I
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Appl
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(
I
J
AP
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)
Vo
l.
1
3
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No
.
4
,
Dece
m
b
er
20
2
4
,
p
p
.
9
4
4
~
9
5
1
I
SS
N:
2252
-
8
7
9
2
,
DOI
:
1
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.
1
1
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1
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.
v
1
3
.
i
4
.
pp
944
-
951
944
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:
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a
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ia
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co
m
Reduction
of t
o
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using
t
he DTC
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m
e
thod in
PMSM
wit
h e
x
te
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K
a
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Am
ba
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pu
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dh
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k
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r
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o
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Cheepurupa
lli K
rish
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Cha
it
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a
Sa
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3
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a
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r
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a
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a
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ra
k
a
s
h
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uk
k
u
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ha
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na
5
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pa
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i V
enk
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t
a
R
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j
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nn
a
6
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i La
litha
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a
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6
1
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RAC
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ticle
his
to
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y:
R
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Ma
r
2
9
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2
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g
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s
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two
m
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t
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r
c
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n
tro
l
a
lg
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rit
h
m
s:
d
irec
t
to
rq
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e
c
o
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tro
l
(DTC)
a
n
d
f
ield
-
o
rien
ted
c
o
n
tro
l
(
F
OC).
T
h
e
re
a
re
two
wa
y
s
th
a
t
a
v
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lt
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g
e
s
o
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e
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n
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rt
e
r
(VSI)
c
a
n
re
g
u
late
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rm
a
n
e
n
t
m
a
g
n
e
t
sy
n
c
h
r
o
n
o
u
s
m
o
t
o
r
(P
M
S
M
).
W
h
e
n
u
si
n
g
t
h
e
P
M
S
M
a
n
d
v
o
lt
a
g
e
so
u
rc
e
in
v
e
rter
(VSI)
,
d
e
a
d
ti
m
e
is
e
m
p
lo
y
e
d
to
t
u
rn
o
ff
b
o
th
th
e
u
p
p
e
r
a
n
d
l
o
we
r
sw
it
c
h
e
s
to
p
re
v
e
n
t
sh
o
r
t
c
ircu
it
s.
Ho
we
v
e
r,
b
y
su
p
p
l
y
in
g
th
e
P
M
S
M
wit
h
u
n
e
x
p
e
c
ted
p
o
larity
v
o
lt
a
g
e
s
a
t
th
e
VSI
o
u
t
p
u
t
v
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lt
a
g
e
,
t
h
is
sw
it
c
h
in
g
tec
h
n
iq
u
e
re
d
u
c
e
s
d
isto
rti
o
n
.
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is
c
h
a
ll
e
n
g
i
n
g
to
u
ti
li
z
e
th
e
se
n
so
r
to
d
irec
tl
y
d
e
tec
t
th
e
fa
u
lt
v
o
lt
a
g
e
t
h
a
t
re
su
l
ts
in
a
n
o
p
e
n
c
ircu
i
t.
T
h
is
wo
rk
e
x
a
m
in
e
s
th
e
n
o
n
li
n
e
a
rit
y
o
f
th
e
e
lec
tri
c
p
o
we
r
c
o
n
tr
o
ll
e
r
d
u
rin
g
d
e
a
d
ti
m
e
d
u
rin
g
P
M
S
M
o
p
e
ra
ti
o
n
u
sin
g
t
h
e
DTC
a
lg
o
rit
h
m
to
in
c
re
a
se
c
o
n
tro
l
sta
b
il
it
y
.
Th
e
stre
ss
d
istri
b
u
ti
o
n
is
e
stim
a
ted
u
sin
g
a
n
e
x
ten
d
e
d
Ka
lma
n
fil
t
e
r
(EKF
).
Ulti
m
a
tely
,
th
e
m
o
d
e
l
p
re
se
n
ted
in
th
is
st
u
d
y
v
e
rifi
e
d
th
e
i
n
c
re
a
s
e
in
sta
to
r
c
u
rre
n
t
a
n
d
to
r
q
u
e
o
u
tp
u
t
t
h
ro
u
g
h
sim
u
latio
n
s a
n
d
tes
ti
n
g
.
K
ey
w
o
r
d
s
:
Dir
ec
t to
r
q
u
e
c
o
n
tr
o
l
E
x
ten
d
ed
Kalm
a
n
f
ilter
PMSM
Sp
ac
e
v
ec
to
r
m
o
d
u
latio
n
T
o
r
q
u
e
r
ip
p
les
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Am
b
ar
ap
u
Su
d
h
ak
a
r
Dep
ar
tm
en
t o
f
E
lectr
ical
an
d
E
lectr
o
n
ics E
n
g
in
ee
r
i
n
g
,
GAT
E
S I
n
s
titu
te
o
f
T
ec
h
n
o
lo
g
y
Go
o
ty
,
An
d
h
r
a
Pra
d
esh
,
I
n
d
ia
E
m
ail:
am
b
ar
ap
u
s
u
d
h
ak
a
r
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
m
o
to
r
c
o
n
tr
o
l,
th
e
two
m
o
s
t ta
lk
ed
-
ab
o
u
t to
p
ics ar
e
d
ir
ec
t to
r
q
u
e
co
n
tr
o
l
(
DT
C
)
an
d
f
iel
d
-
o
r
ien
te
d
co
n
tr
o
l
(
FOC
)
.
Sin
ce
th
e
1
9
8
0
s
,
DT
C
alg
o
r
ith
m
s
h
av
e
b
ee
n
d
ev
elo
p
e
d
.
I
n
th
e
ea
r
ly
y
ea
r
s
o
f
th
e
asy
n
ch
r
o
n
o
u
s
m
o
to
r
b
u
s
in
ess
,
DT
C
alg
o
r
ith
m
s
wer
e
co
m
m
o
n
ly
u
tili
ze
d
.
Sy
n
ch
r
o
n
o
u
s
m
o
to
r
s
s
tar
ted
to
o
p
er
ate
u
s
in
g
DT
C
alg
o
r
ith
m
s
as
h
ig
h
s
p
ee
d
an
d
p
er
f
o
r
m
a
n
ce
b
ec
am
e
m
o
r
e
a
n
d
m
o
r
e
im
p
o
r
tan
t
in
th
e
au
to
m
o
b
ile
s
ec
to
r
.
T
h
e
DT
C
alg
o
r
ith
m
is
a
tech
n
iq
u
e
to
m
an
ag
e
th
e
m
o
to
r
to
r
q
u
e
an
d
f
lu
x
th
at
m
ak
es
u
s
e
o
f
a
h
y
s
ter
esis
co
n
tr
o
ller
as
th
e
s
witch
an
d
a
lo
o
k
-
up
ta
b
le
(
L
UT
)
o
f
t
h
e
s
tato
r
f
lu
x
c
o
m
m
an
d
with
th
e
to
r
q
u
e
co
m
m
an
d
v
alu
e
[
1
]
-
[
3
]
.
T
h
e
to
r
q
u
e
cu
r
v
e
o
f
th
e
co
n
v
en
tio
n
al
DT
C
m
eth
o
d
,
h
o
wev
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,
is
u
n
ab
le
to
m
ain
tain
th
e
an
g
le
b
etwe
en
t
h
e
s
tato
r
an
d
r
o
to
r
f
l
u
x
es
wh
en
th
e
h
y
s
ter
esis
co
n
tr
o
ller
a
n
d
L
UT
ar
e
em
p
lo
y
ed
.
T
h
er
e
a
r
e
n
u
m
er
o
u
s
co
n
t
r
o
l
s
o
lu
tio
n
s
em
p
lo
y
ed
to
a
d
d
r
es
s
th
e
is
s
u
e
o
f
th
e
d
ev
ice'
s
co
n
tin
u
al
r
o
tatio
n
.
Am
o
n
g
th
es
e
is
th
e
in
teg
r
ated
d
ir
ec
t
to
r
q
u
e
c
o
n
tr
o
l
s
p
ac
e
v
ec
to
r
m
o
d
u
latio
n
(
DT
C
-
SV
M
)
tech
n
iq
u
e,
w
h
ich
m
ai
n
ta
in
s
th
e
lo
a
d
an
g
le
d
ir
ec
tly
with
th
e
s
tato
r
f
lu
x
[
4
]
-
[
9
]
.
T
h
e
p
u
r
p
o
s
e
o
f
a
DT
C
-
SVM
co
n
tr
o
l
ap
p
r
o
ac
h
is
t
o
r
eg
u
late
to
r
q
u
e
b
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
R
ed
u
ctio
n
o
f to
r
q
u
e
r
ip
p
les u
s
in
g
th
e
DTC
-
S
V
M me
th
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in
P
MS
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ee
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ity
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f
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o
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ith
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s
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ate
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ased
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r
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en
t
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ar
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te
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is
tics
.
L
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y
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th
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in
v
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ter
v
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s
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ce
(
VSI
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s
en
s
o
r
is
in
s
talled
to
m
o
n
ito
r
th
e
m
o
to
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'
s
th
r
ee
-
p
h
ase
cu
r
r
e
n
t
v
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u
e
an
d
ca
lcu
late
th
e
s
tato
r
f
lu
x
m
ag
n
itu
d
e.
B
y
in
clu
d
in
g
n
o
is
e
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d
m
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s
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r
e
m
en
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it
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o
s
s
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ete
r
m
in
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e
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o
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en
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ich
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o
r
q
u
e
d
r
if
t
o
r
in
a
d
eq
u
ate
c
o
n
tr
o
l
[
1
0
]
-
[
1
2
]
.
W
h
en
o
p
en
i
n
g
an
d
clo
s
in
g
VSI
s
witch
in
g
p
o
in
ts
,
d
if
f
er
en
t
tec
h
n
iq
u
es
h
av
e
b
ee
n
e
m
p
lo
y
e
d
to
s
h
o
r
ten
th
e
tim
e
n
ee
d
e
d
to
av
o
id
s
h
o
r
t
cir
cu
its
[
1
3
]
-
[
1
8
]
.
W
h
ile
em
p
lo
y
in
g
t
h
e
FOC
alg
o
r
ith
m
,
th
e
m
ajo
r
i
ty
o
f
th
ese
tech
n
iq
u
es
m
o
d
if
y
th
e
tim
e
d
if
f
er
e
n
ce
ac
co
r
d
in
g
to
th
e
c
u
r
r
en
t
o
r
ien
tatio
n
.
Fu
r
th
er
m
o
r
e,
th
e
v
o
lta
g
e
p
r
o
d
u
ce
d
b
y
th
e
cu
r
r
en
t
tr
an
s
f
o
r
m
er
’
s
d
io
d
es
wh
ich
in
clu
d
es
th
e
in
v
er
ter
'
s
MO
SF
E
T
s
an
d
I
GB
T
s
d
o
es
n
o
t
en
ter
t
h
e
ass
o
ciate
d
ch
a
r
g
in
g
p
r
o
ce
s
s
.
T
h
e
cir
cu
it
b
r
ea
k
e
r
s
d
io
d
e
v
o
ltag
e
lo
s
s
was
also
m
ea
s
u
r
ed
in
a
s
u
b
s
eq
u
en
t
i
n
v
esti
g
atio
n
,
al
th
o
u
g
h
th
e
p
r
ec
is
e
f
ig
u
r
e
was n
o
t im
m
ed
iately
k
n
o
wn
[
1
9
]
.
L
astl
y
,
th
e
ex
ten
d
ed
Kalm
an
f
ilter
,
o
r
ex
ten
d
ed
Ka
lm
an
f
ilter
(
E
KF
)
,
is
n
o
t
a
r
eliab
le
way
to
d
etec
t
v
o
ltag
e
cu
r
r
e
n
t.
T
h
is
DT
C
co
n
tr
o
l
p
r
o
b
e
co
r
r
ec
ts
f
o
r
th
is
is
s
u
e.
T
h
e
Kalm
an
f
ilter
tech
n
iq
u
e
h
as
b
ee
n
th
e
f
o
cu
s
o
f
c
o
n
s
tan
t
r
esear
ch
s
in
ce
it
was
f
ir
s
t
ap
p
lied
to
s
y
n
c
h
r
o
n
o
u
s
m
o
to
r
s
in
1
9
8
3
[
2
0
]
.
N
u
m
er
o
u
s
p
er
m
a
n
en
t
m
ag
n
et
s
y
n
ch
r
o
n
o
u
s
m
o
t
o
r
(
PMSM
)
alg
o
r
ith
m
ic
d
o
m
ain
s
h
av
e
b
ee
n
th
e
s
u
b
ject
o
f
an
o
n
g
o
in
g
in
v
esti
g
atio
n
in
to
th
e
Kalm
an
f
ilter
[
2
1
]
-
[
2
3
]
.
Fu
r
t
h
er
m
o
r
e,
r
esear
ch
is
b
ein
g
co
n
d
u
cte
d
o
n
th
e
Kalm
an
f
ilter
ap
p
r
o
ac
h
[
2
4
]
-
[
2
6
]
.
Usi
n
g
th
e
FOC
alg
o
r
ith
m
,
p
h
y
s
ical
th
e
r
ap
y
h
as
b
ee
n
th
e
s
u
b
ject
o
f
th
e
m
ajo
r
ity
o
f
in
v
esti
g
atio
n
s
.
T
h
is
wo
r
k
p
r
o
p
o
s
es
a
m
eth
o
d
o
f
ca
lcu
latio
n
u
tili
zin
g
a
co
n
tin
u
o
u
s
Kalm
an
f
ilter
an
d
in
v
esti
g
ates
th
e
r
e
g
r
ess
io
n
p
r
o
d
u
ce
d
b
y
th
e
D
T
C
alg
o
r
ith
m
.
T
h
e
u
s
ef
u
ln
es
s
o
f
th
e
s
u
g
g
ested
m
eth
o
d
h
as b
ee
n
d
e
m
o
n
s
tr
ate
d
b
y
c
o
m
p
ar
is
o
n
,
an
d
th
e
co
n
t
r
o
ller
'
s
p
er
f
o
r
m
an
ce
h
as im
p
r
o
v
ed
.
2.
DT
C
–
SV
M
m
et
ho
d im
p
lem
ent
a
t
io
n in P
M
SM
An
alter
n
atin
g
cu
r
r
e
n
t
(
AC
)
s
y
n
ch
r
o
n
o
u
s
m
o
to
r
ex
cited
b
y
a
s
in
u
s
o
id
al
elec
tr
o
m
ag
n
etic
f
ield
(
E
MF)
wav
e
an
d
a
p
er
m
an
en
t
m
a
g
n
et
is
k
n
o
wn
as
a
p
er
m
an
en
t
m
a
g
n
et
s
y
n
ch
r
o
n
o
u
s
m
o
t
o
r
(
PMSM)
.
A
h
y
b
r
id
f
o
r
m
o
f
an
in
d
u
ctio
n
m
o
to
r
an
d
a
b
r
u
s
h
less
D
C
m
o
to
r
is
th
e
PMS
M.
I
ts
p
er
m
an
en
t m
a
g
n
et
r
o
t
o
r
an
d
s
tato
r
win
d
in
g
ar
e
s
im
ilar
to
th
o
s
e
o
f
a
DC
b
r
u
s
h
less
m
o
to
r
.
No
n
eth
eless
,
th
e
co
il
ar
r
an
g
e
m
en
t
in
th
e
s
tato
r
cr
ea
tes
a
s
in
u
s
o
id
al
cu
r
r
en
t
d
en
s
ity
in
v
ar
io
u
s
air
cu
r
r
en
ts
,
an
d
th
e
s
tato
r
co
n
s
tr
u
ctio
n
is
co
m
p
ar
a
b
le
to
a
s
y
n
ch
r
o
n
o
u
s
m
o
to
r
.
T
h
e
en
e
r
g
y
d
en
s
ity
o
f
t
h
e
s
tato
r
is
lar
g
er
th
a
n
th
at
o
f
co
m
p
ar
ab
le
-
p
r
iced
in
d
u
ctio
n
m
o
to
r
s
b
ec
au
s
e
th
e
en
er
g
y
is
n
o
t
d
is
p
er
s
ed
to
p
r
o
d
u
ce
a
m
ag
n
etic
f
ield
.
PMSM
g
en
er
ates
en
er
g
y
at
ze
r
o
s
p
ee
d
u
s
in
g
p
er
m
a
n
en
t
m
ag
n
ets;
h
o
wev
er
,
it
n
ee
d
s
a
d
ig
ital
d
ev
ice
to
f
u
n
ctio
n
.
Hi
g
h
-
p
er
f
o
r
m
an
ce
d
ev
ices
f
r
eq
u
en
tly
h
av
e
PMSM
in
s
talled
.
T
h
e
c
h
ar
ac
ter
is
tics
o
f
a
h
ig
h
-
p
er
f
o
r
m
a
n
ce
en
g
in
e
in
clu
d
e
ac
ce
ler
atio
n
f
r
o
m
ze
r
o
s
p
ee
d
,
to
r
q
u
e
co
n
tr
o
l a
cr
o
s
s
th
e
en
g
i
n
e
s
p
ee
d
r
an
g
e,
a
n
d
ac
ce
ler
atio
n
f
r
o
m
ze
r
o
s
p
ee
d
.
PMSM
p
r
o
v
id
es t
h
is
co
n
tr
o
l th
r
o
u
g
h
th
e
u
s
e
o
f
v
ec
to
r
co
n
tr
o
l
tech
n
o
lo
g
y
.
An
o
th
e
r
wo
r
d
th
at'
s
f
r
eq
u
en
tly
u
s
ed
to
c
h
ar
ac
ter
ize
v
ec
to
r
co
n
tr
o
l
tech
n
iq
u
es
is
f
ield
-
o
r
ie
n
ted
c
o
n
tr
o
l
(
FOC
)
.
T
h
e
v
ec
to
r
co
n
tr
o
l
alg
o
r
ith
m
'
s
b
asic
co
n
ce
p
t
i
s
to
s
p
lit
th
e
s
tato
r
in
to
two
h
al
v
es,
o
n
e
o
f
wh
ich
p
r
o
d
u
ce
s
to
r
q
u
e
a
n
d
t
h
e
o
th
e
r
o
f
wh
ich
p
r
o
d
u
ce
s
m
ag
n
etis
m
.
W
h
en
s
ep
ar
ated
,
ea
ch
o
b
ject
ca
n
b
e
co
n
tr
o
lled
s
ep
ar
ately
.
T
h
e
p
o
wer
co
n
t
r
o
l
v
al
u
e
an
d
s
tato
r
f
lu
x
co
n
tr
o
l
v
alu
e
ar
e
g
iv
en
to
th
e
co
n
tr
o
l
m
o
d
u
le
in
a
m
an
n
er
as
in
to
th
e
s
tan
d
ar
d
DT
C
p
r
o
ce
d
u
r
e.
T
h
e
DT
C
-
SVM
co
n
t
r
o
ller
,
h
o
wev
er
,
d
o
es
n
o
t
u
tili
ze
a
p
r
o
p
o
r
tio
n
al
in
teg
r
al
(
PI
)
c
o
n
tr
o
ller
b
u
t
in
s
tead
a
h
y
s
ter
esis
co
n
tr
o
ller
to
o
u
tp
u
t
t
h
e
er
r
o
n
eo
u
s
to
r
q
u
e
v
alu
e
b
ased
o
n
th
e
co
m
m
an
d
an
g
le
δ*
.
Fu
r
th
er
m
o
r
e,
b
y
esti
m
atin
g
t
h
e
m
o
to
r
c
u
r
r
en
t
a
n
d
s
tato
r
cu
r
r
en
t,
t
h
e
s
tato
r
f
lu
x
co
n
tr
o
ller
g
en
er
ates
an
an
g
le
i
n
s
tr
u
ctio
n
th
at
p
er
m
its
th
e
o
u
t
p
u
t
o
f
th
e
s
tato
r
cu
r
r
en
t.
Usi
n
g
t
h
e
cu
r
r
en
t
an
g
le
an
d
v
o
ltag
e
co
m
m
an
d
an
g
le
f
r
o
m
th
e
s
tato
r
f
lu
x
co
n
t
r
o
ller
,
t
h
e
SVM
r
ec
eiv
es
th
e
s
tato
r
v
o
lta
g
e
v
ec
to
r
co
m
m
a
n
d
v
alu
e
an
d
an
g
le
co
m
m
an
d
v
al
u
e.
T
h
e
d
if
f
e
r
en
ce
b
etwe
en
th
e
s
tato
r
's
cu
r
r
en
t
p
o
s
itio
n
p
r
o
d
u
ce
d
b
y
th
e
DT
C
-
SVM
alg
o
r
ith
m
a
n
d
th
e
DT
C
-
SVM
co
n
tr
o
l
b
l
o
ck
d
iag
r
a
m
cr
ea
ted
b
y
th
e
co
n
v
en
tio
n
al
DT
C
ap
p
r
o
ac
h
i
s
d
ep
icted
in
Fig
u
r
e
1
.
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
am
o
f
th
e
DT
C
-
SVM
co
n
tr
o
l te
ch
n
iq
u
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
3
,
No
.
4
,
Dece
m
b
er
20
2
4
:
9
4
4
-
951
946
T
h
e
v
ec
to
r
lo
ad
a
n
g
le,
d
en
o
te
d
b
y
δ,
m
ig
h
t
s
tay
u
n
ch
a
n
g
ed
.
I
f
th
e
s
tato
r
cu
r
r
en
t
is
o
v
e
r
esti
m
ated
d
u
e
to
th
e
δ*
er
r
o
r
,
to
r
q
u
e
d
iv
er
g
en
ce
will
ar
is
e
f
r
o
m
an
in
co
r
r
ec
t
ass
ess
m
en
t.
T
h
e
DT
C
-
SVM
ap
p
r
o
ac
h
m
ain
tain
s
a
co
n
s
tan
t a
n
g
le
θ
an
d
en
ab
les th
e
s
tato
r
f
lu
x
to
b
e
p
o
s
itio
n
ed
in
a
p
o
s
itio
n
v
ec
t
o
r
b
y
alter
n
atin
g
th
e
s
tates o
f
th
e
s
ix
s
witch
es in
a
s
in
g
le
cy
cle.
3.
AP
P
L
I
CA
T
I
O
N
O
F
E
XT
E
NDED K
A
L
M
A
N
F
I
L
T
E
R
I
N
P
M
S
M
CO
NT
RO
L
R.
E
.
Kalm
an
cr
e
ated
th
e
Kalm
an
f
ilter
i
n
1
9
6
0
.
T
h
e
Kalm
a
n
f
ilter
h
as
b
ee
n
th
e
s
u
b
ject
o
f
ex
ten
s
iv
e
s
tu
d
y
an
d
u
s
ef
u
l
ap
p
licatio
n
s
as
a
r
esu
lt
o
f
d
ev
elo
p
m
en
ts
in
d
ig
ital
co
m
p
u
tin
g
.
Kalm
an
f
ilter
s
ar
e
u
s
ed
in
m
an
y
way
s
,
in
cl
u
d
in
g
in
wea
th
er
,
m
an
u
f
ac
tu
r
i
n
g
,
a
n
d
n
a
v
i
g
atio
n
.
T
h
e
Kalm
an
f
ilter
is
a
tech
n
iq
u
e
u
s
ed
to
r
em
o
v
e
m
is
s
in
g
d
ata
f
r
o
m
i
n
d
ir
ec
t
(
an
d
n
o
is
y
)
m
ea
s
u
r
e
m
en
ts
.
I
t
cr
ea
tes
an
id
ea
l
d
y
n
am
ic
s
y
s
tem
f
o
r
u
n
d
er
s
tan
d
i
n
g
th
e
s
tatis
tic
s
o
f
b
o
th
lin
ea
r
an
d
d
is
cr
ete
(
m
in
im
u
m
v
ar
ian
ce
)
au
d
io
co
m
p
o
n
e
n
ts
.
Fig
u
r
e
2
d
ep
icts
th
e
Kalm
an
f
ilter
'
s
c
o
n
s
tr
u
ctio
n
.
E
KF
is
a
g
r
ea
t
iter
atio
n
tech
n
iq
u
e
f
o
r
esti
m
atin
g
th
e
s
tate
o
f
d
y
n
am
ic,
n
o
n
lin
ea
r
s
y
s
tem
s
an
d
is
b
ased
o
n
t
h
e
least
s
q
u
ar
es
m
eth
o
d
.
Pu
t
o
th
er
wis
e,
it
is
a
cu
m
u
lativ
e
ap
p
r
o
x
im
atio
n
o
f
th
e
s
tate
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
o
f
a
s
t
o
ch
asti
c
s
y
s
tem
with
m
ea
s
u
r
em
en
t
n
o
is
e
an
d
a
r
an
d
o
m
Gau
s
s
ian
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r
o
ce
s
s
.
Sin
ce
th
e
s
tate
m
o
d
el
is
n
o
n
l
in
ea
r
,
E
KF
ca
n
b
e
u
s
ed
to
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r
ed
ict
th
e
s
tate
tr
an
s
itio
n
.
I
n
th
is
ca
s
e,
th
e
b
ac
k
E
MF
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tr
ea
ted
as a
tr
an
s
itio
n
s
tate.
A
d
is
cr
ete
n
o
n
lin
ea
r
m
o
d
el
with
n
o
is
e
g
iv
en
as
(
1
)
.
{
(
+
1
)
=
(
(
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,
(
)
)
+
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)
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=
ℎ
(
(
)
+
(
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(
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Fig
u
r
e
2
.
B
lo
ck
d
iag
r
am
o
f
D
T
C
-
SVM
co
n
tr
o
l u
s
in
g
Kalm
a
n
f
ilter
-
b
ased
e
x
ten
d
ed
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lt
o
b
s
er
v
er
d
esig
n
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
s
im
u
latio
n
r
esu
lts
illu
s
tr
ate
th
at
th
e
m
o
t
o
r
ca
n
n
o
t
b
e
m
a
d
e
to
ch
a
n
g
e
s
p
ee
d
wh
en
th
e
l
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ad
v
ar
ies
o
n
ce
it
r
ea
c
h
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a
f
ix
e
d
v
al
u
e.
T
h
e
s
p
ac
e
v
ec
t
o
r
p
u
ls
e
wid
th
m
o
d
u
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n
(
SVPW
M
)
m
eth
o
d
also
in
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ea
s
es
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e
PMSM
s
et
tlin
g
tim
e.
T
h
e
s
p
ee
d
ch
ar
ac
ter
is
tics
o
f
th
e
m
ac
h
in
e
ar
e
as
s
h
o
wn
in
Fig
u
r
e
3
.
B
ef
o
r
e
ad
d
itio
n
al
to
r
q
u
e
o
cc
u
r
s
,
a
3
0
N
-
M
to
r
q
u
e
is
ap
p
lied
to
th
e
m
o
to
r
a
f
ter
0
.
2
s
ec
o
n
d
s
,
f
o
llo
we
d
b
y
a
d
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ay
o
f
0
.
0
1
s
ec
o
n
d
s
an
d
1
0
%
r
ip
p
les
as
s
h
o
wn
in
Fig
u
r
e
4
.
Firstl
y
,
th
e
m
o
to
r
d
r
aws
ap
p
r
o
x
im
ately
2
0
A
o
f
p
e
ak
o
v
er
s
h
o
o
t
cu
r
r
e
n
t
as
s
h
o
wn
in
Fig
u
r
e
5
.
Af
ter
a
p
p
ly
in
g
Kalm
an
f
ilter
alg
o
r
ith
m
,
with
a
d
elay
o
f
0
.
0
0
1
a
f
ter
0
.
2
s
ec
o
n
d
s
,
w
h
ich
y
ield
s
3
%
r
ip
p
les
as
s
h
o
wn
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n
Fig
u
r
e
6
an
d
with
d
elay
o
f
0
.
2
5
s
ec
o
n
d
s
,
wh
e
n
th
e
m
o
t
o
r
is
s
tab
le,
it
u
s
e
s
ap
p
r
o
x
im
ately
7
A
o
f
o
v
e
r
s
h
o
o
t
cu
r
r
en
t.
So
,
a
f
ter
0
.
2
5
s
ec
o
n
d
s
,
PMSM
will
co
n
s
u
m
e
ab
o
u
t
7
A
o
f
c
u
r
r
en
t
as
s
h
o
wn
in
Fig
u
r
e
7
.
Fig
u
r
e
3
.
Sp
ee
d
o
f
PMSM
with
o
u
t K
alm
an
f
ilter
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u
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e
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o
r
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u
e
with
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t
u
s
in
g
Kalm
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f
ilter
Fig
u
r
e
5
.
3
-
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ase
s
tato
r
c
u
r
r
en
t w
ith
o
u
t u
s
in
g
Kalm
an
f
ilter
Fig
u
r
e
6
.
T
o
r
q
u
e
ch
ar
ac
ter
is
ti
cs
with
Kalm
an
f
ilter
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SS
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er
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u
r
e
7
.
3
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p
h
ase
s
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r
c
u
r
r
en
t
u
s
in
g
Kalm
an
f
ilter
Fro
m
th
e
r
esu
lts
o
b
tain
ed
as
s
h
o
wn
in
T
ab
le
1
,
th
e
t
o
r
q
u
e
r
ip
p
le
ca
n
b
e
d
ec
r
ea
s
ed
b
y
7
%
an
d
th
e
p
ea
k
o
v
er
s
h
o
o
t
o
f
th
e
s
tato
r
c
u
r
r
en
t
ca
n
b
e
r
ed
u
ce
d
t
o
7
A.
T
h
e
p
ea
k
-
to
-
p
ea
k
r
ip
p
le
v
alu
e
o
f
th
e
s
tato
r
cu
r
r
en
t
ca
n
b
e
r
ed
u
ce
d
u
p
to
4
0
%
b
y
ap
p
ly
in
g
a
Kalm
an
f
ilter
.
T
h
e
co
m
p
ar
is
o
n
o
f
d
if
f
e
r
en
t
p
a
r
am
eter
s
b
ef
o
r
e
an
d
af
ter
th
e
im
p
lem
e
n
tatio
n
o
f
th
e
Kalm
an
f
ilter
is
s
h
o
wn
in
T
a
b
le
1
.
T
ab
le
1
.
Par
am
eter
s
o
f
PMSM
with
an
d
with
o
u
t
u
s
in
g
Kalm
an
f
ilter
alg
o
r
ith
m
P
a
r
a
me
t
e
r
s
W
i
t
h
o
u
t
K
a
l
ma
n
f
i
l
t
e
r
W
i
t
h
K
a
l
ma
n
f
i
l
t
e
r
To
r
q
u
e
r
i
p
p
l
e
s
1
0
%
3%
P
e
a
k
o
v
e
r
s
h
o
o
t
o
f
st
a
t
o
r
c
u
r
r
e
n
t
20
A
7
A
S
t
a
t
o
r
c
u
r
r
e
n
t
r
i
p
p
l
e
2
.
4
0
.
6
5.
CO
NCLU
SI
O
N
T
h
is
f
u
n
ctio
n
in
tr
o
d
u
ce
s
E
KF's
s
p
ee
d
s
en
s
o
r
f
o
r
s
p
ee
d
co
n
tr
o
l
(
DT
C
)
to
esti
m
ate
r
o
to
r
p
o
s
itio
n
an
d
s
p
ee
d
.
T
h
e
alg
o
r
ith
m
wo
r
k
s
at
v
ar
io
u
s
s
p
ee
d
s
.
T
h
e
r
esu
lts
o
f
th
e
Simu
lin
k
m
o
d
el
o
f
DT
C
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s
p
ee
d
co
n
tr
o
l
-
b
ased
PMSM
ar
e
v
er
if
ied
.
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io
u
s
p
ar
am
eter
s
lik
e
s
p
ee
d
,
s
tato
r
cu
r
r
e
n
t
,
an
d
t
o
r
q
u
e
ch
ar
ac
ter
is
tics
o
f
PMSM
ar
e
an
aly
ze
d
b
o
th
with
an
d
with
o
u
t
t
h
e
Kalm
an
f
ilt
er
.
T
h
er
e
is
a
s
ig
n
if
ican
t
im
p
r
o
v
em
en
t
i
n
v
a
r
io
u
s
p
ar
am
eter
s
lik
e
r
ed
u
ctio
n
in
to
r
q
u
e
r
ip
p
le,
d
ec
r
ea
s
ed
m
ag
n
it
u
d
e
o
f
p
ea
k
o
v
er
s
h
o
o
t
s
tato
r
c
u
r
r
en
t
,
an
d
r
ed
u
ce
d
r
ip
p
le
in
th
e
s
tato
r
cu
r
r
en
t
b
y
im
p
lem
en
tin
g
th
e
Kalm
an
f
ilter
.
T
h
is
im
p
r
o
v
es
th
e
p
er
f
o
r
m
an
ce
o
f
PMSM
an
d
h
en
ce
f
u
r
th
er
ca
n
b
e
e
x
ten
d
ed
b
y
u
s
in
g
v
ar
io
u
s
in
tellig
en
t c
o
n
tr
o
ller
s
lik
e
n
eu
r
al
an
d
f
u
zz
y
co
n
tr
o
ller
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
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ed
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ctio
n
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f to
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q
u
e
r
ip
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les u
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th
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RE
F
E
R
E
NC
E
S
[
1
]
I
.
Ta
k
a
h
a
s
h
i
a
n
d
T.
N
o
g
u
c
h
i
,
“
A
n
e
w
q
u
i
c
k
-
r
e
s
p
o
n
s
e
a
n
d
h
i
g
h
-
e
f
f
i
c
i
e
n
c
y
c
o
n
t
r
o
l
st
r
a
t
e
g
y
o
f
a
n
i
n
d
u
c
t
i
o
n
mo
t
o
r
,
”
I
E
E
E
T
ra
n
s
a
c
t
i
o
n
s
o
n
I
n
d
u
st
r
y
A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
I
A
-
2
2
,
n
o
.
5
,
p
p
.
8
2
0
–
8
2
7
,
S
e
p
.
1
9
8
6
,
d
o
i
:
1
0
.
1
1
0
9
/
TI
A
.
1
9
8
6
.
4
5
0
4
7
9
9
.
[
2
]
M
.
D
e
p
e
n
b
r
o
c
k
,
“
D
i
r
e
c
t
se
l
f
-
c
o
n
t
r
o
l
(
D
S
C
)
o
f
i
n
v
e
r
t
e
r
f
e
d
i
n
d
u
k
t
i
o
n
mac
h
i
n
e
,
”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
P
o
w
e
r
El
e
c
t
r
o
n
i
c
s
,
v
o
l
.
3
,
n
o
.
4
,
p
p
.
4
2
0
-
4
2
9
,
O
c
t
.
1
9
8
8
,
d
o
i
:
1
0
.
1
1
0
9
/
6
3
.
1
7
9
6
3
.
[
3
]
J.
-
K
.
K
a
n
g
,
D
.
-
W
.
C
h
u
n
g
,
a
n
d
S
.
-
K
.
S
u
l
,
“
D
i
r
e
c
t
t
o
r
q
u
e
c
o
n
t
r
o
l
o
f
i
n
d
u
c
t
i
o
n
ma
c
h
i
n
e
w
i
t
h
v
a
r
i
a
b
l
e
a
m
p
l
i
t
u
d
e
c
o
n
t
r
o
l
o
f
f
l
u
x
a
n
d
t
o
r
q
u
e
h
y
st
e
r
e
s
i
s
b
a
n
d
s,
”
i
n
I
E
EE
I
n
t
e
r
n
a
t
i
o
n
a
l
E
l
e
c
t
r
i
c
M
a
c
h
i
n
e
s
a
n
d
D
r
i
v
e
s
C
o
n
f
e
r
e
n
c
e
.
I
E
MDC’
9
9
.
Pro
c
e
e
d
i
n
g
s
(
C
a
t
.
N
o
.
9
9
EX
2
7
2
)
,
1
9
9
9
,
p
p
.
6
4
0
–
642
,
d
o
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:
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0
.
1
1
0
9
/
I
EM
D
C
.
1
9
9
9
.
7
6
9
2
0
0
.
[
4
]
D
.
S
w
i
e
r
c
z
y
n
s
k
i
a
n
d
M
.
P
.
K
a
z
mi
e
r
k
o
w
sk
i
,
“
D
i
r
e
c
t
t
o
r
q
u
e
c
o
n
t
r
o
l
o
f
p
e
r
m
a
n
e
n
t
m
a
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[
5
]
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.
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l
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O
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.
[
6
]
D
.
S
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k
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.
P
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.
[
7
]
M
.
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l
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M
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.
K
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[
8
]
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2
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1
8
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.
[
9
]
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0
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s fo
r
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1
1
]
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.
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ma
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[
1
2
]
S.
-
Y
.
K
i
m,
W
.
Le
e
,
M
.
-
S
.
R
h
o
,
a
n
d
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.
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r
k
,
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f
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me
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mat
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9
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.
[
1
3
]
N
.
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r
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sa
k
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,
T.
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,
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.
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p
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me
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m
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n
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h
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o
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m
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r
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v
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,
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I
EEE
T
ra
n
s
a
c
t
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s
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E
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C
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6
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5
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6
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.
[
1
4
]
N
.
U
r
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sa
k
i
,
T.
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,
K
.
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b
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n
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d
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p
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d
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me
c
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s
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n
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e
r
t
e
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f
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d
m
o
t
o
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d
r
i
v
e
s,”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
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n
P
o
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El
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p
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5
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0
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4
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4
6
.
[
1
5
]
N
.
U
r
a
sa
k
i
,
T.
S
e
n
j
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u
,
K
.
U
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d
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,
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A
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d
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me
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c
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n
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.
2
9
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h
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.
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.
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3
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3
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)
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2
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,
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EC
O
N
.
2
0
0
3
.
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2
8
0
2
3
3
.
[
1
6
]
H
.
C
h
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h
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h
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r
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fro
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ra
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m
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m
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c
a
n
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c
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tac
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m
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iet.
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imilarly
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c
a
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c
o
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m
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:
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siv
a
k
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m
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r@k
lu
n
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v
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.
i
n
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Ne
la
tu
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Na
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d
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P
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Un
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lan
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Re
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c
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n
d
a
p
ra
k
a
sh
n
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latu
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m
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.
c
o
m
.
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