i
n
g
a
co
n
ti
n
u
o
u
s
h
ig
h
v
o
lta
g
e
in
j
ec
tio
n
.
A
cc
o
r
d
in
g
o
n
t
h
e
p
r
in
cip
le
o
f
s
ig
n
al
in
j
ec
tio
n
m
e
th
o
d
,
all
th
e
s
ig
n
al
in
j
ec
tio
n
m
eth
o
d
m
u
s
t
b
e
u
s
ed
o
r
p
r
o
ce
s
s
ed
b
ased
o
n
m
ac
h
i
n
e
s
alien
c
y
.
I
t is d
u
e
to
d
o
m
i
n
a
n
t e
f
f
ec
t c
a
u
s
ed
b
y
m
a
g
n
et
ic
f
lu
x
f
r
o
m
p
er
m
a
n
e
n
t
m
ag
n
et
cr
ea
ti
n
g
th
e
s
a
tu
r
atio
n
o
f
th
e
s
tato
r
[
7
]
.
A
co
n
tin
u
o
s
u
s
s
i
g
n
a
l
in
j
ec
tio
n
m
e
th
o
d
ca
n
b
e
class
if
ied
in
to
t
w
o
s
ig
n
al
i
n
j
ec
tio
n
s
n
a
m
ed
as
r
o
tatin
g
in
j
ec
tio
n
an
d
p
u
ls
at
in
g
i
n
j
ec
tio
n
[
7
]
.
Sin
ce
m
o
s
t
h
i
g
h
f
r
eq
u
en
c
y
i
n
j
ec
tio
n
m
e
th
o
d
s
i
n
j
ec
t
v
o
lta
g
es,
t
h
u
s
r
o
tatin
g
i
n
j
ec
tio
n
ca
n
al
s
o
b
e
n
a
m
ed
as r
o
tati
n
g
v
o
lta
g
e
v
ec
t
o
r
o
r
r
ev
o
lv
in
g
ca
r
r
ier
w
h
ile
p
u
ls
at
in
g
i
n
j
ec
tio
n
is
n
a
m
ed
a
s
p
u
ls
ati
n
g
v
o
ltag
e
v
ec
to
r
o
r
alter
n
atin
g
ca
r
r
ier
.
R
o
tatin
g
i
n
j
ec
tio
n
m
eth
o
d
h
ap
p
en
s
w
h
e
n
a
v
o
lta
g
e
v
ec
to
r
at
co
n
s
ta
n
t
ca
r
r
ier
f
r
e
q
u
en
c
y
i
s
s
u
p
er
i
m
p
o
s
ed
o
n
t
h
e
r
e
f
er
en
ce
v
o
lta
g
es
p
r
o
d
u
ce
d
b
y
t
h
e
m
ac
h
i
n
e
co
n
tr
o
l in
s
tatio
n
ar
y
r
e
f
er
en
ce
f
r
a
m
e.
P
u
ls
ati
n
g
v
o
ltag
e
v
ec
to
r
is
i
n
j
ec
ted
o
n
an
esti
m
ated
eit
h
er
d
-
ax
is
o
r
q
-
ax
i
s
r
ef
er
e
n
ce
f
r
a
m
e.
Hen
ce
,
s
en
s
o
r
less
o
p
er
atio
n
is
d
ep
en
d
in
g
o
n
t
h
e
esti
m
ated
d
q
-
a
x
is
r
ef
er
en
ce
f
r
a
m
e
p
o
s
it
io
n
.
Ho
wev
er
,
in
o
r
d
er
to
g
et
th
e
p
er
f
ec
t
o
r
ien
tatio
n
,
t
h
e
i
n
j
ec
tio
n
o
f
h
i
g
h
f
r
eq
u
e
n
c
y
o
n
l
y
o
cc
u
r
s
at
d
-
a
x
is
w
h
i
le
ze
r
o
i
n
j
ec
tio
n
at
q
-
ax
i
s
.
I
n
j
ec
tio
n
h
ig
h
f
r
eq
u
e
n
c
y
w
il
l
p
r
o
d
u
ce
h
i
g
h
f
r
eq
u
e
n
c
y
cu
r
r
en
t
r
ip
p
le
t
h
at
af
f
ec
t
s
m
o
s
tl
y
th
e
f
l
u
x
p
r
o
d
u
cin
g
f
u
n
d
a
m
en
ta
l.
Gen
er
all
y
,
p
u
ls
atin
g
v
o
lta
g
e
v
ec
to
r
in
j
ec
tio
n
m
eth
o
d
ca
n
b
e
u
s
ed
f
o
r
an
y
t
y
p
e
o
f
p
er
m
an
e
n
t
m
ag
n
et
m
o
to
r
.
Fir
s
tl
y
,
h
ig
h
f
r
eq
u
en
c
y
m
et
h
o
d
w
ith
alter
n
at
in
g
ca
r
r
ier
tak
e
s
p
lace
i
n
in
ter
io
r
P
M
m
o
to
r
w
i
th
s
in
g
le
-
la
y
er
[
8
]
.
Nex
t,
it
is
in
j
ec
ted
in
to
th
e
th
er
e
-
la
y
er
in
te
r
io
r
P
M
m
o
to
r
an
d
a
m
az
i
n
g
l
y
,
th
e
r
es
u
lts
o
f
t
wo
s
in
u
s
o
id
al
h
i
g
h
f
r
eq
u
e
n
c
y
i
n
j
ec
tio
n
s
ar
e
s
a
m
e.
Ho
w
e
v
er
,
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o
m
e
r
esear
c
h
er
s
u
g
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ested
t
h
e
h
ig
h
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r
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e
n
c
y
u
s
i
n
g
alter
n
ati
n
g
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r
r
ier
g
i
v
e
t
h
e
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etter
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esu
lt
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o
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MSM
m
o
to
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s
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ec
au
s
e
t
h
e
h
i
g
h
f
r
eq
u
e
n
c
y
cu
r
r
en
t
d
o
es
n
o
t
p
r
o
d
u
ce
to
r
q
u
e,
an
d
r
ed
u
ce
n
o
is
e
a
n
d
v
ib
r
atio
n
.
W
h
e
n
a
n
i
m
p
u
l
s
e
v
o
lta
g
e
v
ec
to
r
is
ap
p
lied
,
th
e
cu
r
r
en
t
tr
an
s
ie
n
t r
esp
o
n
s
e
is
p
r
o
d
u
ce
d
an
d
it g
iv
e
s
af
f
ec
t
s
to
th
e
s
ali
en
c
y
p
o
s
it
io
n
i
n
f
o
r
m
atio
n
.
T
h
i
s
in
j
ec
tio
n
i
s
ca
lled
as tr
an
s
ie
n
t s
ig
n
al
i
n
j
ec
tio
n
.
2
.
1
.
3
.
Art
if
icia
l In
t
ellig
ence
B
a
s
ed
E
s
t
i
m
a
t
o
r
A
r
ti
f
icial
i
n
tel
lig
e
n
ce
b
ased
v
ec
to
r
co
n
tr
o
lled
is
also
u
s
ed
as
s
en
s
o
r
less
tec
h
n
iq
u
e
b
y
u
s
in
g
f
u
zz
y
lo
g
ic
an
d
f
u
zz
y
-
n
e
u
tr
al
co
n
tr
o
ller
.
T
h
is
is
o
n
e
o
f
th
e
s
u
cc
ess
f
u
l
l
y
tec
h
n
iq
u
e
t
h
at
h
as
b
e
en
i
m
p
le
m
e
n
ted
f
o
r
P
MSM
ap
p
licatio
n
.
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t
h
as
b
ee
n
ap
p
lied
to
m
i
n
i
m
ize
t
h
e
t
u
n
i
n
g
e
f
f
o
r
ts
a
n
d
al
s
o
to
i
m
p
r
o
v
e
th
e
e
s
ti
m
ated
r
esp
o
n
s
e.
A
r
tific
ial
i
n
telli
g
e
n
ce
b
ased
s
y
s
te
m
d
o
es
n
o
t
r
eq
u
ir
e
th
e
m
at
h
e
m
atica
l
m
o
d
el
o
f
m
o
to
r
an
d
f
u
zz
y
n
eu
tr
al
s
y
s
te
m
ca
n
o
n
l
y
p
er
f
o
r
m
w
it
h
li
n
g
u
i
s
tic
r
u
le
s
f
r
o
m
th
e
ex
p
er
t o
r
o
th
er
m
et
h
o
d
.
2
.
2
.
M
a
t
he
m
a
t
ica
l
M
o
dellin
g
o
f
P
M
S
M
M
o
t
o
r
A
s
tu
d
y
o
f
p
er
m
a
n
e
n
t
m
a
g
n
et
s
y
n
ch
r
o
n
o
u
s
m
ac
h
in
e
(
P
MS
M)
o
p
er
atio
n
is
m
ad
e
to
u
n
d
er
s
tan
d
th
e
d
y
n
a
m
ic
b
eh
a
v
io
r
o
f
F
OC
d
r
i
v
e.
T
o
co
n
tr
o
l
th
e
P
MSM
m
o
to
r
,
th
e
d
-
q
P
MSM
m
o
d
el
is
n
ee
d
ed
w
h
ile
f
ield
o
r
ien
ted
co
n
tr
o
l
(
FOC
)
al
g
o
r
ith
m
is
ap
p
lied
to
co
n
tr
o
l
t
h
e
f
l
u
x
a
n
d
to
r
q
u
e
i
n
d
ep
en
d
en
tl
y
,
s
i
m
ilar
w
i
th
D
C
m
ac
h
in
e.
B
asicall
y
,
in
F
OC
co
n
tr
o
l
d
r
iv
e,
to
r
q
u
e
an
d
f
lu
x
co
m
p
o
n
e
n
t
w
il
l
alig
n
ed
w
ith
t
h
e
q
an
d
d
co
o
r
d
in
ate
r
esp
ec
tiv
el
y
f
o
r
h
av
in
g
th
e
co
n
s
ta
n
t
s
as
in
p
u
t
r
ef
er
en
ce
.
FO
C
is
a
co
m
p
lex
co
n
tr
o
l
m
et
h
o
d
d
u
e
to
n
u
m
er
o
u
s
tr
an
s
f
o
r
m
atio
n
s
i
n
v
o
l
v
i
n
g
t
h
r
ee
-
p
h
ase
r
e
f
er
en
ce
f
r
a
m
e
to
t
w
o
-
ax
i
s
o
r
th
o
g
o
n
al
s
tatio
n
ar
y
r
ef
er
en
ce
f
r
a
m
e
o
r
v
ice
v
er
s
a.
T
h
e
tr
an
s
f
o
r
m
atio
n
s
ar
e
k
n
o
w
n
a
s
C
lar
k
tr
an
s
f
o
r
m
at
io
n
,
P
ar
k
tr
an
s
f
o
r
m
atio
n
an
d
in
v
er
s
e
C
lar
k
-
P
ar
k
tr
an
s
f
o
r
m
atio
n
.
T
h
is
s
e
ctio
n
w
ill
d
i
s
cu
s
s
m
o
r
e
d
etail
ab
o
u
t
th
e
tr
a
n
s
f
o
r
m
at
io
n
an
d
m
at
h
e
m
atica
l
m
o
d
eli
n
g
o
f
P
MSM
th
o
s
e
is
s
i
m
p
ler
co
m
p
ar
ed
to
th
e
m
at
h
e
m
atica
l
m
o
d
elin
g
o
f
i
n
d
u
ctio
n
m
ac
h
i
n
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
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8
694
R
ev
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o
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f S
e
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tima
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P
o
s
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n
.
.
.
.
(
Yu
s
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1065
2
.
2
.
1
.
d
-
q
Ref
er
ence
Co
rdina
t
e
Sy
s
t
e
m
FOC
ca
n
b
e
class
i
f
ied
in
to
tw
o
co
o
r
d
in
ate
s
y
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m
s
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c
h
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tatic
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ate
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a
n
d
r
ev
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r
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in
ates
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[
1
0
]
.
T
h
e
t
w
o
p
h
ase
s
tato
r
(a
-
B)
co
o
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ate
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a
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tic
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o
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a
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co
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ted
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at
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w
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v
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tica
l
9
0
d
eg
r
ee
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a
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Me
an
wh
ile,
d
-
q
co
o
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d
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ate
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w
it
h
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s
f
i
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n
t
h
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o
to
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is
ca
lled
r
ev
o
l
v
i
n
g
c
o
o
r
d
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ate
s
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te
m
.
Fi
g
u
r
e
2
s
h
o
w
s
th
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r
elatio
n
s
h
ip
b
et
w
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n
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co
o
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ate
s
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te
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a
n
d
d
-
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o
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ate
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w
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F
ig
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r
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3
s
h
o
w
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t
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r
e
latio
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h
ip
b
et
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th
r
ee
-
p
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ase
q
u
a
n
titi
e
s
eith
er
v
o
lt
ag
e
o
r
cu
r
r
en
t
n
a
m
ed
as
A
,
B
,
C
w
it
h
co
o
r
d
in
ate
s
y
s
te
m
.
I
n
Fig
u
r
e
3
,
it sh
o
w
s
th
e
A
co
o
r
d
in
ates a
x
i
s
is
eq
u
al
to
th
e
a
-
ax
is
an
d
t
h
e
an
g
le
b
et
w
ee
n
A
,
B
,
an
d
C
ax
is
is
1
2
0
d
eg
r
ee
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Fig
u
r
e
2.
R
elatio
n
s
h
ip
b
et
w
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n
an
d
d
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q
co
o
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ate
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te
m
Fig
u
r
e
3
.
R
elatio
n
s
h
ip
b
et
w
ee
n
an
d
A
-
B
-
C
co
o
r
d
in
ate
s
y
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m
T
h
e
an
g
le
(
)
b
etw
ee
n
d
an
d
-
a
x
is
i
n
Fig
u
r
e
1
is
k
n
o
w
s
as
r
o
to
r
f
lu
x
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o
s
itio
n
.
I
n
b
o
th
Fig
u
r
es,
th
e
E
q
u
atio
n
(
1
)
an
d
eq
u
atio
n
(
2
)
u
s
ed
th
e
C
lar
k
an
d
P
ar
k
tr
an
s
f
o
r
m
ati
o
n
w
h
er
e
it
in
v
o
l
v
e
th
e
tr
an
s
f
o
r
m
atio
n
b
et
w
ee
n
an
d
A
-
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C
co
o
r
d
in
ate
s
y
s
te
m
an
d
b
et
w
ee
n
an
d
d
-
q
co
o
r
d
in
ate
s
y
s
te
m
r
esp
ec
ti
v
el
y
.
T
h
e
tr
an
s
f
o
r
m
a
tio
n
s
i
n
m
atr
i
x
ar
e
g
iv
e
n
b
elo
w
:
[
]
√
[
]
[
√
√
]
[
]
(
1
)
[
]
[
]
[
]
(
2
)
2
.
2
.
2
.
P
M
S
M
M
a
t
he
m
a
t
ica
l M
o
del
B
a
s
ed
o
n d
-
q
Co
o
rdina
t
e
Sy
s
t
e
m
I
n
o
r
d
er
to
g
et
t
h
e
ac
c
u
r
ate
esti
m
ated
p
o
s
itio
n
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n
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s
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ee
d
,
it
is
i
m
p
o
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ta
n
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to
k
n
o
w
a
n
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s
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e
th
e
m
at
h
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m
a
tical
m
o
d
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n
g
b
ec
au
s
e
P
MSM
m
o
d
elin
g
p
la
y
s
t
h
e
b
ig
g
er
r
o
le
in
th
e
ex
p
er
i
m
e
n
t.
T
h
e
ai
m
s
o
f
it
s
m
o
d
eli
n
g
ar
e
to
p
r
esen
t
t
h
e
d
-
q
ax
i
s
E
q
u
atio
n
i
n
ter
m
s
o
f
c
u
r
r
en
t
s
a
n
d
v
o
ltag
e.
T
h
e
v
o
ltag
e
eq
u
atio
n
o
f
P
MSM
ca
n
b
e
ex
p
r
ess
ed
as f
o
llo
w
:
(
)
[
V]
(
3
)
[
A
]
(
4
)
d
q
= A
B
0
C
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
IJ
PEDS
Vo
l.
8
,
No
.
3
,
Sep
te
m
b
er
2
0
1
7
:
1
0
6
2
-
1069
1066
(
)
[
V]
(
5
)
[
A
]
(
6
)
W
h
er
e
co
m
e
s
f
r
o
m
f
l
u
x
lin
k
a
g
e
eq
u
atio
n
:
(
7
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Me
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1
1
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3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
3
.
1
.
Ana
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s
is
a
nd
Co
m
pa
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a
nta
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rless
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th
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n
s
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iq
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t
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at
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t
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le
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elo
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h
as
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ad
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y
f
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llo
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ti
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s
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I
I
.
3
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1
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1
.
M
o
del B
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s
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M
et
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T
ab
le
1
s
h
o
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th
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tech
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iq
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es
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ad
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d
d
is
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ased
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eth
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.
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m
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lar
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b
ac
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n
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ter
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E
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tech
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A
cc
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d
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th
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T
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le
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l
m
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d
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g
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ased
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atic
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ate
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lt
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f
r
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m
lo
w
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p
ee
d
to
s
tan
d
s
till
[
1
7
]
.
T
ab
le
1
.
A
d
v
an
ta
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es a
n
d
d
is
a
d
v
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ta
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s
[
1
1
]
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r
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to
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t
[
1
3
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[
14]
1)
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su
c
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ssf
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l
y
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mo
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Ex
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K
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man
F
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r
(
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[
1
5
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[
16]
1)
D
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Sa
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[
1
8
]
-
[
1
9
]
1)
H
i
g
h
F
r
e
q
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n
c
y
sh
o
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(
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F
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a
n
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M
F
[
2
0
]
1)
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mi
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a
t
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s
b
u
m
p
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g
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r
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smo
o
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me
[
2
1
]
-
[
22]
1)
T
h
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b
a
n
d
w
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d
t
h
o
f
t
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p
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2)
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t
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.
1
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3
.
Art
if
icia
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nte
llig
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M
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As
s
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T
ab
le
3
,
ar
tif
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telli
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tech
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tr
al
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m
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ab
le
3
.
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d
v
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ta
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c
i
mp
l
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me
n
t
a
t
i
o
n
[
2
3
]
-
[
24]
1)
R
o
t
o
r
p
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si
t
i
o
n
i
s
a
l
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g
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d
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q
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[
2
5
]
-
[
26]
1)
T
h
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p
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a
k
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v
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sh
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o
t
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M
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[
2
7
]
1)
I
mp
r
o
v
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h
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c
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t
r
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l
sy
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m’
s e
f
f
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y
2)
G
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p
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4.
CO
NCLU
SI
O
N
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co
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cl
u
s
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n
,
a
r
ev
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w
o
f
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itio
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n
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les
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d
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r
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MSM
h
as
b
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s
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.
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h
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r
less
tech
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g
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u
p
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b
y
ca
te
g
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ies
ar
e
also
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escr
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.
A
v
ar
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h
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in
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o
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as
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o
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tech
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th
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ch
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h
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s
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in
d
u
s
tr
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au
to
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licatio
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[1
]
T
.
D.
Ba
tze
l
a
n
d
K.
Y.
L
e
e
,
“
S
lo
t
les
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p
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a
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so
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to
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a
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so
r,
”
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E
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r
a
n
s.
En
e
rg
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Co
n
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ter
s.
,
v
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l
/i
ss
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e
:
15
(
4
)
,
p
p
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3
3
6
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3
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0
0
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.
[2
]
B
.
K.
Bo
se
,
“
M
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n
P
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w
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El
e
c
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Driv
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s
,
”
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h
e
Un
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rs
it
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f
T
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n
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e
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,
Kn
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v
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le
,
1
9
9
8
.
[3
]
O.
Be
n
jak
a
n
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D.
G
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,
“
Re
v
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XI
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In
ter
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ter
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n
fer
e
n
c
e
o
n
El
e
c
t
ric
M
a
c
h
in
e
s (
ICEM
)
,
p
p
.
1
-
6
,
2
0
1
0
.
[5
]
O.
Be
n
jak
a
n
d
D.
G
e
rli
n
g
,
“
R
e
v
i
e
w
o
f
P
o
siti
o
n
Esti
m
a
ti
o
n
M
e
th
o
d
f
o
r
P
M
S
M
Driv
e
s
w
it
h
o
u
t
a
P
o
siti
o
n
S
e
n
so
r
,
P
a
rt
III:
M
e
th
o
d
s
b
a
se
d
o
n
S
a
li
e
n
c
y
a
n
d
S
ig
n
a
l
In
jec
ti
o
n
,
”
In
te
rn
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
El
e
c
tric
M
a
c
h
in
e
s
a
n
d
S
y
ste
ms
,
p
p
.
8
7
3
-
8
7
8
,
2
0
1
0
.
[6
]
A
.
R
.
S
e
tt
y
,
e
t
a
l.
,
“
Co
m
p
a
riso
n
o
f
Hig
h
F
re
q
u
e
n
c
y
S
ig
n
a
l
In
jec
ti
o
n
T
e
c
h
n
i
q
u
e
f
o
r
Ro
to
r
P
o
siti
o
n
Esti
m
a
ti
o
n
a
t
L
o
w
S
p
e
e
d
to
S
tan
d
stil
l
o
f
P
M
S
M
,
”
IEE
E
5
th
I
n
ter
n
a
ti
o
n
a
l
Co
n
fe
re
n
c
e
o
n
P
o
we
r E
lec
tro
n
ics
,
p
p
.
1
-
6,
2
0
1
0
.
[7
]
R.
Ra
u
te,
e
t
a
l
.
,
“
A
Re
v
ie
w
o
f
S
e
n
so
rles
s
Co
n
tro
l
in
I
n
d
u
c
ti
o
n
M
a
c
h
in
e
s
u
si
n
f
HF
In
jec
ti
o
n
,
T
e
st
V
e
c
to
rs
a
n
d
P
W
M
h
a
rm
o
n
ics
,
”
S
y
mp
o
siu
m
o
n
S
e
n
so
rle
ss
Co
n
tro
l
o
f
El
e
c
trica
l
Dr
ive
s,
p
p
.
4
7
-
55
,
2
0
1
1
.
[8
]
R.
Bo
j
o
i,
e
t
a
l.
,
“
S
e
n
so
rles
s
Co
n
tro
l
o
f
P
M
M
o
to
r
Driv
e
s
-
a
T
e
c
h
n
o
l
o
g
y
S
tatu
s
Re
v
ie
w
,
”
IEE
E
W
o
rk
sh
o
p
o
n
El
e
c
trica
l
M
a
c
h
in
e
De
sig
n
,
C
o
n
tr
o
l
a
n
d
Dia
g
n
o
sis (
W
EM
DCD
)
,
p
p
.
1
6
8
-
1
8
2
,
2
0
1
3
.
[9
]
P
.
V
a
s,
“
S
e
n
so
rles
s
V
e
c
to
r
a
n
d
D
irec
t
T
o
rq
u
e
Co
n
tro
l
,
”
L
o
n
d
o
n
,
O
x
f
o
rd
Un
iv
P
re
ss
,
1
9
9
8
.
[1
0
]
X
.
W
a
n
g
,
e
t
a
l.
,
“
S
im
u
latio
n
o
f
P
M
S
M
F
ield
-
O
rie
n
ted
Co
n
tro
l
Ba
se
d
o
n
S
VP
W
M
,
”
IEE
E
Veh
i
c
le
Po
we
r
a
n
d
Pro
p
u
lsio
n
Co
n
fer
e
n
c
e
,
p
p
.
1
4
6
5
-
1
4
6
9
,
2
0
0
9
.
[1
1
]
X
.
S
h
i
,
e
t
a
l.
,
“
A
Ba
c
k
EM
F
-
b
a
se
d
Ro
t
o
r
P
o
siti
o
n
P
re
d
ictio
n
i
n
P
e
r
m
a
n
e
n
t
M
a
g
n
e
t
M
a
c
h
i
n
e
f
o
r
S
u
rv
iv
a
b
le
W
in
d
G
e
n
e
r
a
to
r
S
y
ste
m
s
,
”
IECON
3
6
th
An
n
u
a
l
Co
n
fer
e
n
c
e
o
n
I
EE
E
I
n
d
u
stria
l
El
e
c
tro
n
ics
S
o
c
iety
,
p
p
.
7
7
8
-
7
8
3
,
2
0
1
0
.
[1
2
]
S
.
Ju
rk
o
v
ic
a
n
d
E
.
S
tran
g
a
s,
“
Cro
ss
-
S
a
tu
ra
ti
o
n
Ef
f
e
c
ts
o
n
P
o
siti
o
n
Esti
m
a
ti
o
n
Us
in
g
BEM
F
M
e
t
h
o
d
s
i
n
P
M
A
C
M
a
c
h
in
e
s
,
”
IEE
E
I
n
ter
n
a
ti
o
n
a
l
E
lec
tric
M
a
c
h
in
e
s a
n
d
Dr
ive
s Co
n
f
e
re
n
c
e
(
IEM
DC)
,
p
p
.
7
-
1
2
,
2
0
1
1
.
[1
3
]
V
.
C.
Ili
o
u
d
is
a
n
d
N
.
I.
M
a
rg
a
ris,
“
F
lu
x
W
e
a
k
e
n
in
g
M
e
th
o
d
f
o
r
S
e
n
so
rles
s
P
M
S
M
Co
n
tr
o
l
Us
in
g
T
o
rq
u
e
De
c
o
u
p
li
n
g
T
e
c
h
n
iq
u
e
,
”
Fi
rs
t
S
y
mp
o
siu
m
o
n
S
e
n
s
o
rle
ss
Co
n
tr
o
l
f
o
r E
lec
trica
l
Dr
ive
,
p
p
.
3
2
-
3
9
,
2
0
1
0
.
[1
4
]
L
.
A
.
Jo
n
e
s
a
n
d
J.
H.
L
a
n
g
,
“
A
S
tate
Ob
se
rv
e
r
f
o
r
th
e
P
e
rm
a
n
e
n
t
-
m
a
g
n
e
t
S
y
n
c
h
ro
n
o
u
s
M
o
to
r
,
”
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
I
n
d
u
stria
l
El
e
c
tro
n
ics
,
v
o
l.
3
6
,
p
p
.
3
7
4
-
3
8
2
,
1
9
8
9
.
[1
5
]
S
.
Bo
l
o
g
n
a
n
i
,
e
t
a
l.
,
“
S
e
n
s
o
rles
s
f
u
ll
-
d
ig
it
a
l
P
M
S
M
Driv
e
w
it
h
EKF
Esti
m
a
ti
o
n
o
f
S
p
e
e
d
a
n
d
R
o
to
r
P
o
siti
o
n
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
stri
a
l
El
e
c
tro
n
ics
,
v
o
l.
4
6
,
p
p
.
1
8
4
-
1
9
1
,
1
9
9
9
.
[1
6
]
S
.
M
o
rim
o
to
,
e
t
a
l.
,
“
S
e
n
so
rles
s
Co
n
tr
o
l
S
trate
g
y
f
o
r
S
a
li
e
n
t
-
P
o
l
e
P
M
S
M
b
a
se
d
o
n
Ex
ten
d
e
d
E
M
F
in
R
o
tatin
g
Re
fe
re
n
c
e
F
ra
m
e
,
”
In
d
u
stry
Ap
p
l
ica
ti
o
n
C
o
n
fer
e
n
c
e
,
T
h
irty
-
Si
x
t
h
IAS
A
n
n
u
a
l
M
e
e
ti
n
g
,
IEE
E
Co
n
f
e
re
n
c
e
Rec
o
rd
,
v
o
l.
4
,
p
p
.
2
6
3
7
-
2
6
4
4
,
2
0
0
1
.
[1
7
]
Y
.
L
e
e
,
e
t
a
l.
,
“
Co
m
p
a
riso
n
o
f
Ro
to
r
P
o
siti
o
n
Esti
m
a
ti
o
n
P
e
rf
o
rm
a
n
c
e
in
f
u
n
d
a
m
e
n
tal
-
M
o
d
e
-
B
a
se
d
S
e
n
so
rles
s
Co
n
tr
o
l
o
f
P
M
S
M
,
”
IE
EE
E
n
e
rg
y
Co
n
v
e
rs
io
n
Co
n
g
re
ss
a
n
d
Ex
p
o
si
ti
o
n
(
ECCE
),
p
p
.
5
6
2
4
-
5
6
3
3
,
2
0
1
5
.
[1
8
]
H
.
Zh
u
,
e
t
a
l.
,
“
A
S
im
p
li
f
i
e
d
Hig
h
F
re
q
u
e
n
c
y
In
jec
ti
o
n
M
e
th
o
d
f
o
r
P
M
S
M
S
e
n
so
r
les
s
Co
n
t
ro
l
,
”
IEE
E
6
th
In
ter
n
a
t
io
n
a
l
Po
we
r E
lec
tro
n
ics
a
n
d
M
mo
ti
o
n
C
o
n
tr
o
l
Co
n
fer
e
n
c
e
,
p
p
.
4
0
1
-
4
0
5
,
2
0
0
9
.
[1
9
]
J
.
H
.
Ja
n
g
,
e
t
a
l.
,
“
S
e
n
s
o
rles
s
Driv
e
o
f
S
u
rfa
c
e
-
Mo
u
n
ted
P
e
rm
a
n
e
n
t
-
M
a
g
n
e
t
M
o
t
o
r
b
y
Hig
h
-
F
r
e
q
u
e
n
c
y
S
ig
n
a
l
In
jec
ti
o
n
Ba
se
d
o
n
M
a
g
n
e
ti
c
S
a
li
e
n
c
y
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s o
n
I
n
d
u
stry
Ap
p
li
c
a
ti
o
n
s,
v
o
l.
3
9
,
p
p
.
1
0
3
1
-
1
0
3
9
,
2
0
0
3
.
[2
0
]
J.
L
a
ra
,
e
t
a
l.
,
“
In
teg
ra
ti
o
n
o
f
HFS
I
a
n
d
Ex
ten
d
e
d
-
EM
F
Ba
se
d
T
e
c
h
n
iq
u
e
f
o
r
P
M
S
M
S
e
n
so
r
les
s
Co
n
tr
o
l
i
n
HEV
/E
V
A
p
p
li
c
a
ti
o
n
s
,
”
IECON
-
38
th
An
n
u
a
l
Co
n
fer
e
n
c
e
o
n
IEE
E
In
d
u
stri
a
l
El
e
c
tro
n
ics
S
o
c
iety
,
p
p
.
3
6
8
8
-
3
6
9
3
,
2
0
1
2
.
[2
1
]
J.
M
.
L
iu
a
n
d
Z.
Q.
Zh
u
,
“
S
e
n
s
o
rles
s
Co
n
tro
l
S
trate
g
y
b
y
S
q
u
a
re
-
W
a
v
e
f
o
r
m
Hig
h
-
F
re
q
u
e
n
c
y
P
u
lsa
ti
n
g
S
ig
n
a
l
In
jec
ti
o
n
i
n
t
o
S
tatio
n
a
ry
Re
f
e
r
e
n
c
e
F
ra
m
e
,
”
IEE
E
J
o
u
rn
a
l
o
f
Eme
rg
in
g
a
n
d
S
e
lec
ted
T
o
p
ics
i
n
P
o
we
r
El
e
c
tro
n
ics
,
v
o
l.
2
,
p
p
.
1
7
1
-
1
8
0
,
2
0
1
4
.
[2
2
]
J.
M
.
L
iu
a
n
d
Z.
Q.
Zh
u
,
“
A
N
e
w
S
e
n
so
rles
s
Co
n
tro
l
S
trate
g
y
b
y
Hig
h
-
F
re
q
u
e
n
c
y
P
u
lsa
ti
n
g
S
ig
n
a
l
In
jec
ti
o
n
in
t
o
S
tatio
n
a
ry
Re
fe
re
n
c
e
F
ra
m
e
,
”
In
ter
n
a
ti
o
n
a
l
El
e
c
tric M
a
c
h
in
e
a
n
d
Dr
ive
s Co
n
fer
e
n
c
e
,
p
p
.
5
0
5
-
5
1
2
,
2
0
1
3
.
[2
3
]
J.
S
riram
a
n
d
K
.
S
u
re
sh
k
u
m
a
r,
“
S
p
e
e
d
Co
n
tro
l
o
f
BL
DC
M
o
to
r
Us
in
g
F
u
z
z
y
L
o
g
ic
Co
n
tro
ll
e
r
Ba
se
d
o
n
S
e
n
so
rles
s
T
e
c
h
n
iq
u
e
,
”
In
ter
n
a
t
io
n
a
l
C
o
n
fe
re
n
c
e
o
n
Gr
e
e
n
Co
mp
u
ti
n
g
Co
m
mu
n
ica
t
io
n
a
n
d
El
e
c
tr
ica
l
En
g
in
e
e
rin
g
,
p
p
.
1
-
6
,
2
0
1
4
.
[2
4
]
P
.
A
lb
e
rto
s
a
n
d
A
.
S
a
la,
“
F
u
z
z
y
L
o
g
ic
Co
n
tro
ll
e
rs.
A
d
v
a
n
tag
e
s
a
n
d
Dra
w
b
a
c
k
,
”
VII
I
In
ter
n
a
ti
o
n
a
l
Co
n
g
re
ss
o
f
Au
to
m
a
ti
c
Co
n
tro
l,
v
o
l.
3
,
1
9
9
8
.
[2
5
]
K.
M
.
A
.
P
ra
sa
d
a
n
d
A
.
Un
n
ik
ris
h
n
a
n
,
“
F
u
z
z
y
S
li
d
in
g
M
o
d
e
Co
n
t
ro
l
o
f
a
P
e
rm
a
n
e
n
t
M
a
g
n
e
t
S
y
n
c
h
ro
n
o
u
s
M
o
t
o
r
w
it
h
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