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20
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I
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I
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t J E
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&
C
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p
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g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
2
5
-
6
2
3
6
6226
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7
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esti
g
atio
n
o
f
th
e
ef
f
ec
ts
o
f
T
im
e
d
o
m
ain
c
h
ar
ac
ter
is
tics
,
v
iz.
,
,
,
,
an
d
p
o
wer
q
u
ality
is
s
u
es
v
iz.
,
p
o
wer
f
ac
to
r
(
PF
)
an
d
to
tal
h
a
r
m
o
n
ic
d
is
to
r
tio
n
(
T
HD)
s
im
u
ltan
eo
u
s
ly
as
a
n
o
v
el
attem
p
t.
A
v
ar
iety
o
f
s
p
ee
d
co
n
tr
o
ller
s
a
n
d
s
tate
-
of
-
th
e
-
a
r
t
co
n
tr
o
llin
g
tech
n
iq
u
es
h
av
e
b
ee
n
u
s
ed
f
o
r
s
o
lv
i
n
g
th
is
p
r
o
b
lem
.
M
etah
eu
r
is
tic
o
p
tim
izatio
n
is
a
u
n
iq
u
e
tec
h
n
iq
u
e
th
at
ca
n
h
a
n
d
le
u
n
ce
r
tain
ties
an
d
n
o
n
lin
ea
r
p
ar
am
eter
s
.
Hen
ce
it
h
as
b
ee
n
u
s
ed
f
o
r
th
e
f
in
e
tu
n
in
g
o
f
th
e
co
n
tr
o
ller
g
ain
s
co
n
s
id
er
in
g
i
ts
ab
ilit
y
to
p
r
o
v
id
e
ap
p
r
o
p
r
ia
te
s
o
lu
tio
n
s
f
o
r
th
e
p
r
o
b
lem
s
in
cr
ea
s
ed
in
n
o
n
lin
ea
r
p
r
o
g
r
am
m
in
g
-
h
ar
d
s
itu
atio
n
s
[
8
]
.
T
h
e
th
r
ee
co
n
tr
ib
u
tio
n
s
to
im
p
r
o
v
e
th
e
d
y
n
am
ic
p
r
o
p
e
r
ties
o
f
B
L
DC
d
r
iv
es a
r
e
lis
ted
b
elo
w.
−
T
h
e
ar
tific
ial
im
m
u
n
e
s
y
s
tem
(
AI
S)
,
h
o
n
ey
b
ee
m
atin
g
o
p
tim
izatio
n
(
HB
O)
co
n
tr
o
l
s
y
s
te
m
is
in
ten
d
e
d
f
o
r
an
aly
s
is
o
f
th
e
co
n
t
r
o
ller
'
s
p
er
f
o
r
m
an
ce
in
ter
m
s
o
f
s
ev
er
al
m
etr
ics r
elate
d
to
m
o
to
r
d
y
n
a
m
ics.
−
T
h
e
f
r
o
g
lea
p
in
g
g
u
id
ed
(
FL
G)
alg
o
r
ith
m
,
s
o
m
etim
es
k
n
o
wn
as
“
Fro
g
ju
m
p
in
g
alg
o
r
ith
m
”
is
a
p
o
wer
f
u
l
o
p
tim
izatio
n
tech
n
i
q
u
e
in
t
h
e
d
r
iv
e
cir
cu
its
.
−
C
o
m
p
ar
is
o
n
with
r
esu
lts
s
ee
n
in
h
ar
d
war
e
,
h
elp
s
v
er
if
icatio
n
o
f
t
h
e
b
e
h
av
io
r
o
f
th
e
m
o
to
r
with
th
e
u
s
e
o
f
th
e
s
im
u
lated
o
u
tco
m
e.
T
h
e
p
a
p
er
is
o
r
g
an
ize
d
as
f
o
llo
ws:
s
ec
tio
n
2
d
ea
ls
with
o
u
tli
n
e.
Sectio
n
3
d
is
cu
s
s
es
s
p
ee
d
co
n
tr
o
ller
s
th
at
u
s
e
d
if
f
er
en
t
u
n
iq
u
e
o
p
tim
izatio
n
s
s
u
ch
as
HB
O,
AI
S,
an
d
FLG
.
Sectio
n
4
r
ef
er
s
to
r
esu
lts
an
d
d
is
cu
s
s
io
n
;
s
ec
tio
n
5
p
r
esen
ts
th
e
h
ar
d
war
e
d
esig
n
an
d
r
esu
lts
.
Sectio
n
6
r
ef
lects
th
e
c
o
n
clu
s
io
n
s
to
en
s
u
r
e
th
at
it m
ee
ts
th
e
b
en
ch
m
a
r
k
s
s
et
b
y
th
e
I
E
E
E
s
tan
d
ar
d
s
b
y
c
o
m
p
ar
in
g
with
s
im
u
lated
r
esu
l
ts
.
2.
WO
RK
-
O
UT
L
I
NE
Var
io
u
s
m
et
ah
e
u
r
is
tic
al
g
o
r
it
h
m
s
w
it
h
i
n
s
p
ir
ati
o
n
f
r
o
m
n
atu
r
e
h
av
e
b
ee
n
d
e
v
e
lo
p
ed
r
ec
e
n
t
ly
f
o
r
m
a
x
i
m
at
io
n
o
f
t
h
e
co
n
t
r
o
l
s
y
s
te
m
g
a
in
s
o
f
B
L
DC
m
o
t
o
r
s
.
S
m
a
r
t
c
o
m
p
u
ti
n
g
t
ec
h
n
iq
u
es
ar
e
b
ec
o
m
i
n
g
in
c
r
ea
s
i
n
g
l
y
p
o
p
u
l
ar
i
n
c
o
n
tr
o
l
e
n
g
in
ee
r
i
n
g
,
as
d
em
o
n
s
t
r
at
ed
[
9
]
.
I
t
h
as
b
ee
n
s
u
g
g
est
e
d
th
e
a
d
a
p
ti
v
e
f
u
zz
y
p
r
o
p
o
r
ti
o
n
al
–
i
n
te
g
r
a
l
–
d
e
r
i
v
ati
v
e
(
PI
D
)
c
o
n
t
r
o
l
s
p
ee
d
f
o
r
im
p
r
o
v
em
en
t in
t
h
e
s
p
e
e
d
c
o
n
tr
o
l
ch
ar
ac
t
er
is
ti
c
o
f
t
h
e
B
L
DC
d
r
i
v
es
[
1
0
]
.
An
ad
a
p
ti
v
e
f
u
zz
y
l
o
g
ic
c
o
n
tr
o
l
le
r
(
F
L
C
)
a
n
d
a
s
im
p
l
e
P
I
D
c
o
n
t
r
o
lle
r
a
r
e
c
o
m
p
o
n
e
n
ts
o
f
th
e
s
u
g
g
este
d
s
y
s
te
m
.
T
h
is
m
e
th
o
d
u
s
es
g
e
n
et
ic
al
g
o
r
it
h
m
(
GA)
f
o
r
th
e
f
i
n
e
t
u
r
n
in
g
o
f
t
h
e
c
o
n
tr
o
l
le
r
g
ai
n
s
f
o
r
th
e
m
a
n
a
g
em
en
t
o
f
s
p
ee
d
o
f
t
h
e
B
L
DC
m
o
t
o
r
t
ill
r
ea
c
h
es
a
s
p
e
ci
f
ic
s
t
ea
d
y
s
tat
e
c
o
n
d
i
ti
o
n
.
A
GA
o
p
ti
m
iz
ati
o
n
f
u
zz
y
-
PI
D
c
o
n
t
r
o
ll
er
f
o
r
i
m
p
r
o
v
e
m
e
n
t
in
b
e
h
a
v
i
o
r
c
r
ea
t
ed
[
1
1
]
,
ad
a
p
ti
v
e
f
ac
t
o
r
,
m
u
l
ti
-
o
b
j
ec
ti
v
e
e
q
u
a
ti
o
n
a
n
d
im
p
r
o
v
e
d
d
if
f
e
r
e
n
t
ial
e
v
o
l
u
ti
o
n
al
(
DE
)
a
p
p
r
o
a
c
h
ar
e
u
s
e
d
t
o
o
p
ti
m
iz
e
th
e
g
ai
n
s
o
f
t
h
e
co
n
t
r
o
ll
er
[
1
2
]
.
Par
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
,
is
a
m
eth
o
d
f
o
r
in
cr
e
asin
g
co
n
tr
o
ller
g
o
als
[
1
3
]
.
T
h
e
s
tu
d
y
d
em
o
n
s
tr
ated
th
at,
in
co
m
p
ar
is
o
n
to
GA
-
b
ased
co
n
t
r
o
ller
s
,
th
e
s
u
g
g
ested
PS
O
b
ased
a
lg
o
r
ith
m
p
r
o
d
u
ce
d
lo
wer
lev
els
o
f
o
v
er
s
h
o
o
t
(
6
3
.
9
4
%),
p
ea
k
tim
e
(
0
.
2
6
s
ec
o
n
d
s
)
,
an
d
co
r
r
ec
tio
n
tim
e
(
1
.
4
s
ec
o
n
d
s
)
.
Acc
o
r
d
in
g
to
th
ese
f
in
d
in
g
s
,
ch
o
ice
o
f
th
e
co
n
tr
o
ller
'
s
p
ar
am
eter
h
as
a
m
ajo
r
im
p
ac
t
o
n
p
er
f
o
r
m
an
ce
.
T
h
e
au
th
o
r
s
u
s
ed
a
tr
ad
itio
n
al
ap
p
r
o
ac
h
with
th
i
s
alg
o
r
ith
m
f
o
r
th
e
ap
p
licati
o
n
o
f
d
r
iv
es.
Usi
n
g
an
e
n
h
a
n
ce
d
DE
ap
p
r
o
ac
h
,
B
eig
et
a
l.
[
1
4
]
s
u
g
g
ested
s
witch
in
g
p
atter
n
f
o
r
p
u
ls
e
wid
th
m
o
d
u
latio
n
tech
n
iq
u
e
to
co
n
tr
o
l sp
ee
d
.
T
h
e
s
u
cc
ess
f
u
l
ap
p
licatio
n
d
ep
en
d
s
u
p
o
n
c
o
m
p
o
n
en
t
id
e
n
tific
atio
n
in
p
o
we
r
co
n
v
er
ter
b
ased
o
n
ap
p
licatio
n
[
1
5
]
.
T
h
is
tech
n
iq
u
e
is
u
s
ed
to
ac
h
iev
e
th
e
m
in
im
izin
g
er
r
o
r
wh
ile
m
ax
im
izi
n
g
co
n
tr
o
ller
g
ain
s
.
Salp
s
war
m
o
p
tim
izatio
n
alg
o
r
ith
m
was
p
r
o
p
o
s
ed
f
o
r
B
L
DC
m
o
to
r
s
with
s
en
s
o
r
s
[
1
6
]
.
I
n
o
r
d
er
t
o
m
a
x
im
ize
th
e
b
en
e
f
its
o
f
a
co
n
v
en
tio
n
al
co
n
tr
o
ller
,
an
ad
ju
s
tab
le
s
p
ee
d
an
d
p
o
wer
f
ac
to
r
c
o
r
r
e
ctio
n
co
n
t
r
o
ller
is
p
r
o
p
o
s
ed
[
1
7
]
,
h
o
we
v
er
th
ey
d
id
n
o
t
an
aly
ze
t
h
e
T
HD.
A
g
r
ey
wo
lf
o
p
tim
izatio
n
tech
n
iq
u
e
was
p
r
esen
ted
f
o
r
th
e
o
p
tim
izatio
n
o
f
t
h
e
g
ai
n
s
o
f
th
e
p
r
o
p
o
r
tio
n
al
–
in
te
g
r
al
(
PID
)
co
n
tr
o
ller
o
f
B
L
DC
m
o
to
r
s
[
1
8
]
.
Simu
ltan
eo
u
s
an
aly
s
is
o
f
th
e
tim
e
d
o
m
ai
n
s
p
ec
if
icatio
n
s
a
n
d
p
o
wer
q
u
ality
is
s
u
es
th
r
o
u
g
h
o
p
tim
izatio
n
is
th
e
n
ee
d
o
f
th
e
h
o
u
r
as
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
is
will
en
s
u
r
e
h
i
g
h
er
im
p
ac
t
in
th
e
d
r
iv
e
s
y
s
tem
.
I
E
E
E
s
tan
d
ar
d
519
-
2
0
1
4
r
ec
o
m
m
e
n
d
s
th
e
h
ar
m
o
n
ics
lim
its
,
lo
wer
T
HD
im
p
lies
lo
w
elec
tr
o
m
ag
n
etic
in
ter
f
er
en
ce
(
E
MI
)
,
lo
w
h
ea
tin
g
a
n
d
lo
w
ir
o
n
co
r
e
lo
s
s
.
Stato
r
v
o
lta
g
e
h
ar
m
o
n
ics
ca
n
g
e
n
er
ate
to
r
q
u
e
r
ip
p
le,
wh
ich
im
p
e
d
es
s
m
o
o
th
o
p
e
r
atio
n
a
n
d
in
c
r
ea
s
es
h
ea
t
an
d
in
a
d
d
itio
n
t
o
th
at
p
o
s
itiv
e
s
eq
u
en
ce
c
o
m
p
o
n
en
t
is
r
esp
o
n
s
ib
le
f
o
r
o
v
er
h
ea
tin
g
an
d
n
eg
ativ
e
s
eq
u
en
ce
co
m
p
o
n
en
t is r
esp
o
n
s
ib
le
f
o
r
to
r
q
u
e
r
ip
p
le.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
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g
I
SS
N:
2088
-
8
7
0
8
P
erfo
r
ma
n
ce
en
h
a
n
ce
me
n
t o
f
b
r
u
s
h
less
d
ir
ec
t c
u
r
r
en
t m
o
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u
n
d
er d
iffer
en
t
…
(
B
a
b
u
A
s
h
o
k
)
6227
Fig
u
r
e
1
.
Stru
ctu
r
e
o
f
co
n
tr
o
ller
3.
SPEE
D
CO
NT
RO
L
L
E
R
U
S
I
NG
VARIO
U
S O
P
T
I
M
I
Z
A
T
I
O
NS
-
S
I
M
UL
AT
E
D
RE
S
UL
T
S
3
.
1
.
H
o
ney
bee
m
a
t
ing
o
ptim
iza
t
io
n
(
H
B
O
t
un
ed
co
ntr
o
ller
f
o
r
B
L
DC
m
o
t
o
r
)
A
g
o
al
o
f
o
p
tim
izatio
n
-
b
ased
s
o
lu
tio
n
s
in
th
is
d
i
g
ital
er
a
is
to
r
ed
u
ce
m
a
n
u
al
lab
o
r
an
d
s
o
lu
tio
n
tim
e.
R
esear
ch
er
s
h
av
e
p
r
o
d
u
ce
d
a
p
leth
o
r
a
o
f
s
o
f
twar
e
p
a
ck
ag
es
th
at
ac
h
iev
e
th
is
d
u
al
b
en
ef
it.
Ho
n
e
y
b
ee
m
atin
g
o
p
tim
izatio
n
[
1
9
]
is
e
m
p
lo
y
ed
as
a
s
o
f
t
co
m
p
u
tin
g
m
eth
o
d
w
h
er
e
iter
atio
n
s
ar
e
c
ar
r
ied
o
u
t
u
n
til
th
e
d
esire
d
s
p
ee
d
is
r
ea
ch
ed
.
An
n
ea
lin
g
f
u
n
ctio
n
f
o
r
q
u
ee
n
p
r
o
b
a
b
ilit
y
,
ac
ce
p
t
th
d
r
o
n
e
to
m
ate
an
d
im
p
r
o
v
e
t
r
ial
s
o
lu
tio
n
is
,
(
,
)
=
[
−
∆
(
)
(
)
]
(
1
)
∆
(
)
r
ef
er
,
m
o
d
u
l
u
s
v
alu
e
o
f
f
itn
es
s
d
if
f
er
en
ce
with
d
r
o
n
e
an
d
q
u
ee
n
.
W
h
en
m
atin
g
f
lig
h
t is in
p
r
o
g
r
ess
b
o
t
h
q
u
ee
n
’
s
s
p
ee
d
a
n
d
e
n
er
g
y
r
ed
u
ce
s
im
u
ltan
eo
u
s
ly
af
ter
ea
ch
iter
atio
n
.
(
+
1
)
=
∞
(
)
(
2
)
wh
er
e
€
[
0
,
1
,
2
,
…
]
an
d
d
ec
ay
r
ate
0
<
∞
<
1
(
+
1
)
=
(
)
−
ℎ
€
[
0
,
1
,
2
…
.
]
ℎ
[
0
,
1
]
(
3
)
Qu
ee
n
u
p
d
ates its
en
er
g
y
an
d
s
p
ee
d
with
th
e
u
s
e
o
f
(
2
)
an
d
(
3
)
.
Ma
tin
g
f
lig
h
t e
n
d
s
wh
en
th
e
en
er
g
y
lev
el
f
alls
b
elo
w
a
th
r
esh
o
l
d
v
alu
e
(
clo
s
e
to
ze
r
o
)
.
−
Qu
ee
n
:
Hig
h
est we
ig
h
tag
e
in
t
h
e
clu
s
ter
at
th
e
cu
r
r
en
t
in
s
tan
t.
−
Dr
o
n
e:
L
o
w
weig
h
ta
g
e
3
.
2
.
Art
if
icia
l
im
m
un
e
s
y
s
t
em
L
if
e
b
ec
o
m
es
f
atal
i
n
th
e
a
b
s
en
ce
o
f
im
m
u
n
e
s
y
s
tem
.
AI
S
m
im
ics’
h
u
m
an
im
m
u
n
o
lo
g
y
ap
p
lied
to
co
m
p
licated
is
s
u
es.
A
s
in
g
le
an
tig
en
ca
n
b
e
r
ec
o
g
n
ized
b
y
s
ev
er
al
an
tib
o
d
ies.
As
s
h
o
wn
in
Fig
u
r
e
2
,
AI
S
d
is
tin
g
u
is
h
es
b
etwe
en
an
tig
en
an
d
an
tib
o
d
y
;
th
is
p
h
e
n
o
m
en
o
n
is
u
tili
ze
d
as
a
to
o
l
f
o
r
n
o
n
lin
ea
r
a
n
d
tim
e
v
ar
ian
t a
p
p
licatio
n
s
[
2
0
]
–
[
2
2
]
.
T
h
e
f
o
llo
win
g
s
tep
s
ar
e
in
v
o
lv
ed
in
th
e
p
r
o
ce
s
s
.
a.
I
n
itializatio
n
An
tig
en
-
v
alu
e
to
b
e
o
p
tim
ize
d
is
o
b
jectiv
e
f
u
n
ctio
n
(
)
an
d
a
n
tib
o
d
ies
-
co
r
r
esp
o
n
d
i
n
g
s
o
lu
ti
o
n
to
th
e
p
r
o
b
lem
s
.
b.
C
lo
n
in
g
ℎ
,
=
Ʃ
(
∗
/
)
(
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
2
5
-
6
2
3
6
6228
wh
er
e
=
1
,
2
,
3
…
,
is
clo
n
e
n
u
m
b
er
,
m
e
an
s
m
u
ltip
lier
f
ac
to
r
,
an
d
r
ef
er
s
an
tib
o
d
ies
p
o
p
u
latio
n
s
ize.
c.
Hy
p
er
m
u
tatio
n
C
lo
n
es
ar
e
m
u
tated
in
in
v
e
r
s
e
p
r
o
p
o
r
tio
n
o
f
a
f
f
in
ity
an
d
N
an
tib
o
d
ies
-
s
elec
ted
f
o
r
th
e
n
e
x
t
iter
atio
n
.
I
f
an
tib
o
d
ies
m
atch
an
tig
e
n
(
th
r
esh
o
ld
v
alu
e)
th
e
n
c
o
n
ce
n
tr
atio
n
i
n
cr
ea
s
es
‘
s
tim
u
latio
n
’
if
n
o
t
co
n
ce
n
tr
atio
n
d
ec
r
ea
s
es ‘
s
u
p
p
r
ess
io
n
’
.
d.
R
ep
ea
t
I
n
tr
o
d
u
ce
a
r
a
n
d
o
m
n
u
m
b
er
til
l a
n
tib
o
d
ies ar
e
g
e
n
er
ated
.
e.
E
n
d
Sto
p
p
in
g
cr
iter
ia
m
et,
i.e
.
,
a
n
tib
o
d
y
c
o
n
ce
n
tr
atio
n
will n
u
llif
y
an
tig
en
.
Fig
u
r
e
2
.
An
tig
e
n
n
u
llified
b
y
an
tib
o
d
y
3
.
2
.
F
ro
g
lea
pin
g
wit
h g
lo
ba
l g
ui
ded a
lg
o
rit
hm
T
h
is
s
tu
d
y
h
as
d
ev
el
o
p
ed
a
m
etah
eu
r
is
tic
m
eth
o
d
ca
l
led
f
r
o
g
lea
p
in
g
with
g
l
o
b
al
g
u
id
e
d
o
p
tim
izatio
n
(
FLG)
m
ea
n
t
f
o
r
a
ch
an
g
e
in
g
ain
co
ef
f
icien
ts
f
o
r
c
o
n
tr
o
l.
T
h
e
g
lo
b
al
b
est
f
r
o
g
will
b
e
r
ep
lace
d
b
y
wo
r
s
t
f
r
o
g
f
o
r
th
e
cr
ea
tio
n
o
f
FLG,
th
e
g
l
o
b
al
b
est
f
r
o
g
i
s
u
s
ed
in
p
lace
o
f
th
e
wo
r
s
t
f
r
o
g
.
Me
m
es
in
FLG
th
er
ef
o
r
e
s
p
r
ea
d
at
a
q
u
ick
e
r
r
ate
o
f
co
n
v
e
r
g
en
ce
.
T
h
e
o
p
tim
al
v
alu
es
o
f
th
e
s
ca
lin
g
f
ac
to
r
s
,
n
am
ely
a
n
d
o
f
th
e
c
o
n
tr
o
ller
,
ar
e
ascer
tain
ed
u
s
in
g
th
e
p
r
o
p
o
s
ed
FLG.
T
h
is
ap
p
r
o
ac
h
h
as
b
ee
n
v
er
i
f
ied
th
r
o
u
g
h
s
im
u
latio
n
s
an
d
co
n
tr
asted
wit
h
r
ea
l
-
wo
r
ld
B
L
DC
d
r
iv
e
im
p
l
em
en
tatio
n
s
.
A
s
war
m
o
f
f
r
o
g
s
h
as
b
ee
n
u
s
ed
in
FLG'
s
p
o
p
u
latio
n
-
b
ased
,
ev
o
l
v
in
g
m
etah
e
u
r
is
tic,
wh
ich
m
ax
im
izes
p
r
ey
[
2
3
]
–
[
2
5
]
.
I
ts
in
teg
r
atio
n
o
f
a
m
em
ep
lex
al
g
o
r
ith
m
b
ased
o
n
g
e
n
etic
ev
o
lu
tio
n
with
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
is
a
m
ajo
r
f
ac
to
r
in
its
s
u
cc
ess
.
T
h
e
PS
O
alg
o
r
ith
m
s
er
v
es
as
th
e
f
o
u
n
d
atio
n
f
o
r
th
is
m
eth
o
d
'
s
lo
ca
l
ex
p
lo
r
atio
n
,
an
d
th
e
i
d
ea
is
in
teg
r
atio
n
o
f
d
ata
f
r
o
m
co
n
c
u
r
r
e
n
t
lo
ca
l
s
ea
r
ch
es
o
r
ig
in
ates
f
r
o
m
th
e
s
h
u
f
f
lin
g
co
m
p
lex
e
v
o
lu
tio
n
m
eth
o
d
o
lo
g
y
.
Fro
g
p
o
p
u
latio
n
s
h
o
ws
a
clu
s
ter
o
f
p
o
ten
tial
s
o
lu
tio
n
s
in
FLG.
T
h
e
f
r
o
g
s
ets
wer
e
d
i
v
id
ed
in
to
s
ev
er
al
m
im
etics’
g
r
o
u
p
s
,
ea
ch
o
f
wh
ich
r
e
p
r
esen
ts
an
ex
clu
s
iv
e
tem
p
er
am
en
t.
T
h
e
f
r
o
g
s
ten
d
t
o
co
n
g
r
eg
ate
at
wh
at
ap
p
ea
r
s
t
o
b
e
th
e
b
est;
th
is
is
ju
s
t p
r
o
v
is
io
n
al
an
d
co
u
ld
b
e
a
lo
ca
l
o
p
tim
u
m
.
Ho
wev
e
r
,
s
o
m
e
m
em
etics
wer
e
tak
en
in
s
u
b
-
m
em
etics
to
av
o
id
en
t
r
ap
m
e
n
t
in
lo
ca
l
o
p
tim
a.
I
t
is
b
est
to
m
o
v
e
th
e
f
r
o
g
th
a
t
is
at
th
e
wo
r
s
t
p
lace
.
A
n
ew
g
r
o
u
p
k
n
o
w
n
as
m
em
eticist
s
h
as
b
ee
n
d
ev
elo
p
e
d
th
r
o
u
g
h
o
u
t
m
em
ep
lex
iter
atio
n
s
.
FLG
s
tep
s
in
v
o
lv
ed
ar
e.
a.
Po
p
u
latio
n
cr
ea
tio
n
: T
h
e
in
itia
l p
o
p
u
latio
n
(
f
r
o
g
s
)
is
d
ef
in
e
d
as
=
{
,
,
=
1
,
2
,
3
…
.
}
ℎ
ℎ
,
wh
er
e
is
th
e
p
o
s
itio
n
o
f
th
f
r
o
g
a
n
d
r
ep
r
esen
ts
its
f
itn
ess
.
T
h
e
f
itn
ess
v
alu
es
ar
e
ar
r
an
g
ed
i
n
d
ec
r
ea
s
in
g
o
r
d
er
.
b.
Sp
litt
in
g
th
e
m
em
etics:
Div
id
e
th
e
p
o
p
u
latio
n
in
to
m
em
eticist
s
{
1
,
2
,
3
…
.
.
}
,
ea
ch
c
o
n
tain
s
f
r
o
g
s
an
d
=
[
(
,
)
]
|
=
+
(
−
1
)
,
=
+
(
−
1
)
(
5
)
wh
er
e
=
1
,
2
,
3
…
.
.
.
c.
Su
b
m
em
etics
cr
ea
tio
n
:
T
h
e
s
tr
ateg
y
s
elec
tio
n
o
f
a
s
u
b
m
e
m
etics
(
f
o
r
k
f
r
o
g
s
)
in
e
v
er
y
m
em
eticist
s
h
as
lar
g
er
p
ar
am
ete
r
s
d
is
tr
ib
u
ted
in
g
o
o
d
lo
ca
tio
n
s
.
B
etter
p
o
s
itio
n
in
f
r
o
g
s
tr
ateg
y
h
as
g
r
ea
ter
weig
h
ts
allo
ca
ted
to
s
u
b
m
em
etics h
av
i
n
g
tr
ian
g
u
lar
p
r
o
b
a
b
ilit
y
d
is
tr
ib
u
tio
n
as
(
6
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
erfo
r
ma
n
ce
en
h
a
n
ce
me
n
t o
f
b
r
u
s
h
less
d
ir
ec
t c
u
r
r
en
t m
o
to
r
u
n
d
er d
iffer
en
t
…
(
B
a
b
u
A
s
h
o
k
)
6229
=
2
(
+
1
−
)
(
+
1
)
,
=
1
,
2
,
3
…
,
(
6
)
d.
Su
b
m
em
etics
ev
o
lu
tio
n
:
L
et
is
th
e
b
est
lo
ca
tio
n
an
d
is
th
e
wo
r
s
t
lo
ca
tio
n
in
s
u
b
m
em
e
tics
.
T
h
en
,
lo
ca
l
e
x
p
lo
r
atio
n
s
tar
ts
f
r
o
m
th
e
wo
r
s
t
f
r
o
g
to
leap
in
b
est
g
r
o
u
p
.
T
h
e
cu
r
r
en
t
p
o
s
itio
n
is
u
p
d
ated
b
y
o
n
e
leap
in
g
s
tep
as sh
o
wn
in
(
7
)
.
l
g
+
1
=
{
min
{
in
t
[
r
g
(
p
b
es
t
g
−
p
w
o
r
s
t
g
)
]
,
l
m
ax
}
,
if
p
b
es
t
g
≥
p
w
o
r
s
t
g
min
{
in
t
[
r
g
(
p
b
es
t
g
−
p
w
o
r
s
t
g
)
]
,
−
l
m
ax
}
,
if
p
b
es
t
g
<
p
w
o
r
s
t
g
(
7
)
wh
er
e
(
.
)
d
en
o
tes
th
e
i
n
teg
er
f
u
n
ctio
n
wh
ich
co
n
v
er
ts
th
e
s
p
e
cif
ied
v
alu
e
in
to
an
in
te
g
er
n
u
m
b
er
;
min
(
.
)
f
u
n
ctio
n
r
etu
r
n
s
th
e
item
w
ith
th
e
lo
west
v
alu
e
in
an
it
er
ab
le;
is
m
ax
im
u
m
leap
s
i
ze
;
-
r
an
d
o
m
n
u
m
b
er
an
d
-
ev
o
lu
ti
o
n
g
en
er
atio
n
.
Mo
r
eo
v
e
r
,
if
th
e
cu
r
r
e
n
t
lo
ca
tio
n
is
b
etter
th
a
n
wo
r
s
t
f
r
o
g
,
th
en
wo
r
s
t f
r
o
g
’
s
p
o
s
itio
n
is
m
o
d
if
ied
as
+
1
=
+
+
1
(
8
)
E
ls
e
,
th
e
wo
r
s
t f
r
o
g
p
o
s
itio
n
b
ec
o
m
es g
lo
b
al
o
p
tim
a
h
en
ce
+
1
=
{
{
[
(
−
)
]
,
}
,
≥
{
[
(
−
)
]
,
−
}
,
<
(
9
)
wh
er
e
is
b
est
p
o
s
itio
n
o
f
th
e
s
war
m
.
I
n
ca
s
e
if
th
e
wo
r
s
t
f
r
o
g
f
ails
to
im
p
r
o
v
e
its
p
o
s
itio
n
,
a
r
an
d
o
m
p
o
s
itio
n
is
au
to
m
atica
lly
g
en
e
r
ated
to
r
e
p
lace
it
+
1
=
1
+
[
(
1
−
2
)
]
(
1
0
)
wh
er
e
[
1
,
2
]
-
b
o
u
n
d
a
r
y
f
o
r
p
o
s
s
ib
le
lo
ca
tio
n
o
f
f
r
o
g
s
.
T
h
e
n
,
f
r
o
g
s
ar
e
s
o
r
ted
i
n
d
ec
r
ea
s
in
g
o
r
d
er
,
ascer
tain
ed
o
n
elig
ib
ilit
y
.
A
b
o
v
e
s
tep
s
ar
e
r
ep
ea
ted
till
s
u
b
m
em
etics
1
is
f
o
r
m
e
d
.
e.
T
h
e
r
em
ain
in
g
m
e
m
etics
h
av
e
b
ee
n
r
ea
r
r
a
n
g
ed
in
th
e
d
ec
r
ea
s
in
g
o
r
d
er
o
f
f
itn
ess
o
n
co
m
p
letio
n
o
f
th
is
lo
ca
l
in
v
esti
g
atio
n
.
T
h
is
is
k
n
o
wn
as
m
em
eticist
s
s
h
u
f
f
lin
g
.
Un
til
m
em
etic
ev
o
lu
tio
n
g
en
er
atio
n
2
i
s
r
ea
ch
ed
,
th
e
g
r
o
u
p
is
d
iv
i
d
ed
i
n
to
m
em
eticist
s
,
an
d
th
e
lo
ca
l
ex
p
lo
r
atio
n
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t r
ep
ea
ted
l
y
.
4.
RE
SU
L
T
S WI
T
H
DI
SCUS
S
I
O
N
Usi
n
g
MA
T
L
AB
/Si
m
u
lin
k
2
0
2
1
s
o
f
twar
e,
th
e
B
L
DC
d
r
iv
e
cir
c
u
its
wer
e
d
esig
n
e
d
f
o
r
th
e
v
er
if
icatio
n
o
f
t
h
e
s
p
ee
d
o
f
th
is
in
n
o
v
ativ
e
ap
p
r
o
ac
h
.
Usi
n
g
th
e
FLG
tech
n
iq
u
e,
th
e
ef
f
ec
tiv
en
ess
o
f
s
p
ee
d
co
n
tr
o
l
f
o
r
B
L
DC
d
r
iv
es
is
co
n
f
ir
m
ed
u
n
d
e
r
v
ar
i
o
u
s
test
s
ce
n
ar
io
s
.
T
h
e
AI
S
a
n
d
HB
O
ar
e
s
ee
n
as
two
f
u
r
th
er
s
o
p
h
is
ticated
co
n
tr
o
l
s
y
s
tem
s
with
th
e
p
er
f
o
r
m
an
ce
o
f
c
o
m
p
ar
is
o
n
with
FLG
co
n
tr
o
ller
.
All
th
e
th
r
ee
alg
o
r
ith
m
s
wer
e
u
tili
ze
d
u
n
til
th
e
r
esu
lts
wer
e
o
b
tain
ed
.
T
h
r
ee
d
is
tin
ct
in
s
tan
ce
s
h
av
e
b
ee
n
tak
en
in
to
co
n
s
id
er
atio
n
f
o
r
a
n
aly
s
is
o
f
t
h
e
p
er
f
o
r
m
an
ce
o
f
t
h
e
s
u
g
g
est
ed
co
n
tr
o
l
s
y
s
tem
:
i)
s
p
ee
d
r
e
s
p
o
n
s
e
f
o
r
c
o
n
s
tan
t
lo
ad
,
ii)
s
p
ee
d
r
esp
o
n
s
e
f
o
r
s
tep
ch
an
g
e
in
lo
ad
,
an
d
iii)
r
esp
o
n
s
e
f
o
r
v
a
r
iab
le
s
p
ee
d
.
I
n
o
p
tim
izatio
n
s
th
e
co
m
p
u
tatio
n
tim
e
o
f
alg
o
r
ith
m
is
p
r
o
p
o
r
tio
n
al
to
co
n
s
tr
ain
ts
,
it
p
r
o
ce
ed
s
iter
ativ
ely
s
e
le
ctin
g
a
n
ew
s
o
lu
tio
n
u
n
til p
r
ed
e
f
in
ed
h
alt
co
n
d
itio
n
is
m
et.
4
.
1
.
Sp
ee
d r
es
po
ns
e
f
o
r
co
ns
t
a
nt
lo
a
d
4
.
1
.
1
.
Sim
ula
t
io
n r
esu
lt
s
B
L
DC
m
o
to
r
s
ar
e
d
esig
n
ed
f
o
r
co
n
tin
u
o
u
s
d
u
ty
.
I
n
te
r
ac
tio
n
o
f
th
e
m
a
g
n
etic
f
o
r
ce
s
o
f
p
er
m
an
en
t
m
ag
n
et
(
r
o
to
r
)
with
elec
tr
o
m
a
g
n
etic
f
ield
o
f
ar
m
at
u
r
e
(
Stato
r
)
is
s
ee
n
in
th
e
p
r
o
d
u
ctio
n
o
f
to
r
q
u
e.
T
h
e
lo
a
d
to
r
q
u
e
d
u
r
in
g
a
lo
a
d
test
wh
i
ch
s
h
o
u
ld
b
e
id
en
tical
to
th
e
o
p
er
atin
g
to
r
q
u
e,
is
d
eter
m
in
e
d
b
y
th
e
d
u
t
y
cy
cle
(
d
)
wh
ic
h
th
e
co
n
tr
o
ller
g
en
e
r
ates
b
ased
o
n
th
e
s
p
ee
d
er
r
o
r
,
as
illu
s
tr
ated
in
th
e
b
lo
c
k
d
iag
r
am
Fig
u
r
e
1
b
elo
w.
Fo
r
d
if
f
er
e
n
t
o
p
tim
iz
atio
n
s
tr
ateg
ies,
Simu
latio
n
p
r
ed
icts
p
er
f
o
r
m
an
ce
f
o
r
d
if
f
er
en
t
o
p
tim
izatio
n
s
tr
ateg
ies
with
th
e
u
s
e
o
f
s
tatic
lo
ad
in
g
at
2
5
%,
5
0
%,
7
5
%,
an
d
1
0
0
%
o
f
f
u
ll
lo
ad
.
T
a
b
le
1
an
d
Fig
u
r
e
s
3
to
5
s
u
g
g
est
th
at
FLG
is
s
tr
o
n
g
r
o
b
u
s
tn
ess
,
im
p
r
o
v
ed
c
o
n
v
e
r
g
e
n
ce
s
p
ee
d
th
an
to
HB
O
an
d
AI
S.
T
h
e
alg
o
r
ith
m
s
h
o
u
ld
ch
o
o
s
e
“
d
”
as
th
e
i
d
ea
l
v
alu
e
c
o
n
s
id
er
in
g
in
cr
ea
s
in
g
th
e
s
witch
in
g
f
r
e
q
u
en
c
y
will
r
esu
lt
in
m
o
r
e
p
u
ls
e
wid
th
m
o
d
u
latio
n
(
PW
M)
lo
s
s
es
an
d
d
ec
r
ea
s
in
g
it
will
r
esu
lt
in
less
s
y
s
tem
b
an
d
wid
t
h
,
wh
ich
co
u
ld
h
ar
m
th
e
d
r
iv
e
s
y
s
tem
o
r
ca
u
s
e
s
to
p
p
ag
e
o
f
th
e
m
o
to
r
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
2
5
-
6
2
3
6
6230
T
ab
le
1
.
Per
f
o
r
m
an
ce
s
f
o
r
d
i
f
f
er
en
t lo
ad
in
g
@
2
0
0
0
r
p
m
M
e
t
h
o
d
P
e
r
f
o
r
ma
n
c
e
me
t
r
i
c
s
2
5
%
5
0
%
7
5
%
1
0
0
%
I
=
0
.
3
A
I
=
0
.
6
I
=
0
.
9
I
=
1
.
2
A
H
B
O
TH
D
1
5
.
9
4
1
6
.
2
1
8
.
2
2
2
0
.
7
1
80
1
4
0
2
1
0
2
6
0
0
.
6
0
.
8
0
.
9
1
PF
0
.
9
3
6
4
0
.
9
2
7
4
0
.
9
2
1
0
.
9
1
4
2
A
I
S
TH
D
1
3
.
2
8
1
4
.
3
1
5
.
7
1
7
.
2
5
40
1
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1
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0
1
6
0
0
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5
0
.
1
6
0
.
2
0
.
2
5
PF
0
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9
5
8
6
0
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9
5
1
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9
4
7
5
0
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9
3
6
1
F
LG
TH
D
7
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6
7
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2
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9
8
8
0
.
9
8
0
.
9
7
4
0
.
9
7
1
Fig
u
r
e
3
.
Sp
ee
d
r
esp
o
n
s
e
o
f
B
L
DC
m
o
to
r
@
1
0
0
% lo
ad
in
g
Fig
u
r
e
4
.
T
HD
co
m
p
ar
is
o
n
f
o
r
s
tatic
lo
ad
in
g
Fig
u
r
e
5
.
PF
co
m
p
ar
is
o
n
f
o
r
s
tatic
lo
ad
in
g
4
.
2
.
Respo
ns
e
f
o
r
s
t
ep
cha
ng
e
in
lo
a
d us
ing
o
ptim
iza
t
io
ns
As
s
h
o
wn
in
Fig
u
r
e
6
an
d
T
ab
le
2
,
FLG
p
er
f
o
r
m
s
b
etter
th
an
o
th
e
r
m
et
h
o
d
s
f
o
r
d
if
f
er
en
t
s
tep
ch
an
g
es
in
lo
ad
i
n
g
u
n
d
er
d
if
f
er
en
t
o
p
tim
izatio
n
s
.
I
n
d
u
ctio
n
o
r
elec
tr
o
m
ec
h
an
ical
en
e
r
g
y
co
n
v
e
r
s
io
n
is
th
e
s
am
e
o
p
er
atio
n
al
p
r
in
ci
p
le
th
at
u
n
d
er
p
in
s
all
elec
tr
ical
m
o
to
r
s
,
r
eg
ar
d
less
o
f
th
eir
v
ar
io
u
s
k
in
d
s
an
d
s
izes.
Fas
t
Fo
u
r
ier
tr
an
s
f
o
r
m
(
FFT
)
an
aly
s
is
in
MA
T
L
AB
is
u
s
ed
in
t
h
e
m
ea
s
u
r
em
e
n
t
o
f
T
HD
(
I
E
E
E
s
tan
d
a
r
d
519
-
2
0
1
4
r
ec
o
m
m
en
d
s
th
e
h
a
r
m
o
n
ics
lim
its
,
lo
wer
T
HD
i
m
p
lies
lo
w
E
MI
,
l
o
w
h
ea
tin
g
an
d
lo
w
ir
o
n
co
r
e
lo
s
s
in
m
o
to
r
s
)
,
d
o
n
e
in
ad
d
itio
n
to
PF
in
B
L
DC
m
o
to
r
s
,
co
n
s
id
er
in
g
th
e
m
e
n
ac
e
o
f
T
HD
f
o
r
th
e
o
v
er
h
ea
tin
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
erfo
r
ma
n
ce
en
h
a
n
ce
me
n
t o
f
b
r
u
s
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less
d
ir
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t c
u
r
r
en
t m
o
to
r
u
n
d
er d
iffer
en
t
…
(
B
a
b
u
A
s
h
o
k
)
6231
o
f
win
d
in
g
s
th
at
tr
ip
s
r
elay
s
.
Step
ch
an
g
es
in
lo
ad
in
g
,
s
u
ch
as
p
r
ess
in
g
,
cu
ttin
g
,
an
d
d
r
illi
n
g
,
ca
n
b
en
ef
it
f
r
o
m
th
e
s
tep
ch
an
g
e
i
n
lo
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9
3
6
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0
.
7
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2
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S
p
e
e
d
e
r
r
o
r
1
9
.
9
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7
9
.
5
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2
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F
LG
TH
D
0
7
.
6
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3
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1
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9
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1
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4
1
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6
PF
0
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9
8
8
0
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9
8
0
0
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9
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9
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9
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9
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0
1
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S
p
e
e
d
e
r
r
o
r
1
.
9
5
6
.
9
4
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9
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9
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9
1
5
.
9
15
18
5.
H
ARDWA
R
E
DE
SI
G
N
C
o
u
p
lin
g
a
m
o
t
o
r
with
s
m
all
v
alu
e
o
f
m
ec
h
an
ical
tim
e
co
n
s
tan
t
with
lar
g
e
in
er
tial
lo
ad
,
s
h
all
r
esu
lt
in
lo
s
in
g
th
e
m
er
it
o
f
h
av
in
g
a
s
m
all
m
o
m
en
t
o
f
in
er
tia.
W
h
er
ea
s
,
wh
en
th
e
m
o
to
r
with
a
lar
g
e
m
o
m
en
t
o
f
in
er
tia
if
u
s
ed
f
o
r
d
r
iv
in
g
lig
h
t
lo
ad
,
th
e
m
o
to
r
ef
f
icien
cy
will
b
e
r
ed
u
ce
d
.
T
h
e
m
o
s
t
im
p
o
r
tan
t
f
ea
tu
r
e
o
f
B
L
DC
m
o
to
r
is
its
ab
ilit
y
to
b
alan
ce
th
e
p
o
wer
co
n
v
e
r
ter
an
d
lo
ad
r
eq
u
i
r
em
en
ts
th
r
o
u
g
h
elec
tr
o
n
ic
co
m
m
u
tatio
n
.
An
ex
p
e
r
im
en
ta
l
p
r
o
t
o
ty
p
e
o
f
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
s
h
o
wn
in
Fig
u
r
e
8
.
A
b
r
id
g
eless
b
u
ck
b
o
o
s
t
co
n
v
er
te
r
in
ten
d
ed
f
o
r
o
p
er
atio
n
in
d
is
co
n
tin
u
o
u
s
co
n
d
u
ctio
n
m
o
d
e
(
DC
M
)
eith
er
in
d
u
cto
r
cu
r
r
en
t
o
r
ca
p
ac
ito
r
v
o
ltag
e
is
d
is
co
n
tin
u
o
u
s
wh
ich
is
a
p
r
er
e
q
u
is
ite
f
o
r
th
e
d
esig
n
[
1
7
]
o
f
d
r
iv
e
cir
cu
its
an
d
in
a
d
d
itio
n
to
th
at
to
av
o
id
g
ea
r
r
ed
u
ce
r
,
c
o
u
p
lin
g
,
an
d
p
u
lley
,
p
o
wer
c
o
n
v
er
ter
is
ac
tiv
ated
b
y
co
n
tr
o
ll
er
.
a.
Du
ty
r
atio
ca
lcu
latio
n
T
h
e
m
o
to
r
p
o
wer
r
atin
g
is
7
5
0
W
an
d
th
e
co
n
v
er
ter
p
o
wer
is
850
W
.
L
et
th
e
s
u
p
p
ly
v
o
ltag
e
be
220
V
r
o
o
t
m
ea
n
s
q
u
a
r
e
(
R
MS
)
v
alu
e
,
th
en
in
p
u
t v
o
ltag
e
is
=
2
√
2
=
2
√
2
×
220
=
198
(
1
1
)
Vol
ta
ge
r
a
tio
,
=
+
(
1
2
)
L
et
th
e
v
o
ltag
e
lim
its
ac
r
o
s
s
d
c
lin
k
co
n
tr
o
l b
e
(
)
,
=
50
,
(
)
=
200
a
nd
(
)
=
100
an
d
th
e
c
o
r
r
esp
o
n
d
in
g
d
u
ty
r
atio
=
0
.
2
0
1
7
an
d
=
0
.
5
0
2
4
r
esp
ec
tiv
ely
.
b.
I
n
p
u
t
in
d
u
cto
r
s
(
1
an
d
2
)
–
d
esig
n
=
(
1
−
)
2
2
(
1
3
)
is
ca
lcu
lated
at
th
e
v
o
ltag
e
is
(
)
=
50
th
e
co
r
r
esp
o
n
d
in
g
p
o
wer
is
1
9
0
watts
=
(
)
2
×
(
1
−
)
2
2
=
50
2
1
90
×
(
1
−
0
.
2016
)
2
2
20000
=
209
.
69
µH
(
1
4
)
1
is
tak
en
as
10
,
Hen
ce
1
=
2
=
25
µ
(
1
5
)
T
h
is
s
ize,
weig
h
t a
n
d
co
s
t o
f
th
e
b
u
c
k
b
o
o
s
t c
o
n
v
er
te
r
(
BBC
)
is
r
ed
u
ce
d
.
c.
DC
lin
k
ca
p
ac
ito
r
,
–
d
esig
n
=
2
∆
=
(
)
⁄
2
∆
=
850
100
⁄
2
×
314
×
0
.
03
×
100
(
1
6
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
2
5
-
6
2
3
6
6234
Ass
u
m
in
g
p
er
m
is
s
ib
le
v
o
ltag
e
r
ip
p
le
ac
r
o
s
s
th
e
d
c
lin
k
v
o
lta
g
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o
f
3%
=
∆
=
4511
.
67
µF
(
1
7
)
Hen
ce
th
e
n
ea
r
est v
alu
e
is
5
0
0
0
µF
.
d.
Fil
ter
cir
cu
it
A
s
ec
o
n
d
o
r
d
e
r
lo
w
p
ass
in
d
u
ctan
ce
ca
p
ac
itan
ce
(
LC
)
f
ilt
er
is
ap
p
lied
ac
r
o
s
s
th
e
s
u
p
p
ly
f
o
r
th
e
elim
in
atio
n
o
f
n
eg
ativ
e
a
n
d
ze
r
o
s
eq
u
en
ce
co
m
p
o
n
en
ts
as we
ll a
s
h
ig
h
er
o
r
d
er
h
ar
m
o
n
ics.
=
(
Ф
)
=
850
220
⁄
314
√
2
220
(
1
)
(
1
8
)
=
690
.
32
=
+
(
1
9
)
L
et
L
s
=
4%
o
f
b
ase
im
p
e
d
an
ce
=
1
4π
2
fc
2
C
f
+
0
.
04
(
1
ω
)
(
Vs
2
P
o
)
(
2
0
)
=
1
4π
2
×
2000
2
×
690
.
32
×
10
−
2
+
0
.
04
314
(
220
2
850
)
=
0
.
00917347
032
+
0
.
0072536530
5
=
0
.
0164
=
16
(
2
1
)
5
.
1
.
E
x
perim
ent
a
l set
up
Har
d
war
e
r
esu
lts
d
etailed
in
T
ab
le
4
is
co
m
p
ar
ed
with
s
im
u
latio
n
r
esu
lts
v
i
d
e
T
a
b
le
5
.
Ver
if
icatio
n
o
f
th
e
o
u
tco
m
es
o
f
th
e
s
im
u
latio
n
f
o
r
t
h
e
m
o
to
r
p
ar
a
m
eter
s
is
m
en
tio
n
ed
in
T
a
b
le
6
.
HB
O
s
ee
n
h
av
in
g
len
g
th
y
s
ea
r
ch
d
u
r
atio
n
co
u
l
d
g
et
s
tu
ck
in
lo
ad
o
p
tim
a
d
etails
ar
e
s
ee
n
in
b
o
th
s
im
u
l
atio
n
an
d
h
a
r
d
war
e.
R
ec
o
g
n
itio
n
o
f
alien
th
in
g
s
h
elp
ed
th
e
im
m
u
n
e
s
y
s
tem
,
s
o
m
etim
es
r
ef
er
r
e
d
to
as
“
th
e
s
ec
o
n
d
b
r
ain
”
in
th
e
cr
ea
tio
n
o
f
s
elf
/n
o
n
-
s
elf
,
n
o
n
-
lin
ea
r
n
etwo
r
k
s
f
r
o
m
v
ar
io
u
s
an
tib
o
d
ies.
T
h
is
ca
n
u
tili
ze
th
e
im
m
u
n
o
l
o
g
ical
law
f
o
r
c
o
n
tr
o
l
an
d
er
ad
icatio
n
o
f
an
tig
en
.
An
y
d
is
r
u
p
tio
n
i
s
also
elim
in
ated
b
y
th
e
s
o
f
tw
ar
e
s
o
lu
tio
n
,
wh
ich
u
s
es
d
ig
ital
f
ilter
in
g
,
in
s
tr
u
cti
o
n
r
ed
u
n
d
a
n
cy
,
s
o
f
twar
e
d
ela
y
/r
eset
an
d
s
m
o
o
t
h
in
g
r
ea
ct
o
r
/f
ilter
in
h
ar
d
war
e
f
o
r
th
e
r
eg
u
latio
n
o
f
B
L
DC
d
r
iv
es.
T
ab
le
6
.
B
L
DC
m
o
to
r
p
a
r
am
e
ter
s
(
f
o
r
Har
d
wa
r
e)
P
a
r
a
me
t
e
r
s
V
a
l
u
e
N
u
mb
e
r
o
f
p
o
l
e
s
4
P
o
w
e
r
7
5
0
W
a
t
t
s
V
o
l
t
a
g
e
4
8
V
o
l
t
s
C
u
r
r
e
n
t
1
3
.
5
A
mp
S
p
e
e
d
1
,
5
0
0
r
p
m
To
r
q
u
e
18
Nm
P
e
a
k
t
o
r
q
u
e
2
4
N
m
To
r
q
u
e
c
o
n
st
a
n
t
,
K
T
0
.
8
6
R
o
t
o
r
i
n
e
r
t
i
a
2
.
5
K
g
6.
CO
NCLU
SI
O
N
T
h
e
co
n
tr
o
ller
o
p
tim
izatio
n
p
r
o
ce
s
s
an
d
c
o
n
tr
o
ller
d
esig
n
ar
e
cr
itical
to
th
e
tr
ac
k
in
g
a
n
d
c
o
n
tr
o
llin
g
p
er
f
o
r
m
an
ce
o
f
B
L
DC
m
o
to
r
s
.
Hen
ce
p
r
o
p
o
r
tio
n
al
an
d
in
teg
r
al
g
ain
v
al
u
es
ar
e
p
r
ed
eter
m
in
e
d
f
o
r
co
n
v
en
tio
n
al
f
ix
e
d
g
ain
m
eth
o
d
s
,
in
d
ep
e
n
d
en
t
o
f
test
co
n
d
itio
n
s
,
g
o
o
d
r
esu
lts
ca
n
n
o
t
b
e
o
b
tain
e
d
f
o
r
all
o
p
er
atio
n
al
m
o
d
es.
Ad
d
itio
n
al
ly
,
th
e
o
u
td
ated
m
eth
o
d
d
o
es
n
o
t
g
u
ar
an
tee
wo
r
k
in
g
f
o
r
o
n
e
o
r
m
o
r
e
p
ar
am
eter
in
d
icato
r
s
s
u
ch
as
p
ea
k
o
v
e
r
s
h
o
o
t,
s
ettlin
g
tim
e
,
p
o
wer
co
n
s
u
m
p
tio
n
,
s
tead
y
-
s
tate
ac
cu
r
a
cy
.
T
h
e
d
r
i
v
e
cir
cu
it
r
eq
u
ir
es
th
e
em
p
lo
y
m
en
t
o
f
m
an
y
m
eta
h
eu
r
is
tic
o
p
tim
izat
io
n
m
eth
o
d
s
,
in
clu
d
in
g
HB
O,
AI
S
,
an
d
FLG,
f
o
r
th
e
attain
m
en
t
o
f
t
h
e
ex
ac
t
s
p
ee
d
co
n
tr
o
l.
E
f
f
ec
tiv
e
f
in
e
tu
n
in
g
f
o
r
th
e
s
p
ee
d
co
n
tr
o
l
was
tak
en
as
th
e
o
b
jectiv
e
f
o
r
th
e
ac
h
ie
v
em
en
t
o
f
g
o
o
d
p
er
f
o
r
m
an
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.