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[
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f
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m
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r
,
th
e
s
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te
m
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m
p
le
m
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D
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2.
P
M
S
M
M
AT
H
E
M
AT
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CAL
M
O
DE
L
AND
D
I
RE
CT
T
O
RQ
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CO
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RO
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T
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s
tato
r
f
lu
x
li
n
k
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ψs
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d
r
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f
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ca
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w
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i
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e
r
o
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r
r
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er
en
ce
f
r
a
m
e
(
d
-
q
)
,
s
tato
r
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r
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(
d
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s
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a
n
d
s
tatio
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ar
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r
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en
ce
f
r
a
m
e(
α
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β)
as
s
h
o
w
n
in
Fig
u
r
e
1
[
9
]
-
[
1
2
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.
(
1
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(
2
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(
3
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(
4
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(
5
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W
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n
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o
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8
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.
Fig
u
r
e
1
.
T
h
e
s
tato
r
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d
r
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to
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l
u
x
li
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in
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en
t r
e
f
er
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(7
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I
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8
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I
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3
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ter
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al
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3.
SPAC
E
V
E
C
T
O
R
M
O
DULAT
I
O
N
T
h
e
m
ai
n
ad
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n
ta
g
es
o
f
t
h
e
s
p
ac
e
v
ec
to
r
m
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d
u
latio
n
(
S
VM
)
ar
e:
A
1
5
%
in
cr
ea
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e
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n
DC
l
in
k
v
o
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g
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u
tili
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m
p
ar
ed
w
it
h
t
h
e
s
i
n
e
-
tr
ian
g
le
tec
h
n
iq
u
e.
L
o
w
er
h
ar
m
o
n
ic
co
n
ten
t,
p
ar
ticu
lar
l
y
a
t
h
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g
h
m
o
d
u
latio
n
in
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ice
s
co
m
p
ar
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w
it
h
t
h
e
s
i
n
e
-
tr
ian
g
le
tec
h
n
iq
u
e
[
1
1
]
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T
h
e
v
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e
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v
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s
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Fi
g
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2
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m
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ter
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0
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t7
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r
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1
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Fig
u
r
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2
.
Vo
ltag
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4.
I
NT
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RVA
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2
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lled
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p
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1
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1
8
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I
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P
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&
Dr
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I
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N:
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u
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MS
M
Dri
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a
h
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h
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MF
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n
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t
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b
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t
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tai
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FOU)
w
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n
ce
r
tai
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tie
s
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e
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h
ap
e
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d
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o
s
itio
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o
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th
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1
f
u
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y
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et.
Sh
o
w
n
i
n
Fi
g
u
r
e
3
.
An
UM
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n
d
a
L
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ar
e
t
w
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f
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r
th
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an
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n
ter
v
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t
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p
e
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MF.
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h
e
UM
F
is
a
s
u
b
s
et
t
h
at
h
a
s
th
e
m
ax
i
m
u
m
m
e
m
b
er
s
h
ip
g
r
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e
o
f
th
e
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d
th
e
L
MF
is
a
s
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b
s
et
th
at
h
as
t
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m
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m
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m
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e
m
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ip
g
r
ad
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o
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th
e
FO
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Fi
g
u
r
e
4
.
Fig
u
r
e
3
.
B
lo
ck
d
iag
r
a
m
o
f
a
P
MSM
d
r
iv
e
w
it
h
DT
C
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SVM
s
y
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te
m
Fig
u
r
e
4
.
Me
m
b
er
s
h
ip
Fu
n
ctio
n
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f
F
u
zz
y
t
y
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e
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2
A
I
T
2
FL
S
co
n
s
is
ts
o
f
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o
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r
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asic
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m
e
n
t
s
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g
u
r
e
5
:
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e
t
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f
u
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ier
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f
u
zz
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ase,
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.
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h
e
I
T
2
FL
s
y
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k
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s
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o
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h
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ase
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ce
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w
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f
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Af
ter
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e
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tain
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s
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tp
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ts
t
h
at
ar
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s
e
n
t to
th
e
ac
t
u
ato
r
s
[
1
4
]
-
[
1
6
]
.
Fig
u
r
e
5
.
C
o
n
f
ig
u
r
atio
n
o
f
a
f
u
zz
y
t
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2
lo
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y
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te
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th
a
t
u
s
i
n
g
I
T
2
F
s
ets
to
r
ep
r
esen
t
t
h
e
i
n
p
u
ts
a
n
d
/o
r
o
u
tp
u
ts
o
f
FLCs
h
as
m
a
n
y
ad
v
an
ta
g
es
w
h
e
n
co
m
p
ar
ed
to
t
y
p
e
-
1
f
u
zz
y
s
ets
;
w
e
s
u
m
m
ar
ies s
o
m
e
o
f
th
e
s
e
ad
v
an
tag
e
s
a
s
f
o
llo
w
s
:
1.
As
th
e
t
y
p
e
-
2
f
u
zz
y
s
e
t
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
ar
e
t
h
e
m
s
el
v
es
f
u
zz
y
a
n
d
co
n
tai
n
a
f
o
o
tp
r
in
t
o
f
u
n
ce
r
tai
n
t
y
,
t
h
e
y
ca
n
m
o
d
el
a
n
d
h
a
n
d
le
t
h
e
lin
g
u
is
tic
a
n
d
n
u
m
er
ical
u
n
ce
r
tai
n
ties
as
s
o
ciate
d
w
ith
t
h
e
in
p
u
t
s
an
d
o
u
tp
u
t
s
o
f
t
h
e
FLC.
T
h
er
ef
o
r
e,
FL
C
s
t
h
at
ar
e
b
ased
o
n
ty
p
e
-
2
f
u
z
z
y
s
et
s
w
il
l
h
a
v
e
th
e
p
o
ten
tial to
p
r
o
d
u
ce
a
b
etter
p
er
f
o
r
m
an
ce
t
h
a
n
t
y
p
e
-
1
F
L
C
s
w
h
e
n
d
ea
lin
g
w
it
h
u
n
ce
r
tai
n
ti
es.
2.
Usi
n
g
t
y
p
e
-
2
f
u
zz
y
s
et
s
to
r
ep
r
esen
t
t
h
e
F
L
C
i
n
p
u
ts
a
n
d
o
u
t
p
u
ts
w
ill
r
es
u
lt
i
n
t
h
e
r
ed
u
ctio
n
o
f
t
h
e
F
L
C
r
u
le
b
ase
w
h
e
n
co
m
p
ar
ed
to
u
s
i
n
g
t
y
p
e
-
1
f
u
zz
y
s
e
ts
a
s
t
h
e
u
n
ce
r
tai
n
t
y
r
ep
r
esen
ted
i
n
th
e
f
o
o
tp
r
in
t
o
f
u
n
ce
r
tai
n
t
y
i
n
t
y
p
e
-
2
f
u
zz
y
s
et
s
lets
u
s
co
v
er
t
h
e
s
a
m
e
r
an
g
e
as
t
y
p
e
-
1
f
u
zz
y
s
et
s
w
it
h
a
s
m
aller
n
u
m
b
er
o
f
lab
els.
T
h
e
r
u
le
r
ed
u
ctio
n
will b
e
g
r
ea
ter
as th
e
n
u
m
b
er
o
f
th
e
F
L
C
i
n
p
u
ts
i
n
cr
ea
s
es
.
3.
E
ac
h
in
p
u
t
an
d
o
u
tp
u
t
w
ill
b
e
r
ep
r
esen
ted
b
y
a
lar
g
e
n
u
m
b
er
o
f
t
y
p
e
-
1
f
u
zz
y
s
ets
w
h
ic
h
ar
e
em
b
ed
d
ed
in
t
h
e
t
y
p
e
-
2
f
u
zz
y
s
et
s
.
T
h
e
u
s
e
o
f
s
u
c
h
a
lar
g
e
n
u
m
b
er
o
f
t
y
p
e
-
1
f
u
zz
y
s
et
s
to
d
escr
ib
e
th
e
i
n
p
u
t
an
d
o
u
tp
u
t
v
ar
iab
le
s
allo
w
s
f
o
r
a
d
etailed
d
escr
ip
tio
n
o
f
th
e
an
a
l
y
tical
co
n
tr
o
l
s
u
r
f
ac
e
as
t
h
e
ad
d
itio
n
o
f
th
e
ex
tr
a
lev
el
s
o
f
clas
s
i
f
icatio
n
g
i
v
es a
m
u
c
h
s
m
o
o
th
er
co
n
tr
o
l s
u
r
f
ac
e
a
n
d
r
esp
o
n
s
e.
4.
I
t
h
as
b
ee
n
s
h
o
w
n
th
at
t
h
e
e
x
tr
a
d
eg
r
ee
s
o
f
f
r
ee
d
o
m
p
r
o
v
id
ed
b
y
t
h
e
f
o
o
tp
r
in
t
o
f
u
n
ce
r
ta
in
t
y
e
n
ab
les
a
t
y
p
e
-
2
F
L
C
t
o
p
r
o
d
u
ce
o
u
tp
u
ts
t
h
at
ca
n
n
o
t
b
e
ac
h
iev
ed
b
y
t
y
p
e
-
1
FLCs
w
it
h
th
e
s
a
m
e
n
u
m
b
er
o
f
m
e
m
b
er
s
h
ip
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t
,
Vo
l.
9
,
No
.
3
,
Sep
tem
b
er
2
0
1
8
:
1
0
9
8
–
1
1
0
5
1102
A
s
tan
d
ar
d
ap
p
r
o
ac
h
f
o
r
s
p
ee
d
co
n
tr
o
l
in
d
r
iv
es
is
t
h
e
u
s
e
o
f
a
P
I
c
o
n
tr
o
ller
.
R
ec
en
t
d
ev
elo
p
m
e
n
t
s
i
n
ar
tif
icial
i
n
telli
g
e
n
ce
b
ased
co
n
tr
o
l
h
av
e
b
r
o
u
g
h
t
i
n
to
f
o
cu
s
a
p
o
s
s
ib
ilit
y
o
f
r
ep
lacin
g
a
PI
co
n
tr
o
ller
w
ith
a
f
u
zz
y
lo
g
ic
(
FL
)
.
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
f
o
r
in
p
u
t
an
d
o
u
tp
u
t
v
ar
iab
le
s
f
o
r
th
e
P
I
-
t
y
p
e
f
u
zz
y
t
y
p
e
-
2
ar
e
s
p
ee
d
er
r
o
r
(
E
)
,
ch
an
g
e
o
f
s
p
ee
d
er
r
o
r
(
ΔE
)
,
an
d
ch
an
g
e
o
f
to
r
q
u
e
a
s
o
u
tp
u
t (
Δ
T
)
.
5.
E
XP
E
R
I
M
E
NT
A
L
DRI
VE
CO
NF
I
G
URA
T
I
O
N
T
h
e
lab
o
r
ato
r
y
s
et
-
u
p
b
u
i
lt
f
o
r
ex
p
er
i
m
e
n
tal
te
s
ts
o
f
t
h
e
P
MSM
d
r
iv
e
s
y
s
te
m
co
n
s
is
ts
o
f
t
h
e
f
o
llo
w
in
g
m
ai
n
p
ar
ts
:
1.
P
MSM
B
ec
k
h
o
f
f
A
M
2
4
7
Ser
ies
w
ith
r
eso
l
v
er
.
2.
B
ec
k
h
o
o
f
A
X2
5
1
3
s
er
ies d
ig
it
al
s
er
v
o
a
m
p
li
f
ier
.
3.
DSP
(
DSP
A
C
E
DS1
1
0
2
)
m
o
d
el.
4.
P
C
P
e
n
tiu
m
2
,
3
2
MB
o
f
R
A
M
,
1
GB
o
f
R
OM
w
it
h
W
in
d
o
w
s
an
d
DSP
P
r
o
ce
s
s
o
r
.
5.
P
C
P
en
tiu
m
4
,
C
P
U
3
GHz
,
1
GB
o
f
R
A
M
w
it
h
W
in
d
o
w
s
X
P
an
d
B
ec
k
h
o
f
f
Mo
to
r
s
o
f
t
w
ar
e.
6.
MCR
T
4
8
2
0
0
V
d
ig
ital to
r
q
u
e
tr
an
s
d
u
ce
r
.
7.
T
ek
tr
o
n
ix
d
ig
ital
s
to
r
ag
e
o
s
cil
lo
s
co
p
e
T
P
S2
0
2
4
m
o
d
el.
8.
Dc
g
en
er
ato
r
an
d
r
esis
tiv
e
lo
a
d
T
h
e
o
v
er
all
s
y
s
te
m
a
s
s
h
o
w
n
in
Fi
g
u
r
e
6
co
n
s
i
s
ts
o
f
t
h
e
P
MSM
w
ith
b
u
ilt
i
n
r
eso
lv
er
an
d
s
h
a
f
t
en
co
d
er
in
o
r
d
er
to
m
ea
s
u
r
e
t
h
e
m
o
to
r
p
o
s
itio
n
,
a
n
o
th
er
co
m
p
o
n
en
t
i
n
th
e
s
y
s
te
m
i
s
th
e
B
E
C
KHOFF
d
i
g
ita
l
s
er
v
o
a
m
p
li
f
ier
w
h
ic
h
d
r
iv
e
t
h
e
m
o
to
r
u
s
i
n
g
s
p
ac
e
v
ec
to
r
P
W
M
tech
n
iq
u
e,
al
s
o
,
th
er
e
a
r
e
o
u
tp
u
t
g
r
o
u
p
o
f
s
en
s
o
r
s
to
m
ea
s
u
r
e
th
e
ac
tu
a
l
m
o
to
r
cu
r
r
en
ts
,
v
o
ltag
e,
a
n
d
to
r
q
u
e.
T
h
is
s
y
s
te
m
i
s
co
n
tr
o
lled
u
s
i
n
g
DSP
i
m
p
le
m
en
ted
i
n
co
m
p
u
ter
s
y
s
t
e
m
u
s
i
n
g
Ma
tlab
s
o
f
t
w
ar
e.
6.
SI
M
UL
AT
I
O
N
A
ND
E
XP
E
RIM
E
NT
AL
R
E
S
UL
T
S
T
h
er
e
ar
e
m
a
n
y
co
n
tr
o
l
s
tr
ate
g
ies
f
o
r
DT
C
P
MSM
d
r
iv
es.
Fu
zz
y
t
y
p
-
1
w
as
u
s
ed
in
co
n
t
r
o
l
o
f
DT
C
P
MSM
d
r
iv
es
a
n
d
n
o
w
w
e
a
p
p
ly
I
T
2
FL
S.
I
T
2
FL
co
n
tr
o
ll
er
is
u
s
ed
f
o
r
s
p
ee
d
lo
o
p
,
to
r
q
u
e
an
d
f
l
u
x
lo
o
p
s
co
n
tr
o
ller
s
ar
e
o
f
co
n
v
en
tio
n
al
P
I
co
n
tr
o
ller
ty
p
e
[
1
9
]
-
[
2
3
]
.
T
h
e
s
y
s
te
m
is
m
o
d
ele
d
w
ith
M
A
T
L
A
B
SIM
UL
I
NK
u
s
i
n
g
P
MSM
d
at
a
in
ap
p
en
d
ix
(
A
)
,
w
it
h
s
w
itc
h
in
g
ti
m
e
T
s
=0
.
0
0
0
2
s
ec
.
Fig
u
r
e
7
s
h
o
w
s
t
h
e
s
p
ee
d
r
esp
o
n
s
e
at
2
0
0
0
r
p
m
r
ef
er
e
n
ce
s
p
ee
d
,
w
h
ile
Fi
g
u
r
e
8
s
h
o
w
s
t
h
e
lo
ad
to
r
q
u
e
r
esp
o
n
s
e
(
T
L
)
at
lo
ad
s
tep
ch
an
g
e
f
r
o
m
0
.
5
5
NM
to
1
.
1
N.
M
at
1
s
ec
ti
m
e,
F
ig
u
r
e
9
.
s
h
o
w
s
th
e
cu
r
r
en
t
r
esp
o
n
s
e.
Mo
to
r
to
r
q
u
e
an
d
r
ef
er
en
ce
to
r
q
u
e
is
s
h
o
w
n
i
n
F
ig
u
r
e
1
0
.
Fig
u
r
e
6
.
L
ab
o
r
ato
r
y
Set
-
up
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:
2088
-
8
694
I
mp
leme
n
ta
tio
n
o
f Typ
e
-
2
F
u
z
z
y
Lo
g
ic
C
o
n
tr
o
ller
in
P
MS
M
Dri
ve
s
U
s
in
g
DS
P
(
S
.
W
a
h
s
h
)
1103
(
a)
Si
m
u
latio
n
(
b
)
E
x
p
er
im
e
n
tal
Fig
u
r
e
7
.
Sp
ee
d
R
esp
o
n
s
e
(
a)
Si
m
u
latio
n
(
b
)
E
x
p
er
im
e
n
tal
Fig
u
r
e
8
.
T
o
r
q
u
e
R
esp
o
n
s
e
(
a)
Si
m
u
latio
n
(
b
)
E
x
p
er
im
e
n
tal
Fig
u
r
e
9
.
T
h
r
ee
p
h
ase
C
u
r
r
en
t
R
esp
o
n
s
e
7.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
esen
ts
m
o
d
elin
g
,
s
i
m
u
la
tio
n
a
n
d
i
m
p
le
m
en
ta
t
io
n
o
f
a
s
p
ee
d
co
n
tr
o
l
i
n
P
M
SM
d
r
iv
e
b
ased
o
n
DT
C
tec
h
n
iq
u
e.
I
T
2
FL
u
til
ized
as
a
s
p
ee
d
co
n
tr
o
ller
,
s
i
n
ce
i
t
p
r
o
v
id
es
ad
d
itio
n
al
d
eg
r
ee
s
o
f
f
r
ee
d
o
m
a
n
d
h
a
n
d
les
s
y
s
te
m
s
u
n
ce
r
tai
n
tie
s
.
T
h
e
d
r
iv
e
s
y
s
te
m
h
as
b
ee
n
s
i
m
u
lated
an
d
test
ed
u
s
i
n
g
M
A
T
L
A
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[5
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J.M
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D.Z
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H.T
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M
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