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R
M
s)
a
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a
in
in
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ll
e
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iza
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ims
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o
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a
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iza
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imiz
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sh
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ri
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ters
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ra
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g
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o
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it
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imu
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re
su
lt
s
d
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m
o
n
stra
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ig
n
ifi
c
a
n
t
imp
ro
v
e
m
e
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ts:
to
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ri
p
p
le
is
r
e
d
u
c
e
d
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o
m
a
ra
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f
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ti
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imilarly
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strial
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a
u
t
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m
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v
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c
to
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K
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w
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r
d
s
:
An
t c
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p
tim
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Mo
to
r
d
r
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p
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Switch
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elu
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o
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ip
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h
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s
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c
c
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ss
a
rticle
u
n
d
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r th
e
CC B
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SA
li
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d
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1.
I
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UCT
I
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Du
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to
t
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s
u
p
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u
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p
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ch
allen
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v
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r
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m
en
ts
,
s
witch
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r
elu
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m
o
to
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s
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SR
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h
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etitiv
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f
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m
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s
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o
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er
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t
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a
n
tag
es,
wh
ich
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clu
d
e
f
au
lt
to
ler
an
ce
an
d
h
ig
h
to
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q
u
e
d
en
s
ity
.
On
th
e
o
th
er
h
an
d
,
th
eir
to
r
q
u
e
g
en
er
atio
n
is
n
o
n
-
lin
ea
r
,
w
h
ich
m
ak
es
it
d
if
f
icu
lt
to
p
r
o
v
id
e
ef
f
ec
tiv
e
an
d
s
ea
m
less
co
n
tr
o
l
ac
r
o
s
s
a
wid
e
r
an
g
e
o
f
s
p
ee
d
s
.
T
o
r
q
u
e
r
ip
p
le
is
a
co
m
m
o
n
p
r
o
b
lem
i
n
SR
Ms
t
h
at
r
eq
u
ir
es
m
o
d
e
r
n
m
an
a
g
e
m
en
t
tech
n
iq
u
es
f
o
r
ef
f
icien
t
m
itig
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n
s
in
ce
it
c
an
r
esu
lt
in
m
ec
h
a
n
ical
s
tr
ess
,
v
ib
r
atio
n
,
an
d
au
d
it
o
r
y
n
o
is
e.
T
h
er
e
h
av
e
b
ee
n
s
ev
er
al
m
an
ag
e
m
en
t
s
o
l
u
tio
n
s
p
r
o
p
o
s
ed
to
d
ec
r
ea
s
e
th
e
t
o
r
q
u
e
r
ip
p
le
in
SR
Ms.
E
v
en
th
o
u
g
h
th
e
t
o
r
q
u
e
s
h
ar
in
g
f
u
n
ctio
n
s
(
T
SF
s
)
is
f
r
eq
u
en
tl
y
o
n
ly
ap
p
lied
at
lo
w
to
m
ed
iu
m
s
p
ee
d
s
,
it
is
o
n
e
o
f
th
e
m
o
s
t
p
o
p
u
lar
an
d
s
u
cc
ess
f
u
l
tech
n
iq
u
es
f
o
r
lo
wer
in
g
to
r
q
u
e
r
ip
p
le.
T
h
is
s
tu
d
y
p
r
o
p
o
s
es
an
en
h
an
ce
d
T
SF
to
im
p
r
o
v
e
to
r
q
u
e
ch
ar
ac
ter
is
tics
o
f
SR
Ms
o
v
er
a
wid
er
s
p
ee
d
r
an
g
e.
T
h
e
s
u
g
g
ested
m
eth
o
d
also
im
p
r
o
v
es
m
o
to
r
e
f
f
icien
cy
b
y
lo
wer
in
g
th
e
p
h
ase
c
u
r
r
e
n
t'
s
r
o
o
t
m
ea
n
s
q
u
ar
e
(
R
MS
)
v
alu
e
.
T
o
r
q
u
e
r
ip
p
le
r
ed
u
ctio
n
is
a
n
im
p
o
r
tan
t
ar
ea
o
f
r
esear
ch
f
o
r
SR
Ms
b
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au
s
e
o
f
its
ef
f
ec
ts
o
n
th
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p
er
f
o
r
m
a
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ce
o
f
m
o
t
o
r
s
,
ef
f
icien
c
y
,
a
n
d
r
eliab
ilit
y
.
Ma
n
y
tech
n
iq
u
es h
av
e
b
ee
n
p
u
t f
o
r
th
to
en
h
a
n
ce
T
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with
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n
iq
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e
ap
p
r
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d
r
awb
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
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8
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4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
3
,
Sep
tem
b
er
20
25
:
1537
-
1
5
5
1
1538
A
g
en
etic
alg
o
r
ith
m
-
b
ased
te
ch
n
iq
u
e
f
o
r
alter
in
g
co
m
m
u
tatio
n
an
g
les
was
p
r
esen
te
d
in
[
1
]
,
wh
ic
h
d
ec
r
ea
s
ed
to
r
q
u
e
r
ip
p
le
an
d
C
u
lo
s
s
es.
T
h
e
s
tu
d
y
also
r
em
o
v
e
s
n
eg
ativ
e
to
r
q
u
e
ef
f
ec
ts
,
wh
ic
h
lo
wer
th
e
a
v
er
ag
e
to
r
q
u
e.
Nev
e
r
th
eless
,
its
ap
p
licatio
n
in
q
u
ick
l
y
ch
an
g
in
g
s
e
ttin
g
s
m
ay
b
e
lim
ited
d
u
e
t
o
its
r
elian
ce
o
n
GA
p
ar
am
eter
s
f
o
r
co
n
v
er
g
e
n
ce
.
A
n
ew
T
SF
tech
n
iq
u
e
i
n
[
2
]
i
m
p
r
o
v
es
p
er
f
o
r
m
an
ce
at
h
ig
h
s
p
ee
d
s
b
y
r
e
d
ef
in
in
g
T
SF
p
ar
am
eter
s
to
in
co
r
p
o
r
at
e
n
eg
at
iv
e
to
r
q
u
e
z
o
n
es.
T
h
e
to
r
q
u
e
-
s
p
ee
d
ch
ar
ac
ter
is
tics
an
d
cu
r
r
en
t
d
y
n
am
ics
ar
e
s
u
cc
ess
f
u
lly
en
h
an
ce
d
b
y
th
e
tech
n
iq
u
e.
T
r
ad
itio
n
al
T
SF
s
f
o
r
SR
M
s
ar
e
d
esig
n
ed
to
r
ed
u
ce
to
r
q
u
e
r
i
p
p
le
b
y
s
h
ap
in
g
th
e
p
h
ase
cu
r
r
en
t
p
r
o
f
ile.
Ho
wev
er
,
c
o
n
v
e
n
tio
n
al
ap
p
r
o
ac
h
es
s
u
ch
as
lin
ea
r
,
s
in
u
s
o
id
al,
an
d
ex
p
o
n
e
n
tial
T
SF
s
d
o
n
o
t
ac
co
u
n
t
f
o
r
r
ea
l
-
tim
e
cu
r
r
en
t
d
y
n
am
ics
an
d
in
d
u
ce
d
elec
tr
o
m
o
ti
v
e
f
o
r
ce
(
E
M
F),
lim
itin
g
th
eir
ef
f
ec
tiv
en
ess
in
ac
h
iev
in
g
p
r
ec
is
e
to
r
q
u
e
co
n
tr
o
l
[
3
]
.
T
o
en
h
a
n
ce
SR
M
p
er
f
o
r
m
an
ce
,
an
o
n
lin
e
T
SF
m
eth
o
d
was
in
tr
o
d
u
ce
d
in
[
4
]
,
wh
ich
d
y
n
am
ically
ad
ju
s
ts
th
e
c
u
r
r
e
n
t
r
ef
e
r
en
ce
b
ased
o
n
r
ea
l
-
tim
e
m
ea
s
u
r
em
en
ts
.
T
h
e
cu
r
r
e
n
t
r
ef
er
en
ce
is
u
p
d
ate
d
u
s
in
g
th
e
f
a
d
in
g
p
h
ase
c
u
r
r
en
t
f
o
llo
win
g
t
h
e
tu
r
n
-
o
f
f
an
g
le
.
T
h
e
m
eth
o
d
e
n
s
u
r
es
ac
cu
r
ate
to
r
q
u
e
p
r
o
d
u
ctio
n
wh
ile
m
in
im
izin
g
co
p
p
e
r
lo
s
s
es.
Sev
er
al
m
eth
o
d
s
h
av
e
b
ee
n
ex
p
lo
r
e
d
in
[
5
]
to
r
ed
u
ce
co
p
p
er
lo
s
s
an
d
to
r
q
u
e
r
ip
p
le
in
m
o
to
r
s
with
s
witc
h
in
g
r
elu
ctan
ce
,
p
ar
ticu
lar
ly
d
u
r
in
g
co
m
m
u
tatio
n
.
Pre
d
i
ctiv
e
to
r
q
u
e
co
n
tr
o
l
tec
h
n
iq
u
es
h
a
v
e
b
ee
n
wid
ely
s
tu
d
ied
f
o
r
o
p
tim
izin
g
p
h
ase
to
r
q
u
e
tr
a
n
s
itio
n
s
an
d
im
p
r
o
v
in
g
m
o
to
r
ef
f
icien
c
y
.
Prio
r
r
esear
ch
h
as
f
o
cu
s
ed
o
n
r
ef
in
in
g
co
s
t
f
u
n
ctio
n
s
an
d
we
ig
h
t
p
a
r
am
eter
s
to
en
h
a
n
ce
c
o
n
tr
o
l
p
er
f
o
r
m
an
ce
.
Ho
wev
er
,
ex
is
tin
g
m
eth
o
d
s
s
ti
ll f
ac
e
ch
alle
n
g
es in
ac
h
iev
in
g
a
b
alan
ce
b
etwe
en
to
r
q
u
e
r
ip
p
le
s
u
p
p
r
ess
io
n
an
d
co
p
p
er
lo
s
s
r
ed
u
ctio
n
.
Alth
o
u
g
h
th
is
m
eth
o
d
s
ig
n
if
ica
n
tly
r
ed
u
ce
s
to
r
q
u
e
r
ip
p
le
an
d
im
p
r
o
v
es
o
p
er
atin
g
ef
f
icien
cy
,
it m
a
y
b
e
less
f
lex
i
b
le
in
d
y
n
am
ic
s
itu
atio
n
s
d
u
e
t
o
its
r
elian
ce
o
n
s
tatic
ass
ess
m
en
t in
d
ices.
L
i
et
a
l.
[
6
]
p
r
esen
ted
an
o
f
f
lin
e
T
SF
m
eth
o
d
th
at
m
ak
es
u
s
e
o
f
T
SF
-
b
ased
s
tatic
f
l
u
x
lin
k
ag
e
p
r
o
p
er
ties
,
s
h
o
win
g
litt
le
co
p
p
er
lo
s
s
an
d
a
b
r
o
a
d
s
p
ee
d
r
a
n
g
e.
E
v
en
it
wo
r
k
s
well
in
s
im
u
latio
n
s
,
its
o
f
f
lin
e
n
atu
r
e
m
ak
es
it
less
f
lex
ib
le
wh
en
o
p
er
atin
g
cir
c
u
m
s
tan
ce
s
ch
an
g
e
in
r
ea
l
life
.
Ye
et
a
l.
[
7
]
p
r
esen
ted
a
n
ew
ex
ten
d
ed
-
s
p
ee
d
,
lo
w
-
r
ip
p
le
to
r
q
u
e
co
n
t
r
o
l
m
eth
o
d
f
o
r
SR
M
d
r
iv
es
was
p
r
o
p
o
s
ed
with
an
o
n
lin
e
T
SF
.
T
h
e
ab
s
o
lu
te
v
alu
es
o
f
th
e
f
lu
x
lin
k
ag
e
r
ate
ch
an
g
e
b
etwe
en
th
e
ar
r
iv
in
g
an
d
leav
in
g
p
h
ases
d
eter
m
in
e
th
e
two
o
p
er
atio
n
al
m
o
d
es.
A
p
r
o
p
o
r
ti
o
n
al
in
teg
r
al
(
PI)
co
m
p
en
s
ato
r
is
ad
d
ed
t
o
th
e
to
r
q
u
e
r
ef
er
e
n
ce
to
ac
co
u
n
t
f
o
r
to
r
q
u
e
er
r
o
r
s
ca
u
s
ed
b
y
i
n
s
u
f
f
i
cien
t c
u
r
r
en
t m
o
n
ito
r
in
g
.
Un
lik
e
tr
ad
itio
n
al
T
SF
s
,
o
u
r
ap
p
r
o
ac
h
g
u
ar
a
n
tees th
at
th
e
p
h
ase
with
th
e
lo
west
ab
s
o
lu
te
r
ate
o
f
ch
a
n
g
e
o
f
f
lu
x
li
n
k
ag
e
(
AR
C
FL
)
d
eter
m
in
es
th
e
to
tal
to
r
q
u
e.
T
h
e
s
y
s
tem
'
s
s
u
p
er
io
r
ity
o
v
e
r
tr
ad
itio
n
al
T
SF
s
i
s
co
n
f
ir
m
ed
b
y
s
im
u
latio
n
s
test
in
g
u
s
in
g
a
2
.
3
k
W
,
6
0
0
0
r
p
m
,
3
-
p
h
ase
1
2
/8
SR
M.
T
h
is
m
eth
o
d
s
ig
n
if
ican
tly
r
ed
u
ce
s
r
i
p
p
le
s
in
to
r
q
u
e
a
n
d
a
d
v
an
ce
s
m
a
x
im
u
m
to
r
q
u
e
-
r
i
p
p
le
-
f
r
ee
s
p
ee
d
b
y
m
o
r
e
th
an
1
0
tim
es.
T
h
e
m
eth
o
d
r
elies o
n
p
r
e
cise c
o
n
tr
o
l o
f
AR
C
FL,
wh
ich
m
ay
b
e
ch
allen
g
in
g
to
im
p
lem
en
t
in
r
ea
l
-
tim
e
u
n
d
er
d
y
n
a
m
ic
o
p
er
atin
g
c
o
n
d
it
io
n
s
.
I
n
cr
ea
s
ed
co
m
p
u
tatio
n
a
l
r
eq
u
ir
em
en
ts
f
o
r
im
p
lem
en
tin
g
th
e
PI
co
m
p
en
s
ato
r
in
r
ea
l
-
tim
e
ap
p
licatio
n
s
[
8
]
.
A
d
d
r
ess
es
th
e
m
ajo
r
d
is
ad
v
an
tag
e
o
f
SR
Ms,
h
ig
h
to
r
q
u
e
r
ip
p
les,
&
b
y
e
x
p
lo
r
in
g
an
o
p
tim
ized
to
r
q
u
e
co
n
tr
o
l
s
tr
ateg
y
b
ased
o
n
T
SF
s
.
An
im
p
r
o
v
ed
co
n
v
en
tio
n
al
T
SF
an
d
its
ass
o
ciate
d
o
n
lin
e
T
SF
ar
e
p
r
esen
te
d
to
g
eth
e
r
with
a
ch
an
g
ed
c
u
r
r
en
t
co
n
tr
o
l
m
eth
o
d
.
T
h
is
m
eth
o
d
g
r
ea
tly
en
h
a
n
ce
s
to
r
q
u
e
-
s
p
ee
d
p
e
r
f
o
r
m
an
ce
a
n
d
to
r
q
u
e
r
ip
p
le
r
ed
u
ctio
n
.
T
h
e
o
p
tim
izatio
n
p
r
o
ce
s
s
is
lim
ited
b
y
its
h
ea
v
y
r
elian
ce
o
n
s
y
s
tem
-
s
p
ec
if
ic
f
ac
to
r
s
.
B
o
b
er
an
d
Fer
k
o
v
á
[
9
]
p
r
ese
n
ted
a
T
SF
-
b
ased
co
n
tr
o
l
o
f
SR
Ms
with
th
e
f
ir
in
g
a
n
g
le
m
o
d
u
latio
n
(
FAM)
ap
p
r
o
ac
h
was
p
r
esen
ted
.
An
o
f
f
-
th
e
-
s
h
elf
SR
M
-
s
p
ec
if
ic
o
f
f
lin
e
o
p
tim
izatio
n
p
r
o
ce
s
s
is
p
r
esen
ted
,
em
p
h
asizin
g
in
teg
r
al
s
q
u
ar
e
er
r
o
r
,
to
r
q
u
e
r
ip
p
le,
a
n
d
m
o
to
r
ef
f
icien
cy
.
T
h
e
FAM
ap
p
r
o
ac
h
,
wh
ic
h
u
s
es
a
f
in
ite
elem
en
t
m
o
d
el
(
FEM
)
,
cr
ea
te
s
n
o
ticea
b
ly
m
o
r
e
to
r
q
u
e
r
ip
p
le
b
u
t
is
ju
s
t
as
ef
f
icien
t
as
T
SF
.
Ye
et
a
l.
[
1
0
]
p
r
esen
ted
u
s
in
g
a
T
ik
h
o
n
o
v
f
ac
to
r
,
a
to
r
q
u
e
r
ip
p
le
r
e
d
u
ctio
n
o
f
f
lin
e
T
SF
ac
r
o
s
s
a
b
r
o
ad
r
an
g
e
o
f
s
p
ee
d
s
is
s
u
g
g
ested
to
b
alan
ce
to
r
q
u
e
-
s
p
ee
d
p
er
f
o
r
m
an
ce
with
C
u
l
o
s
s
.
I
ts
m
ax
im
u
m
to
r
q
u
e
-
r
ip
p
le
-
f
r
ee
s
p
ee
d
is
s
ev
en
tim
es
f
aster
th
an
th
at
o
f
c
o
n
v
e
n
tio
n
al
T
SF
s
.
T
h
e
m
eth
o
d
'
s
o
f
f
lin
e
n
atu
r
e
lim
its
its
ca
p
ac
ity
to
ad
ju
s
t
to
ch
a
n
g
es
in
r
ea
l
-
tim
e
o
p
er
atio
n
s
.
Ma
k
w
an
a
et
a
l.
[
1
1
]
p
r
esen
ted
an
ar
t
if
icial
n
eu
r
al
n
etwo
r
k
(
ANN)
-
b
ased
p
r
o
ce
d
u
r
e
f
o
r
SR
Ms.
T
h
e
m
eth
o
d
u
s
es
MA
T
L
AB
Simu
lin
k
to
d
esig
n
an
d
s
im
u
late
th
e
ANN,
ac
h
iev
i
n
g
s
atis
f
ac
to
r
y
r
esu
lts
.
A
n
o
v
el
ap
p
r
o
ac
h
t
o
r
ed
u
ce
th
e
n
u
m
b
er
o
f
n
eu
r
o
n
s
f
o
r
m
ap
p
in
g
m
ag
n
etic
ch
a
r
ac
ter
i
s
tics
i
s
in
tr
o
d
u
ce
d
,
d
ec
r
ea
s
in
g
co
m
p
u
tatio
n
al
c
o
m
p
lex
ity
with
o
u
t
s
ig
n
i
f
ican
tly
af
f
ec
tin
g
p
er
f
o
r
m
an
ce
.
T
h
e
ANN
d
esig
n
r
eq
u
ir
es
ex
ten
s
iv
e
tr
ain
in
g
a
n
d
ac
cu
r
ate
m
ag
n
etic
ch
ar
ac
ter
is
tic
d
ata,
wh
ich
m
ig
h
t
n
o
t
b
e
r
ea
d
ily
av
ailab
le
[
1
2
]
.
I
n
v
esti
g
ated
m
ath
e
m
atica
l
m
o
d
ellin
g
m
eth
o
d
s
f
o
r
SR
Ms,
s
u
ch
as
cr
ea
tin
g
a
MA
T
L
AB
em
b
ed
d
ed
f
u
n
ctio
n
to
m
ap
m
ag
n
etic
n
o
n
lin
ea
r
ity
.
A
s
s
tated
in
[
1
3
]
,
a
h
y
b
r
id
T
SF
tech
n
iq
u
e
ef
f
ec
tiv
ely
ad
d
r
ess
es
th
e
is
s
u
e
o
f
to
r
q
u
e
r
ip
p
le
in
SR
Ms
at
h
ig
h
-
s
p
ee
d
r
e
-
p
r
o
f
ilin
g
t
h
e
in
c
r
ea
s
in
g
p
ar
t
o
f
th
e
en
ter
in
g
p
h
ase
t
o
r
q
u
e
to
tak
e
i
n
to
co
n
s
id
er
atio
n
f
o
r
er
r
o
r
s
in
o
u
tg
o
in
g
p
h
ases
.
Ad
d
itio
n
ally
,
b
y
r
ed
u
cin
g
th
e
d
is
cr
ep
an
cy
b
e
twee
n
th
e
r
eq
u
ested
an
d
ac
tu
al
v
alu
e
o
f
to
r
q
u
e
d
u
r
i
n
g
h
ig
h
-
s
p
ee
d
o
p
er
atio
n
s
,
th
e
o
v
er
lap
a
n
g
le
co
n
tr
o
ller
im
p
r
o
v
es
r
ea
l
-
tim
e
to
r
q
u
e
m
o
n
ito
r
in
g
ca
p
ab
ilit
ies.
Simu
latio
n
r
esu
lts
v
alid
ate
th
at
th
e
h
y
b
r
id
T
SF
ac
h
iev
es
s
ig
n
if
ican
t
to
r
q
u
e
r
ip
p
le
s
u
p
p
r
ess
io
n
co
m
p
a
r
ed
to
co
n
v
en
tio
n
al
T
SF
s
.
Ho
wev
er
,
th
e
m
eth
o
d
’
s
r
elian
ce
o
n
r
ea
l
-
t
im
e
ad
ap
tatio
n
a
n
d
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
co
u
ld
p
o
s
e
ch
a
llen
g
es in
t
h
e
im
p
le
m
en
tatio
n
f
o
r
r
eso
u
r
ce
-
co
n
s
tr
ain
ed
s
y
s
tem
s
.
Qu
r
aa
n
et
a
l.
[
1
4
]
p
r
esen
ted
an
I
T
C
s
tr
ateg
y
u
s
in
g
a
T
SF
to
r
ed
u
ce
r
ip
p
le
in
t
o
r
q
u
e
i
n
SR
Ms,
esp
ec
ially
at
in
ter
m
ed
iate
an
d
h
ig
h
s
p
ee
d
s
.
Du
r
in
g
th
e
d
em
ag
n
etizin
g
p
er
io
d
,
th
e
s
u
g
g
ested
m
eth
o
d
p
r
ed
icts
th
e
o
u
tg
o
in
g
p
h
ase
to
r
q
u
e
an
d
m
o
d
if
ies
t
h
e
in
co
m
in
g
p
h
ase
to
r
q
u
e
a
p
p
r
o
p
r
iately
to
co
m
p
en
s
ate
f
o
r
to
r
q
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e
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ac
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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8
6
9
4
To
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tr
ates
a
to
r
q
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r
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o
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s
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A
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itatio
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ea
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ity
ass
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ciate
d
with
p
r
ed
ictiv
e
c
o
n
tr
o
l
alg
o
r
ith
m
s
,
w
h
ich
m
ig
h
t
im
p
ac
t
r
ea
l
-
tim
e
o
p
er
atio
n
[
1
5
]
.
F
o
cu
s
es
o
n
e
n
h
an
cin
g
th
e
T
SF
m
eth
o
d
f
o
r
SR
Ms
to
ac
h
iev
e
h
ig
h
er
o
p
er
atin
g
s
p
ee
d
s
b
y
m
in
im
izin
g
th
e
f
lu
x
lin
k
a
g
e
ch
an
g
e
r
ate
u
s
in
g
g
en
etic
al
g
o
r
ith
m
(
GA)
o
p
tim
izatio
n
.
B
y
r
ef
in
in
g
k
n
o
w
n
p
ar
am
eter
s
an
d
in
tr
o
d
u
cin
g
a
n
ew
o
p
tim
izatio
n
o
b
jectiv
e,
t
h
e
s
tu
d
y
d
em
o
n
s
tr
ates sig
n
if
ican
t im
p
r
o
v
e
m
en
ts
in
s
p
ee
d
p
er
f
o
r
m
an
ce
.
Simu
lati
o
n
o
u
tc
o
m
es
au
th
en
ticate
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
ap
p
r
o
ac
h
.
Ho
wev
er
,
th
is
r
esear
ch
p
r
im
a
r
ily
em
p
h
asizes
s
p
ee
d
im
p
r
o
v
em
en
ts
,
with
lim
ited
atten
tio
n
t
o
th
e
p
o
ten
tia
l
im
p
ac
t
o
n
to
r
q
u
e
r
ip
p
le
o
r
ef
f
icien
cy
,
m
ak
in
g
th
e
an
aly
s
is
less
co
m
p
r
eh
en
s
iv
e.
An
o
p
tim
izatio
n
a
p
p
r
o
ac
h
is
d
escr
ib
ed
in
[
1
6
]
to
i
d
en
tify
t
h
e
id
ea
l
p
ar
am
eter
s
f
o
r
s
in
u
s
o
i
d
al
T
SF
in
SR
Ms,
with
an
em
p
h
asis
o
n
s
tar
t
an
d
o
v
er
lap
an
g
les
at
d
if
f
er
en
t
o
p
e
r
atio
n
al
p
o
in
ts
.
Sev
e
r
al
g
o
al
f
u
n
ctio
n
s
,
in
clu
d
in
g
ef
f
icien
c
y
a
n
d
t
o
r
q
u
e
r
ip
p
le,
a
r
e
tak
e
n
in
t
o
ac
c
o
u
n
t
d
u
r
in
g
t
h
e
o
p
tim
izatio
n
p
r
o
c
ess
,
wh
ich
is
co
n
d
u
cte
d
th
r
o
u
g
h
s
im
u
latio
n
s
u
tili
zin
g
th
e
f
in
ite
elem
en
t
ap
p
r
o
ac
h
.
T
h
e
ap
p
r
o
ac
h
o
f
f
er
s
f
lex
ib
ilit
y
an
d
d
iv
er
s
ity
b
y
g
e
n
er
atin
g
a
s
et
o
f
f
u
n
ctio
n
s
t
h
at
ar
e
tailo
r
ed
f
o
r
ea
c
h
o
p
er
atin
g
p
o
in
t.
Ho
wev
e
r
,
th
e
f
in
d
in
g
s
'
g
en
er
aliza
b
ilit
y
to
o
th
er
SR
M
d
esig
n
s
o
r
o
p
e
r
atio
n
al
s
ettin
g
s
wo
u
ld
b
e
lim
ited
b
y
th
e
s
tu
d
y
'
s
d
ep
en
d
en
ce
o
n
th
e
ac
cu
r
ac
y
o
f
f
in
ite
ele
m
en
t m
o
d
els.
A
u
n
iq
u
e
T
SF
ap
p
r
o
a
ch
th
at
d
iv
id
es
th
e
c
o
m
m
u
tati
o
n
p
r
o
ce
s
s
in
to
two
p
h
ases
is
p
r
esen
ted
in
[
1
7
]
to
im
p
r
o
v
e
to
r
q
u
e
tr
ac
k
in
g
p
e
r
f
o
r
m
a
n
ce
in
SR
Ms.
T
h
e
ad
a
p
tiv
e
co
m
m
u
tatio
n
ap
p
r
o
ac
h
g
u
ar
an
tees
b
etter
p
e
r
f
o
r
m
a
n
ce
at
v
ar
io
u
s
s
p
ee
d
s
b
y
co
m
p
u
tin
g
p
a
r
titi
o
n
a
n
g
le
s
[
1
8
]
.
P
r
o
v
i
d
es
an
im
p
r
o
v
e
d
T
SF
with
lin
ea
r
ac
tiv
e
d
is
tu
r
b
an
ce
r
ejec
tio
n
co
n
tr
o
l
(
L
ADRC
)
an
d
th
e
m
o
d
if
ied
co
y
o
te
o
p
tim
izatio
n
alg
o
r
ith
m
(
MCOA)
to
im
p
r
o
v
e
to
r
q
u
e
co
n
t
r
o
l
in
SR
Ms.
W
h
ile
MCO
A
ad
ju
s
ts
cr
u
cial
f
ac
t
o
r
s
,
in
clu
d
in
g
tu
r
n
-
o
n
an
d
co
n
d
u
ctio
n
an
g
les,
L
ADR
C
en
h
an
ce
s
an
ti
-
d
is
tu
r
b
an
ce
p
er
f
o
r
m
an
ce
,
an
d
th
e
p
ie
ce
wis
e
T
S
F
r
ed
u
ce
s
to
r
q
u
e
r
ip
p
le.
C
o
m
p
a
r
is
o
n
s
b
e
twee
n
s
im
u
latio
n
a
n
d
ex
p
e
r
im
en
t
s
h
o
w
t
h
at
th
e
s
ch
em
e
wo
r
k
s
h
ea
lth
ier
in
ter
m
s
o
f
d
is
tu
r
b
a
n
ce
r
ejec
tio
n
a
n
d
r
i
p
p
le
d
ec
r
ea
s
e
th
an
t
r
ad
itio
n
al
T
SF
tech
n
iq
u
es.
Ho
wev
er
,
th
e
u
s
e
o
f
s
o
p
h
is
ticated
o
p
tim
izatio
n
a
n
d
co
n
tr
o
l
s
ch
e
m
es
ad
d
s
co
m
p
lex
ity
to
t
h
e
s
y
s
tem
,
wh
ich
m
ay
m
ak
e
p
r
ac
t
ical
im
p
lem
en
tatio
n
m
o
r
e
d
if
f
icu
lt.
Do
wlatsh
ah
i
e
t
a
l
.
[
1
9
]
p
r
esen
ted
th
at
to
r
q
u
e
r
ip
p
le
co
m
p
en
s
atio
n
i
n
SR
Ms
is
ac
h
iev
ed
b
y
ad
ap
tin
g
s
tan
d
ar
d
T
SF
s
to
ac
c
o
u
n
t
f
o
r
th
e
n
o
n
lin
ea
r
m
ag
n
eti
c
p
r
o
p
er
ties
an
d
to
r
q
u
e
p
u
ls
atio
n
m
ec
h
an
is
m
.
T
h
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
aim
s
to
e
n
h
an
ce
to
r
q
u
e
c
o
n
tr
o
l.
Fu
r
t
h
e
r
ev
alu
atio
n
is
r
eq
u
i
r
ed
to
d
et
er
m
in
e
its
p
r
ac
tical
im
p
ac
t
with
g
r
ea
te
r
ac
cu
r
ac
y
.
A
T
SF
co
n
tr
o
l
tec
h
n
iq
u
e
f
o
r
S
R
Ms
th
at
m
ax
im
izes
to
r
q
u
e
p
er
s
q
u
ar
e
am
p
er
e
is
u
s
ed
in
[
2
0
]
t
o
im
p
r
o
v
e
m
o
to
r
ef
f
icie
n
cy
a
n
d
d
ec
r
ea
s
e
to
r
q
u
e
r
ip
p
le.
B
etter
to
r
q
u
e
t
r
ac
k
in
g
is
ac
h
iev
ed
b
y
t
h
e
m
eth
o
d
b
y
e
m
p
lo
y
i
n
g
a
n
o
n
lin
e
to
r
q
u
e
c
o
r
r
ec
tio
n
m
eth
o
d
o
l
o
g
y
a
n
d
f
o
r
ec
asti
n
g
p
h
ase
to
r
q
u
e
u
s
in
g
r
ea
l
-
tim
e
p
h
ase
cu
r
r
en
ts
.
Sig
n
i
f
ican
t
g
ain
s
in
t
o
r
q
u
e
r
i
p
p
le
r
ed
u
ctio
n
o
v
er
th
e
co
s
in
e
-
t
y
p
e
T
SF
tech
n
iq
u
e
ar
e
s
h
o
wn
b
y
s
im
u
latio
n
an
d
ex
p
er
im
en
tal
d
ata
H
a
m
o
u
d
a
e
t
a
l
.
[
2
1
]
p
r
e
s
e
n
t
e
d
a
n
e
w
a
p
p
r
o
a
c
h
f
o
r
S
R
M
s
t
o
s
a
t
i
s
f
y
e
le
c
t
r
i
c
v
e
h
i
cl
e
(
E
V
)
s
p
ec
i
f
i
c
a
ti
o
n
s
l
i
k
e
g
r
e
a
t
e
r
s
p
e
e
d
r
a
n
g
e
,
l
o
w
to
r
q
u
e
r
i
p
p
l
e
,
a
n
d
g
o
o
d
e
f
f
i
c
i
e
n
c
y
w
a
s
p
r
es
e
n
t
e
d
.
C
o
n
t
r
o
l
p
a
r
am
e
t
e
r
s
a
r
e
a
d
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u
s
t
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u
s
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n
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t
h
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p
a
r
t
ic
l
e
s
w
a
r
m
o
p
t
im
i
z
a
t
i
o
n
(
PS
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)
m
et
h
o
d
,
a
n
d
to
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q
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t
r
a
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n
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p
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s
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f
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F
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i
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l
a
ti
o
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a
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d
f
i
n
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t
e
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lem
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n
t
a
n
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l
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a
li
d
a
t
e
t
h
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f
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b
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et
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r
o
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b
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o
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d
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a
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H
o
w
e
v
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r
,
a
d
d
i
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PS
O
i
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c
r
e
as
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t
h
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c
o
m
p
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t
at
i
o
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a
l
c
o
m
p
lex
i
t
y
,
w
h
i
c
h
m
i
g
h
t
c
a
u
s
e
i
s
s
u
es
f
o
r
r
e
a
l
-
t
i
m
e
E
V
a
p
p
l
i
c
a
t
i
o
n
s
.
T
w
o
T
SF
-
b
a
s
e
d
m
e
t
h
o
d
s
f
o
r
t
o
r
q
u
e
r
i
p
p
l
e
r
e
d
u
ct
i
o
n
i
n
SR
M
s
w
e
r
e
r
e
p
o
r
t
e
d
i
n
th
e
i
r
p
a
p
e
r
[
2
2
]
-
[
2
4
]
.
T
h
e
y
m
a
t
c
h
e
d
t
h
e
f
l
u
x
l
i
n
k
a
g
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m
o
d
e
l
w
i
t
h
a
4
t
h
-
o
r
d
e
r
F
o
u
r
i
e
r
s
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r
i
es
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n
d
c
o
m
p
u
t
e
d
t
o
r
q
u
e
e
r
r
o
r
u
s
i
n
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a
6
t
h
-
o
r
d
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p
o
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o
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ased
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I
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8
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6
9
4
I
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t J Po
w
E
lec
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Dr
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t
,
Vo
l.
16
,
No
.
3
,
Sep
tem
b
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20
25
:
1537
-
1
5
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1
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R
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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&
Dr
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s
t
I
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N:
2088
-
8
6
9
4
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o
ller
is
f
in
e
-
tu
n
ed
u
s
in
g
th
e
m
o
u
n
tain
g
az
elle
o
p
tim
izer
(
MG
O)
tech
n
i
q
u
e.
MG
O
is
a
n
atu
r
al
o
p
tim
izatio
n
m
eth
o
d
th
at
e
f
f
icien
tly
d
ete
r
m
in
es
th
e
o
p
tim
al
v
alu
es
o
f
Kp
an
d
Ki
b
y
m
i
m
ick
in
g
th
e
s
tr
ateg
ic
m
o
v
e
m
en
ts
an
d
en
er
g
y
-
e
f
f
icien
t
b
e
h
av
io
r
s
o
f
m
o
u
n
tain
g
az
elles.
MG
O
en
s
u
r
es
th
at
th
e
s
p
ee
d
c
o
n
tr
o
ller
ac
h
ie
v
es
b
et
ter
tr
ac
k
in
g
ac
c
u
r
ac
y
an
d
d
y
n
a
m
ic
r
esp
o
n
s
e
wh
ile
m
in
im
izin
g
o
v
e
r
s
h
o
o
t,
s
ettlin
g
tim
e,
an
d
s
tead
y
-
s
tate
er
r
o
r
th
r
o
u
g
h
th
e
o
p
tim
izatio
n
o
f
t
h
e
co
n
tr
o
ller
g
ain
s
.
T
h
is
im
p
r
o
v
ed
PI
-
MG
O
co
n
t
r
o
ller
n
o
t
o
n
ly
im
p
r
o
v
es
th
e
m
o
to
r
'
s
s
p
ee
d
r
eg
u
latio
n
ca
p
ab
il
ities
ac
r
o
s
s
a
r
an
g
e
o
f
o
p
er
atin
g
co
n
d
itio
n
s
,
b
u
t
it
also
r
ed
u
ce
s
to
r
q
u
e
r
ip
p
le
an
d
in
cr
ea
s
es
s
y
s
tem
ef
f
icien
cy
.
T
h
e
PI
-
MG
O
co
n
tr
o
ller
g
en
er
ates th
e
o
u
tp
u
t
to
r
q
u
e
r
ef
er
e
n
ce
s
ig
n
al
(
T
r
e
f
)
,
wh
ich
is
s
en
t to
th
e
T
SF
m
o
d
u
le
.
5
.
ACO
CO
NT
RO
L
F
O
R
T
SF
T
h
e
s
p
ee
d
∗
an
d
th
e
co
m
m
an
d
ed
r
e
f
er
en
ce
to
r
q
u
e
∗
ar
e
t
h
e
in
p
u
ts
.
B
y
u
s
in
g
a
T
SF
b
lo
ck
to
in
tellig
en
tly
d
iv
id
e
th
e
in
p
u
t
to
r
q
u
e
b
etwe
en
m
o
to
r
p
h
ases
,
th
e
p
h
ase
to
r
q
u
e
s
ig
n
al
ℎ
∗
is
p
r
o
d
u
ce
d
.
E
v
er
y
p
h
ase
to
r
q
u
e
s
ig
n
al
is
th
en
tr
an
s
lated
in
to
its
s
u
b
s
eq
u
en
t
r
ef
er
en
ce
cu
r
r
e
n
t
p
r
o
f
ile
i*
,
an
d
b
y
ac
cu
r
ately
tr
ac
k
in
g
th
is
cu
r
r
en
t
u
s
in
g
a
h
y
s
ter
esi
s
co
n
tr
o
ller
,
th
e
to
r
q
u
e
is
in
d
ir
ec
tly
co
n
tr
o
lled
.
Af
ter
co
u
n
tin
g
th
e
r
em
ai
n
in
g
p
o
r
tio
n
o
f
th
e
r
o
to
r
p
o
s
itio
n
(
-
3
0
to
0
)
,
th
e
m
o
d
el
u
s
es
th
e
to
r
q
u
e
an
d
cu
r
r
en
t
lo
o
k
u
p
tab
les.
T
h
e
cu
r
r
e
n
t
lo
o
k
u
p
tab
le
i(
λ
,
θ)
is
p
r
o
d
u
ce
d
b
y
in
v
er
tin
g
th
e
p
o
le
f
lu
x
d
ata
in
Fig
u
r
e
3
.
T
h
e
wav
e
f
o
r
m
s
f
o
r
p
h
as
e
cu
r
r
en
t
(
ip
h
)
an
d
to
tal
elec
tr
o
m
ag
n
etic
to
r
q
u
e
(
T
e)
ar
e
t
h
e
m
o
d
el'
s
o
u
tp
u
ts
.
T
h
e
s
in
u
s
o
id
al
T
SF
,
o
n
e
o
f
th
e
m
o
s
t w
id
ely
u
tili
ze
d
T
SF
k
in
d
s
,
is
em
p
lo
y
ed
in
th
is
m
eth
o
d
b
ec
au
s
e
it
p
r
o
v
id
es
th
e
lo
west
r
ate
o
f
f
lu
x
lin
k
ag
e
c
h
an
g
e
with
th
e
least
am
o
u
n
t
o
f
cu
r
r
en
t.
Fig
u
r
e
3
s
h
o
ws h
o
w
to
u
s
e
AC
O
C
o
n
tr
o
l
to
co
n
tr
o
l
6
/4
SR
M.
(
)
=
{
0
,
(
0
≤
<
)
∗
2
−
∗
2
(
−
)
,
(
≤
<
1
)
∗
,
(
+
≤
<
)
∗
2
+
∗
2
(
−
)
,
(
≤
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2
)
0
,
(
+
≤
<
)
(
1
1
)
W
h
er
e
,
,
,
ar
e
th
e
s
witch
-
o
n
,
s
witch
-
o
f
f
,
o
v
er
lap
,
a
n
d
r
o
to
r
p
itch
an
g
les.
T
h
e
o
v
er
la
p
an
g
le
is
s
u
b
jecte
d
to
(
1
2
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.
≤
2
−
(
1
2
)
B
y
ca
r
ef
u
lly
ch
o
o
s
in
g
t
h
e
o
v
e
r
lap
an
g
le
a
n
d
s
witch
-
o
n
an
g
l
e,
th
e
T
SF
d
is
p
lay
ed
i
n
th
e
a
b
o
v
e
f
ig
u
r
e
m
ay
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e
m
ax
im
ized
.
I
n
th
is
in
v
esti
g
atio
n
,
AC
O
was
u
s
ed
.
T
o
m
in
im
ize
t
h
e
r
ip
p
le
o
f
th
e
t
o
r
q
u
e
an
d
th
e
R
MS
v
alu
e
o
f
th
e
p
h
ase
cu
r
r
e
n
t
wh
i
le
m
ain
tain
in
g
a
r
e
aso
n
ab
le
a
v
er
ag
e
o
u
t
to
r
q
u
e,
th
e
o
p
tim
u
m
v
alu
es
f
o
r
c
o
n
tr
o
l
v
ar
iab
les ar
e
s
elec
ted
u
s
in
g
th
e
p
r
o
p
o
s
ed
AC
O
[
2
6
]
.
5
.
1
.
F
o
rm
ula
t
i
o
n o
f
o
bje
c
t
iv
e
f
un
ct
io
n
T
h
e
o
p
tim
izatio
n
is
s
u
e
is
s
tate
d
(
1
3
)
-
(
1
5
)
:
=
1
(
−
)
+
2
(
)
(
13
)
=
∗
(
1
4
)
≤
2
−
(
1
5
)
wh
er
e
,
an
d
ar
e
th
e
o
u
tp
u
t
to
r
q
u
e
(
T
e
)
wav
ef
o
r
m
'
s
h
ig
h
est,
m
in
im
u
m
,
an
d
av
e
r
ag
e
v
alu
es,
r
esp
ec
tiv
ely
;
w1
an
d
w2
ar
e
w
eig
h
tin
g
f
ac
to
r
s
;
I
rms
is
th
e
p
h
a
s
e
cu
r
r
en
t'
s
R
MS
v
alu
e;
an
d
σ
is
a
s
ca
l
in
g
f
ac
to
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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8
8
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8
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4
I
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t J Po
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E
lec
&
Dr
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s
t
,
Vo
l.
16
,
No
.
3
,
Sep
tem
b
er
20
25
:
1537
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1
5
5
1
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th
at
d
ef
in
es
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e
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p
er
m
itted
as
a
p
er
ce
n
tag
e
o
f
th
e
r
eq
u
e
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ted
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r
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∗
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n
th
is
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tu
d
y
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σ
f
a
lls
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etwe
en
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8
5
a
n
d
0
.
9
5
,
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ile
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d
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e
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et
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0
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1
8
1
2
an
d
0
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3
7
9
1
,
r
esp
ec
tiv
ely
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F
ig
u
r
e
3
.
C
o
n
tr
o
l o
f
6
/4
SR
M
u
s
in
g
AC
O
co
n
tr
o
l
5
.
2
.
Ste
p
-
by
-
s
t
ep
a
lg
o
rit
hm
f
o
r
ACO
T
h
e
A
C
O
a
l
g
o
r
i
t
h
m
w
as
i
m
p
le
m
e
n
t
e
d
i
n
M
A
T
L
A
B
,
w
h
e
r
e
e
a
c
h
a
n
t
r
e
p
r
e
s
e
n
ts
a
p
o
t
e
n
tia
l
s
o
l
u
ti
o
n
(
a
s
e
t
o
f
p
a
r
a
m
e
t
e
r
v
a
l
u
es
)
,
a
n
d
t
h
e
p
h
e
r
o
m
o
n
e
m
a
t
r
i
x
g
u
i
d
e
s
t
h
e
s
e
a
r
c
h
t
o
w
a
r
d
s
p
r
o
m
i
s
i
n
g
r
e
g
i
o
n
s
o
f
t
h
e
s
o
l
u
ti
o
n
s
p
a
c
e
.
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h
e
n
u
m
b
e
r
o
f
n
o
d
e
s
f
o
r
e
a
c
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p
a
r
a
m
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t
e
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w
a
s
s
e
t
t
o
1
0
0
0
t
o
e
n
s
u
r
e
f
i
n
e
r
e
s
o
l
u
t
i
o
n
i
n
t
h
e
p
a
r
a
m
e
t
e
r
s
e
a
r
c
h
s
p
a
c
e
.
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h
e
a
l
g
o
r
it
h
m
u
s
es
p
h
e
r
o
m
o
n
e
t
r
a
i
l
u
p
d
a
t
i
n
g
a
n
d
e
v
a
p
o
r
a
t
i
o
n
t
o
b
a
l
a
n
c
e
e
x
p
l
o
r
a
ti
o
n
a
n
d
e
x
p
l
o
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t
a
t
i
o
n
.
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h
e
s
elec
tio
n
o
f
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O
p
ar
am
eter
s
in
th
is
s
tu
d
y
in
clu
d
es
th
e
n
u
m
b
er
o
f
an
ts
(
NA
=
1
0
)
,
p
h
er
o
m
o
n
e
ev
ap
o
r
atio
n
r
ate
(
ρ
=
0
.
7
)
,
a
n
d
weig
h
tin
g
f
ac
t
o
r
s
(
α
=
0
.
8
,
β
=
0
.
2
)
wer
e
g
u
id
ed
b
y
e
m
p
ir
ical
tu
n
in
g
a
n
d
s
u
p
p
o
r
ted
b
y
ex
is
tin
g
liter
atu
r
e.
T
h
ese
v
alu
es
wer
e
ch
o
s
en
af
ter
co
n
d
u
ctin
g
p
r
elim
in
a
r
y
ex
p
er
im
en
ts
to
b
alan
ce
s
o
lu
tio
n
q
u
ality
a
n
d
c
o
m
p
u
tatio
n
al
ef
f
icie
n
cy
.
A
m
o
d
er
ate
n
u
m
b
er
o
f
a
n
ts
en
s
u
r
ed
s
u
f
f
ic
ien
t
s
ea
r
ch
d
iv
er
s
ity
with
o
u
t
in
cu
r
r
in
g
e
x
ce
s
s
iv
e
co
m
p
u
tatio
n
al
o
v
er
h
ea
d
.
T
h
e
ev
ap
o
r
atio
n
r
ate
was
s
et
at
0
.
7
to
r
etain
u
s
ef
u
l
s
o
lu
tio
n
in
f
o
r
m
atio
n
wh
ile
allo
win
g
ex
p
lo
r
atio
n
o
f
n
ew
p
ath
s
.
T
h
e
weig
h
tin
g
p
ar
a
m
eter
s
wer
e
s
et
to
em
p
h
asize
p
h
er
o
m
o
n
e
i
n
f
lu
en
ce
(
α
)
o
v
e
r
h
eu
r
is
tic
in
f
o
r
m
a
tio
n
(
β),
alig
n
in
g
with
th
e
n
atu
r
e
o
f
th
e
co
n
tr
o
l p
r
o
b
lem
wh
e
r
e
p
r
io
r
s
o
lu
tio
n
f
ee
d
b
ac
k
is
m
o
r
e
cr
itical
th
an
d
ir
ec
t h
e
u
r
is
tics
.
5
.
2
.
1
.
I
m
plem
ent
a
t
i
o
n
T
h
is
s
ec
tio
n
p
r
esen
ts
t
h
e
s
tep
-
by
-
s
tep
im
p
lem
e
n
tatio
n
o
f
th
e
AC
O
alg
o
r
ith
m
,
s
tar
tin
g
f
r
o
m
p
ar
am
eter
in
itializatio
n
an
d
en
d
i
n
g
with
t
h
e
f
in
al
s
y
s
tem
p
er
f
o
r
m
a
n
ce
e
v
alu
atio
n
:
a)
I
n
itialize
AC
O
p
ar
am
eter
s
−
Sp
ec
if
y
a
n
u
m
b
er
o
f
iter
atio
n
s
,
th
e
n
u
m
b
e
r
o
f
a
n
ts
,
an
d
o
th
er
p
ar
am
eter
s
r
elate
d
to
th
e
m
eth
o
d
,
in
clu
d
in
g
th
e
ev
a
p
o
r
atio
n
r
ate,
alp
h
a
(
α
)
,
b
eta
(
β),
n
u
m
b
er
o
f
v
ar
iab
les,
lo
wer
an
d
u
p
p
er
b
o
u
n
d
s
,
an
d
n
u
m
b
er
o
f
n
o
d
es.
−
I
n
itialize
th
e
p
h
er
o
m
o
n
e
m
atr
ix
(
T
)
with
a
s
m
all
p
o
s
itiv
e
v
alu
e
(
e
p
s
)
an
d
cr
ea
te
p
lace
h
o
ld
er
s
f
o
r
v
ar
io
u
s
v
ar
ia
b
les s
u
ch
as a
n
t p
o
s
itio
n
s
,
co
s
ts
,
an
d
p
r
o
b
ab
ilit
ies.
b)
Gen
er
ate
n
o
d
es
−
Div
id
e
th
e
p
ar
am
eter
s
ea
r
ch
s
p
ac
e
in
to
d
is
cr
ete
n
o
d
es,
eq
u
a
lly
s
p
ac
ed
b
etwe
en
th
e
lo
wer
an
d
u
p
p
er
b
o
u
n
d
s
f
o
r
ea
c
h
p
ar
a
m
eter
.
T
h
ese
n
o
d
es r
ep
r
esen
t
p
o
ten
tial so
lu
tio
n
s
to
b
e
e
x
p
lo
r
ed
b
y
th
e
an
ts
.
c)
Star
t iter
atio
n
lo
o
p
−
Fo
r
ea
ch
iter
atio
n
,
ca
lcu
late
t
h
e
p
r
o
b
ab
ilit
y
o
f
s
elec
tin
g
ea
ch
n
o
d
e
f
o
r
ea
ch
p
ar
am
eter
b
ased
o
n
th
e
p
h
er
o
m
o
n
e
lev
els an
d
h
e
u
r
is
tic
v
alu
es (
in
v
er
s
ely
p
r
o
p
o
r
tio
n
al
to
th
e
n
o
d
es'
v
alu
es).
d)
T
o
u
r
c
o
n
s
tr
u
ctio
n
b
y
a
n
ts
−
Fo
r
ea
ch
an
t,
d
eter
m
in
e
its
p
at
h
(
i.e
.
,
p
ar
am
eter
v
alu
es)
b
y
s
elec
tin
g
n
o
d
es p
r
o
b
a
b
ilis
tically
:
−
Gen
er
ate
a
r
an
d
o
m
n
u
m
b
e
r
to
s
im
u
late
a
r
o
u
lette
wh
ee
l selec
tio
n
.
−
Acc
u
m
u
late
p
r
o
b
ab
ilit
ies
f
o
r
e
ac
h
n
o
d
e
u
n
til
th
e
s
u
m
ex
ce
ed
s
to
ch
o
o
s
e
th
e
co
r
r
esp
o
n
d
i
n
g
n
o
d
e
in
d
e
x
.
e)
E
v
alu
ate
co
s
t f
u
n
ctio
n
−
Use
th
e
s
elec
ted
p
ar
a
m
eter
v
alu
es
to
co
m
p
u
te
th
e
c
o
s
t
f
o
r
ea
ch
an
t.
T
h
is
s
tep
i
n
v
o
lv
es r
u
n
n
in
g
a
co
s
t
f
u
n
ctio
n
th
at
ev
alu
ates
th
e
ex
ce
llen
ce
o
f
ch
o
s
en
p
ar
am
eter
s
cr
ea
ted
o
n
a
s
p
ec
if
ic
s
y
s
tem
,
in
d
icatin
g
p
er
f
o
r
m
an
ce
,
s
u
c
h
as e
r
r
o
r
s
in
s
p
ee
d
an
d
c
u
r
r
e
n
t.
f)
Up
d
ate
th
e
b
est s
o
lu
tio
n
−
I
d
en
tify
th
e
an
t
with
th
e
m
in
i
m
u
m
co
s
t
an
d
its
co
r
r
esp
o
n
d
i
n
g
p
ar
am
eter
s
.
I
f
th
e
c
u
r
r
en
t b
est
s
o
lu
tio
n
is
wo
r
s
e
th
an
th
e
p
r
e
v
io
u
s
iter
atio
n
'
s
b
est,
r
etain
th
e
p
r
ev
io
u
s
b
est s
o
lu
tio
n
(
elitis
m
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
To
r
q
u
e
s
h
a
r
in
g
fu
n
ctio
n
o
p
timiz
a
tio
n
fo
r
s
w
itch
ed
r
elu
cta
n
ce
mo
to
r
…
(
Dh
iya
a
Mo
h
a
mm
ed
I
s
ma
el
)
1545
g)
Ph
er
o
m
o
n
e
u
p
d
ate
−
C
alcu
late
th
e
ch
an
g
e
in
p
h
er
o
m
o
n
e
lev
els (
d
T
)
f
o
r
ea
ch
n
o
d
e
b
ased
o
n
t
h
e
co
s
ts
o
f
th
e
a
n
t
s
:
−
No
d
es v
is
ited
b
y
b
etter
-
p
er
f
o
r
m
in
g
an
ts
r
ec
eiv
e
h
ig
h
er
p
h
e
r
o
m
o
n
e
i
n
cr
em
en
ts
.
−
Up
d
ate
th
e
p
h
e
r
o
m
o
n
e
m
at
r
ix
(
T
)
b
y
c
o
m
b
in
i
n
g
t
h
e
cu
r
r
en
t
l
ev
els
an
d
th
e
n
ewly
ca
lcu
lated
ch
an
g
es,
s
ca
led
b
y
th
e
ev
a
p
o
r
atio
n
r
ate
(
r
o
h
)
.
h)
I
ter
ativ
e
o
p
tim
izatio
n
−
Sto
r
e
th
e
b
est co
s
t a
n
d
p
ar
am
e
ter
v
alu
es f
o
r
th
e
cu
r
r
en
t iter
at
io
n
.
−
Plo
t th
e
co
n
v
er
g
en
ce
o
f
th
e
c
o
s
t o
v
er
iter
atio
n
s
f
o
r
v
is
u
aliza
tio
n
.
i)
Simu
latio
n
an
d
s
y
s
tem
ev
alu
at
io
n
−
E
x
tr
ac
t th
e
o
p
tim
ized
p
ar
a
m
eter
s
(
k
e,
k
ce
)
f
r
o
m
th
e
b
est
-
p
er
f
o
r
m
in
g
an
t.
−
Ass
ig
n
th
ese
p
ar
am
eter
s
to
t
h
e
s
im
u
latio
n
e
n
v
ir
o
n
m
en
t
(
e
.
g
.
,
a
Simu
lin
k
m
o
d
el
)
to
s
im
u
late
th
e
s
y
s
tem
’
s
p
er
f
o
r
m
an
ce
o
v
e
r
a
d
ef
in
ed
tim
e
p
e
r
io
d
.
−
C
o
m
p
u
te
p
er
f
o
r
m
a
n
ce
m
etr
ics (
e.
g
.
,
s
p
ee
d
an
d
cu
r
r
en
t e
r
r
o
r
s
)
b
ased
o
n
s
im
u
latio
n
r
esu
lts
.
j)
C
o
m
p
u
te
f
in
al
f
itn
ess
v
alu
e
−
C
alcu
late
th
e
f
itn
ess
v
alu
e
as
a
weig
h
ted
s
u
m
o
f
th
e
p
e
r
f
o
r
m
an
ce
m
etr
ics
(
e.
g
.
,
s
p
ee
d
a
n
d
cu
r
r
en
t
er
r
o
r
s
)
.
−
T
h
is
v
alu
e
d
eter
m
in
es
th
e
q
u
ality
o
f
th
e
s
elec
ted
p
ar
a
m
eter
s
an
d
p
r
o
v
id
es
f
ee
d
b
ac
k
t
o
g
u
id
e
th
e
alg
o
r
ith
m
in
s
u
b
s
eq
u
en
t iter
ati
o
n
s
.
k)
E
n
d
th
e
alg
o
r
ith
m
−
Af
ter
co
m
p
letin
g
t
h
e
tar
g
et
v
a
lu
e
o
f
ep
o
ch
s
,
r
etu
r
n
th
e
o
p
ti
m
ized
p
ar
am
eter
s
an
d
th
e
co
r
r
esp
o
n
d
in
g
f
itn
ess
v
alu
e.
F
o
l
l
o
w
i
n
g
t
h
es
e
p
r
o
c
e
d
u
r
e
s
,
th
e
A
C
O
a
l
g
o
r
i
t
h
m
it
e
r
a
t
i
v
el
y
i
m
p
r
o
v
e
s
t
h
e
s
y
s
t
e
m
'
s
p
e
r
f
o
r
m
a
n
c
e
b
y
o
p
t
i
m
i
z
i
n
g
t
h
e
p
a
r
a
m
e
t
e
r
s
t
h
r
o
u
g
h
c
o
l
l
e
c
t
i
v
e
a
n
t
b
e
h
a
v
i
o
r
,
p
r
o
b
a
b
i
l
i
s
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i
c
d
e
c
is
i
o
n
-
m
a
k
i
n
g
,
a
n
d
p
h
e
r
o
m
o
n
e
r
e
i
n
f
o
r
c
e
m
e
n
t
m
e
c
h
a
n
is
m
s
.
Fig
u
r
e
4
p
r
e
s
e
n
ts
t
h
e
f
l
o
w
d
i
a
g
r
am
f
o
r
t
h
e
s
u
g
g
e
s
t
e
d
s
y
s
t
e
m
u
s
in
g
t
h
e
AC
O
m
e
t
h
o
d
.
Fig
u
r
e
4
.
Flo
w
d
ia
g
r
am
f
o
r
th
e
s
u
g
g
ested
s
y
s
tem
u
tili
zin
g
th
e
AC
O
m
eth
o
d
6.
RE
SU
L
T
S & D
I
SCU
SS
I
O
N
T
h
e
s
u
g
g
ested
m
eth
o
d
'
s
o
u
tco
m
es a
r
e
ex
am
in
ed
b
o
th
with
a
n
d
with
o
u
t
o
p
tim
izatio
n
as f
o
llo
ws:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
3
,
Sep
tem
b
er
20
25
:
1537
-
1
5
5
1
1546
6
.
1
.
Wit
ho
ut
o
ptim
iza
t
io
n
6
.
1
.
1
.
Co
ns
t
a
nt
s
peed
Du
r
in
g
th
is
o
p
e
r
atio
n
,
t
h
e
s
y
s
tem
is
o
p
er
ated
at
a
co
n
s
tan
t
s
p
ee
d
;
Fig
u
r
e
5
r
ep
r
esen
ts
th
e
to
r
q
u
e
&
s
p
ee
d
o
b
tain
e
d
d
u
r
in
g
co
n
s
tan
t
s
p
ee
d
.
T
h
e
to
r
q
u
e
v
ar
ies
b
et
wee
n
-
2
0
Nm
an
d
1
0
Nm
,
wh
i
le
th
e
s
p
ee
d
e
x
h
ib
its
o
s
cillatio
n
s
with
s
ig
n
if
ican
t
r
ip
p
le
co
n
ten
t.
Fig
u
r
e
6
r
ep
r
esen
t
s
th
e
c
u
r
r
e
n
t
with
o
u
t
o
p
tim
izat
io
n
d
u
r
in
g
co
n
s
tan
t
s
p
ee
d
co
n
d
itio
n
s
;
h
er
e
,
th
e
m
a
x
im
u
m
cu
r
r
en
t is ar
o
u
n
d
6
0
A
.
6
.
1
.
2
.
Va
ry
ing
s
peed
D
u
r
i
n
g
t
h
i
s
c
o
n
d
i
t
i
o
n
,
t
h
e
s
y
s
t
em
i
s
o
p
e
r
a
te
d
a
t
v
a
r
i
a
b
l
e
s
p
e
e
d
,
a
n
d
t
h
e
t
o
r
q
u
e
&
t
h
e
c
u
r
r
e
n
t
a
r
e
d
e
n
o
t
e
d
i
n
F
i
g
u
r
e
7
.
I
n
t
h
is
c
o
n
d
i
t
i
o
n
,
th
e
o
s
c
il
l
a
ti
o
n
is
m
o
r
e
i
n
t
o
r
q
u
e
&
s
p
e
e
d
;
t
h
e
s
p
e
e
d
is
s
u
b
j
e
cte
d
t
o
o
s
c
i
ll
a
t
i
o
n
s
&
t
o
r
q
u
e
h
a
s
h
i
g
h
e
r
r
i
p
p
le
c
o
n
t
e
n
t
.
T
h
e
c
u
r
r
e
n
t
d
u
r
i
n
g
v
a
r
y
i
n
g
s
p
e
e
d
wi
t
h
o
u
t
o
s
c
i
ll
a
t
i
o
n
i
s
r
e
p
r
es
e
n
t
e
d
i
n
F
i
g
u
r
e
8
.
H
e
r
e
a
r
e
m
o
r
e
c
u
r
r
e
n
t
r
i
p
p
l
e
s
.
T
h
e
m
a
x
i
m
u
m
p
e
a
k
cu
r
r
e
n
t
a
p
p
e
a
r
s
i
n
d
i
f
f
e
r
e
n
t
i
n
s
t
an
c
e
s
.
Fig
u
r
e
5
.
C
o
n
s
tan
t
s
p
ee
d
a
n
d
t
o
r
q
u
e
with
o
u
t
o
p
tim
izatio
n
Fig
u
r
e
6
.
C
u
r
r
e
n
t w
ith
o
u
t
o
p
ti
m
izatio
n
d
u
r
in
g
co
n
s
tan
t sp
ee
d
Fig
u
r
e
7
.
Var
y
in
g
s
p
ee
d
an
d
to
r
q
u
e
with
o
u
t
o
p
tim
izatio
n
Fig
u
r
e
8
.
C
u
r
r
e
n
t w
ith
o
u
t
o
p
ti
m
izatio
n
d
u
r
in
g
v
ar
y
i
n
g
s
p
ee
d
s
6
.
2
.
Wit
h AC
O
O
ptim
iza
t
io
n
6
.
2
.
1
.
Co
ns
t
a
nt
s
peed
Du
r
in
g
th
is
co
n
d
itio
n
,
AC
O
is
im
p
lem
en
ted
to
tu
n
e
th
e
co
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tr
o
l
v
ar
iab
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th
er
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,
th
e
to
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q
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ip
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e
o
s
cillatio
n
in
th
e
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d
a
r
e
m
in
im
ized
.
Fig
u
r
e
9
r
ep
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esen
ts
th
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n
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p
ee
d
&
to
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q
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e
with
o
p
tim
izatio
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T
h
e
to
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q
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e
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b
elo
w
1
0
Nm
,
an
d
th
e
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w.
T
h
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d
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g
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with
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izatio
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p
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Fig
u
r
e
1
0
,
th
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m
ax
im
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m
cu
r
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e
n
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o
b
tain
ed
is
5
.
5
A.
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