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(
20
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(
21
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I
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C
o
ns
i
de
r
i
n
g
̂
=
an
d
̂
=
co
ns
t
an
t
i
n
st
ea
d
y s
t
a
t
e
t
he
a
bo
ve
eq
u
at
i
on
i
s
r
e
d
uc
ed
t
o
̂
w
h
i
c
h
i
m
p
l
i
e
s
t
h
a
t
r
o
t
o
r
f
l
u
x
i
s
d
ir
ec
tl
y
p
r
o
p
o
r
tio
n
al
to
cu
r
r
en
t i
ds
.
3.
CO
NVEN
T
I
O
NA
L
CO
N
T
R
O
L
T
E
CH
NI
Q
U
E
S
3
.
1
.
K
a
l
m
a
n F
ilte
r
M
et
ho
d
T
h
e
k
al
m
a
n
f
ilter
m
et
h
o
d
is
m
o
s
t
p
o
p
u
lar
an
d
co
m
m
o
n
l
y
u
s
ed
to
o
l
f
o
r
s
to
ch
asti
c
es
ti
m
a
tio
n
.
I
t
u
s
es
a
s
et
o
f
m
at
h
e
m
atica
l
eq
u
ati
o
n
s
t
h
at
i
m
p
le
m
e
n
t
a
p
r
ed
icto
r
-
co
r
r
ec
to
r
ty
p
e
e
s
ti
m
ato
r
.
A
s
i
m
p
le
p
r
ed
icto
r
–
co
r
r
ec
to
r
m
et
h
o
d
ca
n
b
e
co
n
s
tr
u
cted
f
r
o
m
t
h
e
E
u
ler
m
et
h
o
d
an
d
th
e
tr
ap
ez
o
id
al
r
u
le
.
Fo
r
th
is
m
e
th
o
d
o
f
co
n
t
r
o
l
,
th
e
i
n
d
u
ct
io
n
m
o
to
r
is
m
o
d
elled
i
n
t
h
e
r
o
to
r
r
ef
er
en
ce
f
r
a
m
e
b
y
u
s
i
n
g
th
e
f
l
u
x
a
n
d
s
p
ee
d
esti
m
ato
r
b
lo
ck
s
.
T
o
g
et
d
if
f
er
en
ce
in
ti
m
e
co
n
s
t
a
n
t
s
f
o
r
cu
r
r
en
t
a
n
d
s
p
ee
d
t
w
o
P
-
I
co
n
tr
o
ller
s
in
a
n
ested
f
as
h
io
n
h
a
s
b
ee
n
u
s
ed
.
T
h
e
b
lo
ck
d
iag
r
a
m
o
f
ab
o
v
e
co
n
t
r
o
ller
ar
e
s
h
o
w
n
in
Fi
g
u
r
e
1
.
T
h
e
v
ar
iab
les
o
f
P
I
co
n
tr
o
ller
co
n
s
id
er
ed
ar
e
lis
ted
in
T
ab
le
1
.
T
ab
le
1
.
Kalm
a
n
f
i
lter
co
n
tr
o
ll
er
p
ar
am
eter
s
P
a
r
a
me
t
e
r
s
F
l
u
x
S
p
e
e
d
T
o
r
q
u
e
K
p
1
5
1
.
2
4
0
.
2
6
1
0
0
K
i
4
3
6
4
0
1
.
9
8
2
9
8
7
7
T
h
e
ac
cu
r
ac
y
o
f
th
i
s
m
et
h
o
d
lies
in
e
x
ac
t
ca
lcu
latio
n
o
f
s
t
ep
s
ize
an
d
n
o
o
f
iter
atio
n
s
c
o
n
s
id
er
ed
.
T
h
e
b
lo
ck
d
iag
r
am
o
f
th
e
ab
o
v
e
co
n
tr
o
ller
is
s
h
o
w
n
i
n
F
i
g
u
r
e
1.
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
a
m
o
f
k
a
l
m
a
n
f
i
lter
co
n
tr
o
ller
.
3
.
2
.
T
un
ing
o
f
co
ntr
o
ller
by
Z
-
N
M
et
ho
d.
A
C
o
n
v
e
n
tio
n
al
P
I
C
o
n
tr
o
ller
ca
n
b
e
o
b
tain
ed
f
r
o
m
t
h
e
b
asi
c
la
w
g
o
v
er
n
ed
b
y
th
e
e
x
p
r
ess
io
n
g
i
v
e
n
in
E
q
u
atio
n
(
2
3
)
.
T
=
K
p
+
⨛
K
i
d
t
(
2
3
)
T
h
e
to
r
q
u
e
ca
n
b
e
v
ar
ied
b
y
v
ar
y
in
g
t
h
e
co
n
tr
o
ller
v
ar
iab
les
(
K
p
an
d
K
i
)
.
w
h
ich
ar
e
to
b
e
s
elec
ted
b
y
f
r
a
m
i
n
g
a
s
et
o
f
r
u
les
ca
lled
t
u
n
i
n
g
p
r
o
ce
s
s
.
.
T
h
e
co
m
m
o
n
l
y
ad
o
p
ted
m
e
th
o
d
is
th
e
Z
ieg
ler
-
Nich
o
ls
w
h
er
e
p
la
n
t
r
esp
o
n
s
e
d
ec
id
es th
e
co
n
tr
o
l p
ar
a
m
eter
s
.
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
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2
,
J
u
n
e
2
0
1
7
:
712
–
7
2
1
716
Fig
u
r
e
2
.
B
lo
ck
d
iag
r
a
m
o
f
s
e
n
s
o
r
less
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n
tr
o
l o
f
in
d
u
ctio
n
m
o
to
r
b
y
P
I
co
n
tr
o
ller
T
h
e
m
o
d
eli
n
g
o
f
i
n
d
u
ctio
n
m
o
to
r
b
y
P
-
I
co
n
tr
o
l
is
g
i
v
en
i
n
Fi
g
u
r
e
2
.
T
h
e
tr
an
s
f
er
f
u
n
c
tio
n
co
n
s
id
er
ed
f
o
r
m
o
d
eli
n
g
is
as
g
i
v
en
i
n
E
q
u
ati
o
n
(
2
4
)
.
T
h
e
T
h
is
m
o
d
elin
g
em
p
lo
y
s
m
ac
h
in
e
p
ar
a
m
e
ter
s
an
d
in
itia
l
v
al
u
es
f
o
r
co
n
tr
o
ller
in
clo
s
ed
lo
o
p
o
p
e
r
a
tio
n
ca
n
b
e
o
b
tain
ed
b
y
co
n
s
id
er
in
g
lo
ad
to
r
q
u
e
as z
er
o
.
(
)
(
)
(
2
4
)
T
h
e
ch
ar
ac
ter
is
tic
eq
u
atio
n
o
f
th
e
ab
o
v
e
tr
an
s
f
er
f
u
n
ctio
n
is
s
h
o
w
n
in
E
q
u
a
tio
n
(
2
5
)
as:
(
)
(
)
S =
0
(
2
5
)
W
h
er
e
=
an
d
(
–
)
.
I
n
th
e
ab
o
v
e
e
x
p
r
ess
io
n
s
g
iv
e
n
i
n
E
q
u
atio
n
(
2
5
)
is
a
co
n
s
ta
n
t
v
alu
e
w
h
ic
h
is
p
o
s
iti
v
e.
B
y
p
o
le
p
lace
m
e
n
t
m
et
h
o
d
th
e
co
n
tr
o
l
v
ar
iab
les
(
K
p
a
n
d
K
i
)
ar
e
o
b
tai
n
ed
an
d
ar
e
s
h
o
w
n
i
n
T
ab
le
2
4.
I
NT
E
L
L
I
G
E
N
T
CO
NT
RO
L
T
E
CH
NI
Q
U
E
S
4
.
1
.
F
uzzy
lo
g
ic
co
ntr
o
ller
W
ith
th
e
r
ap
id
ad
v
an
ce
m
en
t
o
f
p
o
w
er
elec
tr
o
n
ics
an
d
d
ig
i
tal
co
m
p
u
ter
s
m
an
y
i
n
telli
g
e
n
t
co
n
tr
o
l
m
et
h
o
d
s
h
a
v
e
e
m
er
g
ed
w
h
ich
ca
n
g
i
v
e
s
o
lu
tio
n
s
to
o
v
er
co
m
e
d
r
a
w
b
ac
k
s
o
f
ab
o
v
e
m
et
h
o
d
s
.
I
n
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
o
f
f
u
zz
y
co
n
tr
o
l
t
h
e
c
o
n
tr
o
ller
a
d
o
p
ts
on
-
li
n
e
e
f
f
ici
en
c
y
o
p
ti
m
izatio
n
co
n
ce
p
t.B
y
p
r
o
p
er
s
elec
tio
n
o
f
s
tep
s
ize
o
f
ex
citatio
n
cu
r
r
en
t
f
a
s
t
co
n
v
er
g
en
ce
ca
n
b
e
attain
ed
an
d
b
y
a
f
ee
d
f
o
r
w
ar
d
co
m
p
en
s
at
io
n
alg
o
r
ith
m
.
T
h
e
g
e
n
er
atio
n
o
f
lo
w
-
f
r
eq
u
en
c
y
p
u
ls
ati
n
g
to
r
q
u
e
is
r
ed
u
ce
d
.
T
h
is
m
et
h
o
d
e
m
p
lo
y
s
Ma
m
d
a
n
i
m
et
h
o
d
f
o
r
f
u
zz
if
icatio
n
an
d
ce
n
tr
o
id
m
et
h
o
d
f
o
r
d
e
f
u
zz
if
icatio
n
.
Selec
tio
n
o
f
th
e
p
r
o
p
er
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
a
n
d
in
tu
r
n
s
elec
ti
n
g
th
e
r
ig
h
t
r
u
le
b
ase
d
ep
en
d
in
g
o
n
th
e
s
it
u
atio
n
ar
e
th
e
m
aj
o
r
co
n
s
id
er
atio
n
s
f
o
r
th
is
m
e
th
o
d
.
T
h
u
s
,
t
h
e
o
u
tco
m
e
o
f
th
e
co
n
tr
o
ller
is
a
ls
o
r
an
d
o
m
a
n
d
o
p
ti
m
al
r
es
u
lt
s
m
a
y
n
o
t
b
e
o
b
tai
n
ed
w
h
ic
h
is
a
d
r
a
w
b
ac
k
.
4
.
2
.
Art
if
icia
l neura
l net
w
o
r
k
co
ntr
o
ller
A
r
ti
f
ical
n
e
u
r
al
n
et
w
o
r
k
co
n
tr
o
ller
is
b
ased
o
n
i
n
te
g
r
ate
d
m
eth
o
d
o
f
ap
p
r
o
ac
h
.
I
t
u
s
es
b
ac
k
-
p
r
o
p
ag
atio
n
alg
o
r
ith
m
w
h
er
e
s
elec
tio
n
o
f
th
e
p
r
o
p
er
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
an
d
in
t
u
r
n
s
ele
ctin
g
th
e
r
ig
h
t
r
u
l
e
b
ase
d
ep
en
d
in
g
o
n
t
h
e
s
it
u
ati
o
n
is
e
n
s
u
r
ed
.
I
t
in
v
o
lv
es
4
m
aj
o
r
s
tep
s
ie
s
elec
tio
n
o
f
i
n
p
u
ts
(
i
1
,
i
2
…
i
n
)
an
d
w
eig
h
ted
s
u
m
(
w
1
,
w
2
…
w
n
),
co
m
p
ar
i
s
io
n
o
f
p
r
o
d
u
ct
o
f
in
p
u
ts
a
n
d
w
ei
g
h
ted
s
u
m
w
it
h
at
h
r
es
h
h
o
ld
v
alu
e,
s
ca
lin
g
an
d
ad
d
itio
n
o
f
o
f
f
s
et.
T
h
e
ac
cu
r
ac
y
o
f
th
is
m
e
th
o
d
lies
in
s
elec
t
io
n
o
f
r
ig
h
t
s
tr
u
ctu
r
e
f
o
r
n
eu
r
al
n
et
w
o
r
k
w
h
ic
h
is
a
co
m
p
le
x
p
r
o
b
le
m
.
Fig
u
r
e
5
s
h
o
w
s
th
e
b
lo
ck
d
iag
r
a
m
o
f
ar
ti
f
i
cial
n
e
u
r
al
n
et
w
o
r
k
co
n
tr
o
ller
(
A
NN)
.
4
.
3
.
G
enet
ic
a
lg
o
rit
h
m
co
ntr
o
ller
Gen
etic
al
g
o
r
ith
m
h
a
s
e
m
er
g
ed
as
a
p
o
w
er
f
u
l
o
p
ti
m
izatio
n
to
o
l
b
y
w
h
ich
m
i
n
i
m
al
o
r
m
ax
i
m
u
m
v
alu
e
o
f
a
n
y
f
u
n
ctio
n
ca
n
b
e
e
asil
y
attai
n
ed
.
I
n
th
is
m
et
h
o
d
GA
is
e
m
p
lo
y
ed
to
g
iv
e
o
p
ti
m
al
v
alu
e
s
o
f
K
p
an
d
K
i
f
o
r
tu
n
i
n
g
o
f
co
n
tr
o
ller
f
r
o
m
w
h
ic
h
ac
c
u
r
ate
p
o
s
itio
n
o
f
r
o
to
r
ca
n
b
e
o
b
tain
ed
to
g
et
d
esire
d
to
r
q
u
e
an
d
f
l
u
x
co
m
p
o
n
e
n
t
s
o
f
cu
r
r
en
t
.
Her
e
th
e
f
ir
s
t
s
tep
in
v
o
lv
e
s
in
in
itial
izatio
n
o
f
K
p
&
Ki
v
alu
e
s
b
y
Z
-
N
m
et
h
o
d
.
Fo
r
th
e
g
en
er
ated
p
o
p
u
latio
n
t
h
e
er
r
o
r
f
u
n
ctio
n
s
ar
e
ar
r
an
g
ed
i
n
d
ec
r
ea
s
i
n
g
o
r
d
er
o
f
t
h
eir
v
a
lu
e.
B
y
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5
.
1
.
Co
m
pa
ri
s
io
n o
f
Va
rio
us
Sens
o
rles
s
Co
ntr
o
l M
et
ho
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Fro
m
th
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ab
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w
a
v
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f
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l
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co
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n
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m
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ical
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al
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f
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m
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.
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Fro
m
t
h
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m
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s
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s
f
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s
p
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d
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to
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co
m
p
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en
t
s
f
o
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s
e
n
s
o
r
le
s
s
v
ec
to
r
co
n
tr
o
l
o
f
in
d
u
ctio
n
m
o
to
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it
ca
n
b
e
co
n
clu
d
ed
th
at
t
h
e
p
ea
k
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v
er
s
h
o
o
t
an
d
p
ea
k
ti
m
e
o
f
th
e
p
r
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p
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s
ed
Gen
etic
alg
o
r
ith
m
m
et
h
o
d
ar
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lea
s
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co
m
p
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ed
to
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it c
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m
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m
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d
o
f
all
m
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n
s
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ed
.
6.
CO
NCLU
SI
O
N
Fo
r
th
e
p
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r
p
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s
e
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f
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h
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d
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m
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is
m
o
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in
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ce
f
r
a
m
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an
d
th
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r
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to
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p
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s
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(
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u
s
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v
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s
co
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tr
o
ller
s
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s
f
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d
.
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h
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ar
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m
eter
s
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lo
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n
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m
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k
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p
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k
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m
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ar
e
o
b
tain
ed
.
C
o
n
v
en
tio
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m
et
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ller
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icial
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ti
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o
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ith
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s
.
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h
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ti
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tech
n
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e
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s
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co
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n
ce
is
ac
h
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elec
ti
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ad
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ize
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th
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ci
tatio
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u
r
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en
t.
ANN
C
o
n
tr
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ac
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p
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ag
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ith
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ased
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ated
m
et
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o
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o
f
ap
p
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n
s
id
e
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ed
.
I
n
th
e
ar
ti
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icial
in
te
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g
en
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m
et
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o
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s
d
is
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u
s
s
ed
th
e
ac
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ac
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s
in
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elec
tio
n
o
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ig
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r
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le
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ase
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f
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n
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ller
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r
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N
N
w
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ic
h
is
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co
m
p
le
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r
o
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t
h
e
last
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g
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o
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ith
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ap
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s
ed
f
o
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o
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k
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v
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o
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n
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n
g
o
f
P
I
co
n
tr
o
ller
.
Fro
m
t
h
e
ab
o
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e
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al
y
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s
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n
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e
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n
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at
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m
p
ar
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e
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o
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ar
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lli
g
en
ce
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et
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o
d
s
ar
e
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etter
o
p
tio
n
s
f
o
r
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p
tim
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l c
o
n
tr
o
l a
n
d
th
e
g
en
e
ti
c
alg
o
r
ith
m
ap
p
r
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ac
h
is
th
e
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e
s
t
m
et
h
o
d
o
f
all
th
e
ab
o
v
e
d
is
c
u
s
s
ed
m
et
h
o
d
s
.
RE
F
E
R
E
NC
E
S
[1
]
G
il
b
e
rt
S
y
b
il
le,
Ho
a
n
g
L
e
-
Hu
y
,
“
Dig
it
a
l
S
im
u
latio
n
o
f
P
o
w
e
r
S
y
st
e
m
s an
d
P
o
w
e
r
El
e
c
tro
n
ics
u
sin
g
th
e
M
A
TL
A
B
/
S
im
u
li
n
k
P
o
w
e
r
S
y
ste
m
Blo
c
k
s
e
t,
”
IEE
E
P
o
we
r
En
g
in
e
e
rin
g
S
o
c
i
e
ty
-
W
in
ter
M
e
e
ti
n
g
,
S
p
e
c
ia
l
T
e
c
h
n
ica
l
S
e
ss
io
n
,
2
0
0
0
,
p
p
.
2
9
7
3
-
2
9
8
2
.
[2
]
A
d
rian
Du
m
it
re
sc
u
,
De
n
e
s
F
o
d
o
r,
T
a
p
a
n
i
Jo
k
in
e
n
,
M
a
riu
s
Ro
su
,
S
o
ri
n
.
“
M
o
d
e
li
n
g
A
n
d
S
im
u
lati
o
n
Of
El
e
c
tri
c
Driv
e
S
y
ste
m
s
U
sin
g
M
a
tl
a
b
/
S
i
m
u
li
n
k
En
v
iro
n
m
e
n
ts,
”
IEE
E
I
n
t
.
Co
n
f.
o
n
El
e
c
tric
M
a
c
h
in
e
s
a
n
d
Dr
ive
s
IEM
D
-
9
9
,
M
a
y
1
9
9
9
,
S
e
a
tt
le,
USA
,
p
p
.
4
5
1
-
4
5
3
.
[3
]
P
i
ll
a
y
,
P
.
,
V.
L
e
v
in
,
“
M
a
th
e
m
a
ti
c
a
l
m
o
d
e
ls
f
o
r
in
d
u
c
ti
o
n
m
a
c
h
in
e
s,”
IEE
E
p
a
p
e
r,
1
9
9
5
,
p
p
.
6
0
6
-
6
1
7
.
[4
]
R.
Ra
jen
d
ra
n
,
Dr.
N.
De
v
a
ra
jan
“
A
Co
m
p
a
ra
ti
v
e
P
e
rf
o
r
m
a
n
c
e
A
n
a
l
y
sis
o
f
T
o
rq
u
e
Co
n
t
ro
l
S
c
h
e
m
e
s
f
o
r
In
d
u
c
ti
o
n
M
o
to
r
Driv
e
s”
In
ter
n
a
t
io
n
a
l
J
o
u
r
n
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
i
v
e
S
y
ste
m
(
IJ
PE
DS
)
V
o
l.
2
,
No
.
2
,
Ju
n
e
2
0
1
2
,
p
p
.
1
7
7
~
1
9
1
IS
S
N:
2
0
8
8
-
8
6
9
4
.
[5
]
Ka
n
u
n
g
o
Ba
ra
d
a
m
o
h
a
n
ty
a
n
d
Am
it
p
a
tra,
“
F
lu
x
a
n
d
sp
e
e
d
e
stim
a
ti
o
n
i
n
d
e
c
o
u
p
le
d
in
d
u
c
ti
o
n
m
o
to
r
d
riv
e
u
sin
g
Ka
l
m
a
n
F
il
ter”
.
Pro
c
c
.
o
f
2
9
th
Na
t
io
n
a
l
sy
ste
ms
c
o
n
fer
e
n
c
e
(
NS
C),
IIT
M
u
mb
a
i,
De
c
2
0
0
5
,
pp
-
1
-
9
.
[6
]
R.
G
u
n
a
b
a
ian
,
V
.
S
u
b
b
iah
“
S
p
e
e
d
S
e
n
so
rles
s
V
e
c
to
r
Co
n
tro
l
o
f
In
d
u
c
ti
o
n
M
o
to
r
Driv
e
w
it
h
P
I
a
n
d
F
u
z
z
y
Co
n
tr
o
ll
e
r”
,
IJ
PE
DS
Vo
l.
N
o
5
,
No
.
3
.
F
e
b
r
u
a
ry
2015
,
p
p
.
3
1
5
-
3
2
5
.
[7
]
Ha
ss
a
n
Ba
g
h
g
a
r
Bo
sta
n
A
b
a
d
,
A
li
Y
a
z
d
ian
V
a
rjan
i,
T
a
h
e
ri
As
g
h
a
r,
“
Us
in
g
F
u
z
z
y
Co
n
tro
ll
e
r
i
n
IM
S
p
e
e
d
Co
n
tr
o
l
w
it
h
c
o
n
sta
n
t
F
l
u
x
,
”
T
ra
n
s.
o
n
En
g
g
.
,
Co
m
p
u
ti
n
g
a
n
d
T
e
c
h
.
IS
S
N
1
3
0
5
-
5
3
1
3
,
Vo
l.
5
,
A
p
r.
2
0
0
5
,
p
p
.
307
-
3
1
0
.
[8
]
Ku
n
g
,
Y.S
.
,
C.
M
.
L
ia
w
,
M
.
S
.
Ou
y
a
n
g
,
“
A
d
a
p
ti
v
e
S
p
e
e
d
Co
n
tr
o
l
f
o
r
IM
Driv
e
s
Us
in
g
Ne
u
ra
l
Ne
two
rk
s,”
IEE
E
T
ra
n
s.
O
n
In
d
.
El
e
c
tro
n
ics
,
Vo
l.
4
2
,
N
o
.
1
,
F
e
b
.
1
9
9
5
,
p
p
.
2
5
-
3
2
.
[9
]
S
h
a
rm
a
,
A
.
K.,
R.
A
.
G
u
p
ta,
L
a
x
m
i
S
riv
a
st
a
v
a
,
“
P
e
rf
o
r
m
a
n
c
e
o
f
A
N
N
b
a
se
d
in
d
irec
t
v
e
c
to
r
c
o
n
tr
o
l
o
f
IM
d
riv
e
,
”
J
o
u
rn
a
l
o
f
T
h
e
o
re
ti
c
a
l
a
n
d
A
p
p
l
ied
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
,
Vo
l.
3
,
No
.
3
,
2
0
0
7
,
p
p
.
5
0
-
5
7
.
[1
0
]
M
‟h
a
m
e
d
Ch
e
b
re
1
,
A
b
d
e
lk
a
d
e
r
M
e
ro
u
f
e
l2
,
Ye
ss
e
m
a
Be
n
d
a
h
a
1
“
S
p
e
e
d
Co
n
tr
o
l
o
f
In
d
u
c
ti
o
n
M
o
t
o
r
Us
in
g
G
e
n
e
ti
c
A
l
g
o
rit
h
m
-
b
a
se
d
P
I
Co
n
tro
l
ler”
,
Acta
Po
lyte
c
h
n
ica
Hu
n
g
a
ric
a
,
V
o
l.
8
,
No
.
6
,
2
0
1
1
.
[1
1
]
A
ru
n
ima
DEY
1)
,
B
h
im
S
ING
H
2)
a
n
d
Bh
a
rti
DW
IV
EDI
1)
“
V
e
c
to
r
c
o
n
tr
o
ll
e
d
I
n
d
u
c
ti
o
n
M
o
t
o
r
d
r
iv
e
Us
in
g
G
e
n
e
ti
c
A
l
g
o
rit
h
m
T
u
n
e
d
P
I
S
p
e
e
d
Co
n
tr
o
ll
e
r.
”
El
e
c
trica
l
P
o
we
r Qu
a
li
ty a
n
d
Uti
li
sa
ti
o
n
J
o
u
r
n
a
l
Vo
l.
XV
,
No
1
,
2
0
0
9
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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