I
nte
rna
t
io
na
l J
o
urna
l o
f
Rec
o
nfig
ura
ble a
nd
E
m
be
dd
e
d Sy
s
t
e
m
s
(
I
J
R
E
S)
Vo
l.
9
,
No
.
1
,
Ma
r
ch
20
20
,
p
p
.
8
3
~9
2
I
SS
N
: 2
0
8
9
-
4864
,
DOI
: 1
0
.
1
1
5
9
1
/i
j
r
es.
v
9
.
i1
.
p
p
8
3
-
92
83
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
r
es.ia
esco
r
e.
co
m
Applica
tion
o
f
o
pti
m
a
l
a
rtif
i
cia
l int
ellig
ence bas
ed
tu
ned
co
ntrollers
t
o
a
cl
a
ss
of e
m
bedded
no
nlinea
r
po
w
er
s
y
ste
m
M
a
g
dy
A.
S.
Abo
elela
F
a
c
u
lt
y
o
f
En
g
in
e
e
rin
g
,
Ca
iro
Un
iv
e
rsit
y
,
Eg
y
p
t
E
m
ail:
ab
o
elela
m
a
g
d
y
@
s
ta
f
f
.
cu
.
ed
u
.
eg
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ma
y
1
9
,
2
0
1
9
R
ev
i
s
ed
Oct
2
0
,
2
0
1
9
A
cc
ep
ted
No
v
1
5
,
2
0
1
9
T
h
is
p
a
p
e
r
stu
d
ies
t
h
e
im
p
lem
e
n
tatio
n
o
f
th
e
Ba
t
In
s
p
ired
A
lg
o
ri
th
m
(BIA)
a
s
a
n
o
p
ti
m
iza
ti
o
n
tec
h
n
i
q
u
e
to
f
in
d
t
h
e
o
p
ti
m
a
l
p
a
ra
m
e
ters
o
f
t
w
o
c
las
se
s
o
f
c
o
n
tro
ll
e
rs.
T
h
e
f
irst
is
th
e
c
las
s
ica
l
P
r
o
p
o
rti
o
n
a
l
-
In
teg
ra
l
-
De
riv
a
t
iv
e
(P
ID).
T
h
e
se
c
o
n
d
is
th
e
h
y
b
rid
f
ra
c
ti
o
n
a
l
o
r
d
e
r
a
n
d
Bra
i
n
Em
o
ti
o
n
a
l
In
telli
g
e
n
t
c
o
n
tro
ll
e
r.
T
h
e
tw
o
c
o
n
tro
ll
e
rs
h
a
v
e
b
e
e
n
im
p
le
m
e
n
ted
,
se
p
a
ra
tel
y
,
f
o
r
th
e
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
a
sin
g
le
a
re
a
e
le
c
tri
c
p
o
w
e
r
s
y
ste
m
w
it
h
th
re
e
p
h
y
sic
a
l
im
b
e
d
d
e
d
n
o
n
li
n
e
a
rit
ies
.
T
h
e
f
irst
n
o
n
li
n
e
a
rit
y
re
p
re
se
n
ts
th
e
g
e
n
e
ra
ti
o
n
’s
ra
te
c
o
n
stra
in
t
(
G
RC).
T
h
e
se
c
o
n
d
is
o
w
in
g
to
th
e
g
o
v
e
rn
o
r
d
e
a
d
b
a
n
d
(G
DB).
T
h
e
las
t
is
d
u
e
to
t
h
e
ti
m
e
d
e
la
y
im
p
o
se
d
b
y
th
e
g
o
v
e
rn
o
r
-
tu
rb
i
n
e
li
n
k
,
th
e
t
h
e
rm
o
d
y
n
a
m
i
c
p
ro
c
e
ss
,
a
n
d
th
e
c
o
m
m
u
n
ica
ti
o
n
c
h
a
n
n
e
ls.
T
h
e
se
n
o
n
li
n
e
a
rit
ies
h
a
v
e
b
e
e
n
e
m
b
e
d
d
e
d
in
th
e
si
m
u
latio
n
m
o
d
e
l
o
f
th
e
sy
ste
m
u
n
d
e
r
stu
d
y
.
M
a
tl
a
b
/S
im
u
li
n
k
so
f
t
w
a
re
h
a
s
b
e
e
n
a
p
p
li
e
d
t
o
o
b
tai
n
th
e
re
su
lt
s
o
f
a
p
p
ly
in
g
th
e
tw
o
c
las
se
s
o
f
c
o
n
tro
ll
e
rs
w
h
ich
h
a
v
e
b
e
e
n
,
o
p
ti
m
a
ll
y
,
tu
n
e
d
u
si
n
g
th
e
BIA
.
T
h
e
In
teg
ra
l
o
f
S
q
u
a
re
Err
o
r
(I
S
E)
c
rit
e
rio
n
h
a
s
b
e
e
n
se
lec
ted
as
a
n
e
le
m
e
n
t
o
f
th
e
o
b
jec
ti
v
e
f
u
n
c
ti
o
n
a
l
o
n
g
w
it
h
th
e
p
e
rc
e
n
tag
e
o
v
e
rsh
o
o
t
a
n
d
se
tt
li
n
g
ti
m
e
f
o
r
th
e
o
p
ti
m
u
m
tu
n
in
g
tec
h
n
iq
u
e
o
f
th
e
tw
o
c
o
n
tro
ll
e
rs.
T
h
e
sim
u
latio
n
re
su
lt
s
sh
o
w
th
a
t
wh
e
n
u
si
n
g
th
e
h
y
b
rid
f
ra
c
ti
o
n
a
l
o
rd
e
r
a
n
d
Bra
in
Em
o
ti
o
n
a
l
In
telli
g
e
n
t
c
o
n
tro
ll
e
r,
it
g
iv
e
s
b
e
tt
e
r
re
sp
o
n
se
a
n
d
p
e
rf
o
rm
a
n
c
e
in
d
ice
s
th
a
n
th
e
c
o
n
v
e
n
ti
o
n
a
l
P
r
o
p
o
rti
o
n
a
l
-
In
teg
ra
l
-
De
riv
a
ti
v
e
(P
ID) co
n
tro
l
l
e
rs
.
K
ey
w
o
r
d
s
:
B
r
ain
e
m
o
tio
n
al
lear
n
in
g
b
ase
d
in
telli
g
e
n
t c
o
n
tr
o
ller
s
Fra
ctio
n
o
r
d
er
p
r
o
p
o
r
tio
n
al
-
in
te
g
r
al
-
d
er
i
v
ativ
e
co
n
tr
o
ller
s
Ma
tlab
/
s
i
m
u
l
in
k
No
n
li
n
ea
r
s
y
s
te
m
s
P
r
o
p
o
r
tio
n
al
-
in
te
g
r
al
-
d
er
iv
ati
v
e
co
n
tr
o
ller
s
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ma
g
d
y
A
.
S.
A
b
o
elela
,
Facu
lt
y
o
f
E
n
g
i
n
ee
r
i
n
g
,
C
air
o
Un
i
v
er
s
it
y
,
Giza
Go
v
er
n
o
r
ate
1
2
6
1
3
,
E
g
y
p
t
.
E
m
ail:
ab
o
elela
m
a
g
d
y
@
s
ta
f
f
.
cu
.
ed
u
.
eg
1.
I
NT
RO
D
UCT
I
O
N
Du
e
to
u
n
r
e
m
it
tin
g
d
ev
elo
p
m
en
t
o
f
s
ize
a
n
d
co
m
p
lex
it
y
o
f
elec
tr
ical
p
o
w
er
s
y
s
te
m
,
t
h
e
p
r
o
b
lem
o
f
m
ai
n
tai
n
in
g
t
h
e
p
o
w
er
an
d
f
r
eq
u
en
c
y
f
r
ee
f
r
o
m
o
s
cillat
io
n
s
h
as
b
ec
o
m
e
r
ap
id
l
y
cr
u
cial
b
ec
au
s
e
o
f
ir
r
eg
u
lar
lo
ad
v
ar
iatio
n
s
a
n
d
i
m
b
ed
d
ed
s
y
s
te
m
n
o
n
lin
ea
r
it
ies
[
1
]
.
T
h
ese
u
n
e
x
p
ec
ted
lo
ad
v
ar
iatio
n
s
r
es
u
lt
i
n
th
e
m
i
s
m
a
tch
o
f
g
e
n
er
ated
p
o
w
er
a
n
d
lo
ad
d
e
m
a
n
d
f
o
r
co
n
s
u
m
p
tio
n
.
T
h
i
s
w
il
l
f
i
n
all
y
d
i
s
tr
ess
e
s
t
h
e
q
u
a
lit
y
an
d
r
eliab
ilit
y
o
f
elec
tr
ic
p
o
w
er
s
u
p
p
l
y
.
T
h
is
ca
n
b
e
ac
h
ie
v
e
d
b
y
t
h
e
lo
ad
f
r
eq
u
e
n
c
y
co
n
tr
o
l (
L
F
C
)
id
e
o
lo
g
ie
s
.
No
w
ad
a
y
s
,
a
lo
t
o
f
w
o
r
k
i
s
g
o
in
g
o
n
to
m
ak
e
th
e
s
y
s
te
m
s
in
telli
g
e
n
t
s
o
th
e
s
y
s
te
m
s
ca
n
s
u
cc
e
s
s
f
u
ll
y
s
er
v
e
th
e
b
en
e
f
its
o
f
m
a
n
k
i
n
d
[
2
-
3
]
.
T
h
e
m
ain
g
o
al
o
f
o
p
er
atio
n
o
f
th
e
L
FC
i
n
th
e
s
i
n
g
le
ar
ea
o
r
m
u
lti
ar
ea
p
o
w
er
s
y
s
te
m
s
is
to
m
ai
n
tai
n
th
e
f
r
eq
u
e
n
c
y
w
it
h
in
th
e
p
er
m
is
s
ib
le
l
i
m
i
ts
.
I
n
t
h
e
p
ast
f
e
w
y
ea
r
s
,
e
n
o
r
m
o
u
s
i
m
p
r
o
v
e
m
e
n
t
h
as
b
ee
n
m
ad
e
i
n
th
e
ar
ea
o
f
lo
ad
f
r
eq
u
en
c
y
c
o
n
tr
o
l
o
f
a
s
i
n
g
le
ar
ea
p
o
w
er
s
y
s
te
m
an
d
m
u
lti
ar
ea
as
well
[
4
-
5
]
.
Desig
n
i
n
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t,
Vo
l.
9
,
No
.
1
,
Ma
r
ch
2
0
2
0
:
8
3
–
92
84
th
e
L
FC
w
it
h
t
h
e
h
elp
o
f
P
I
D
co
n
tr
o
ller
s
m
a
k
es
it
p
r
o
m
i
n
e
n
t
a
n
d
tr
u
s
t
w
o
r
t
h
y
,
b
u
t
th
e
m
ain
c
h
alle
n
g
e
i
s
to
d
ec
id
e
th
e
p
ar
am
eter
s
o
f
co
n
tr
o
ller
s
[
6
-
7
]
.
T
o
h
av
e
b
etter
b
eh
av
io
r
f
r
o
m
a
n
y
co
n
tr
o
ller
,
its
p
a
r
a
m
eter
s
s
h
o
u
ld
b
e
o
p
ti
m
a
ll
y
t
u
n
ed
.
T
h
e
co
n
v
e
n
tio
n
a
l
m
et
h
o
d
s
f
a
ce
s
o
m
e
d
if
f
ic
u
ltie
s
to
ac
h
ie
v
e
t
h
i
s
p
u
r
p
o
s
e,
s
u
c
h
as
co
m
p
lex
m
ath
e
m
at
ical
eq
u
atio
n
s
f
o
r
lar
g
e
s
y
s
te
m
s
.
Sev
er
al
ap
p
r
o
ac
h
es
s
u
c
h
as
o
p
ti
m
al,
Ge
n
etic
A
l
g
o
r
ith
m
(
G
A
)
,
P
ar
ticle
S
w
ar
m
Op
ti
m
izatio
n
(
P
SO)
,
B
ac
ter
ial
Fo
r
ag
in
g
Op
ti
m
izatio
n
(
B
FO)
,
etc.
,
f
o
r
th
e
d
esig
n
an
d
o
p
ti
m
izatio
n
o
f
t
h
e
L
F
C
s
y
s
te
m
,
h
av
e
b
ee
n
r
ep
o
r
ted
in
th
e
li
ter
atu
r
e
[
8
]
.
Mo
d
e
r
n
o
p
tim
al
co
n
tr
o
l
co
n
ce
p
t
f
o
r
A
G
C
d
esig
n
s
o
f
in
ter
co
n
n
ec
ted
p
o
w
er
s
y
s
te
m
w
a
s
f
ir
s
tl
y
p
r
esen
ted
b
y
[
9
]
.
Gen
etic
al
g
o
r
ith
m
s
(
G
A
s
)
h
a
v
e
b
ee
n
e
x
ten
s
i
v
el
y
co
n
s
id
er
ed
f
o
r
th
e
d
esig
n
o
f
Au
to
m
a
tic
Gen
er
at
io
n
C
o
n
tr
o
l
(
A
G
C
)
.
Op
ti
m
al
P
I
D
an
d
f
r
ac
tio
n
al
-
o
r
d
er
PID
co
n
tr
o
l
p
ar
a
m
eter
s
h
a
v
e
b
ee
n
ap
p
lied
b
y
th
e
G
A
s
tec
h
n
iq
u
e
f
o
r
i
n
ter
co
n
n
ec
ted
,
eq
u
al
n
o
n
-
r
eh
ea
t
an
d
r
e
h
ea
t
t
y
p
e
t
w
o
g
e
n
er
atin
g
ar
ea
s
[
1
0
]
.
I
n
[
1
1
]
,
th
e
p
ar
a
m
e
ter
s
o
f
P
I
D
s
lid
i
n
g
-
m
o
d
e
u
s
ed
i
n
L
F
C
o
f
m
u
l
ti
-
ar
ea
p
o
w
er
s
y
s
te
m
s
w
it
h
n
o
n
li
n
ea
r
ele
m
en
ts
ar
e
o
p
ti
m
ized
b
y
G
A
.
I
n
[
1
2
]
,
GA
is
u
s
ed
to
co
m
p
u
te
th
e
d
ec
en
tr
alize
d
co
n
tr
o
l
p
ar
am
eter
s
to
r
ea
ch
to
an
o
p
ti
m
u
m
o
p
er
atin
g
p
o
in
t
f
o
r
a
r
ea
lis
tic
s
y
s
te
m
co
m
p
r
i
s
in
g
g
e
n
er
atio
n
r
ate
co
n
s
tr
ain
t
(
GR
C
)
,
d
ea
d
b
an
d
,
an
d
ti
m
e
d
ela
y
s
.
A
GC
u
s
i
n
g
i
n
teg
r
al
co
n
tr
o
ller
an
d
P
I
c
o
n
tr
o
ller
b
ased
o
n
P
SO
is
r
ep
o
r
ted
in
[
1
3
]
.
I
n
[
1
4
]
,
th
e
p
ar
am
eter
s
o
f
P
I
co
n
tr
o
ller
ar
e
ev
alu
ated
u
s
i
n
g
P
SO [
1
3
]
.
I
n
[
1
5
]
,
a
r
o
b
u
s
t P
I
D
co
n
tr
o
ller
b
ased
o
n
I
C
A
is
u
s
e
d
f
o
r
L
FC
ap
p
licatio
n
.
T
h
e
au
th
o
r
s
o
f
[
1
6
-
1
8
]
h
av
e
p
r
o
p
o
s
ed
b
ac
ter
ial
f
o
r
ag
in
g
o
p
tim
izatio
n
al
g
o
r
ith
m
(
B
FO
A
)
f
o
r
d
esig
n
in
g
P
I
an
d
P
I
D
-
b
ased
lo
ad
f
r
eq
u
en
c
y
co
n
tr
o
ller
s
.
Fo
r
a
s
in
g
le
ar
ea
p
o
w
er
s
y
s
te
m
,
t
h
e
p
r
o
b
lem
o
f
L
F
C
an
d
A
G
C
h
a
s
b
ee
n
tr
ea
ted
b
y
s
e
v
er
al
r
esear
ch
er
s
.
T
h
is
in
cl
u
d
es
a
v
ar
iet
y
o
f
tec
h
n
iq
u
es
s
u
c
h
as
g
r
av
ita
tio
n
al
s
ea
r
c
h
alg
o
r
it
h
m
[
1
9
]
,
th
e
m
o
d
if
ied
p
ar
ticle
s
w
ar
m
o
p
ti
m
izatio
n
[
2
0
]
,
th
e
ap
p
licatio
n
o
f
a
r
tif
icial
n
e
u
r
al
n
et
w
o
r
k
[
2
0
]
,
o
p
ti
m
al
co
n
tr
o
l
d
esig
n
[
2
1
]
,
f
u
zz
y
lo
g
ic
[
2
2
-
2
3
]
,
p
r
o
p
o
r
tio
n
al
-
in
te
g
r
al
-
o
b
s
er
v
er
tech
n
iq
u
es
[
2
4
]
,
an
d
L
QR
an
d
L
e
g
e
n
d
r
e
w
a
v
elet
f
u
n
ct
io
n
[
2
5
]
.
Fin
all
y
,
th
e
a
u
to
m
atic
g
e
n
er
atio
n
c
o
n
tr
o
l
o
f
s
i
n
g
le
ar
ea
p
o
w
er
s
y
s
te
m
w
i
th
m
u
lti
-
s
o
u
r
ce
p
o
w
er
g
e
n
er
atio
n
h
as
b
ee
n
s
tu
d
ied
i
n
[
2
6
]
.
A
ll
th
e
s
e
r
esear
ch
es
d
ea
l
o
n
l
y
w
it
h
th
e
ca
s
e
w
h
er
e
n
o
n
o
n
li
n
ea
r
itie
s
ex
i
s
t i
n
th
e
co
n
t
r
o
l lo
o
p
s
.
T
o
in
clu
d
e
th
e
n
o
n
li
n
ea
r
ities
p
r
ev
io
u
s
l
y
m
en
tio
n
ed
i
n
th
is
ar
ticle,
w
e
h
av
e
s
elec
ted
a
s
p
ec
ial
ca
teg
o
r
y
o
f
co
n
tr
o
ller
s
w
h
ic
h
ar
e
th
e
Fra
ctio
n
al
Or
d
er
P
I
D
c
o
n
tr
o
ller
s
(
FOP
I
D)
[
2
7
-
3
3
]
an
d
B
r
ain
E
m
o
tio
n
al
L
ea
r
n
i
n
g
b
ased
in
tel
lig
e
n
t c
o
n
tr
o
ller
s
(
B
E
L
B
I
C
)
[
3
4
-
35]
.
2.
CL
AS
SI
CA
L
P
I
D
CO
N
T
R
O
L
L
E
R
T
h
e
P
I
D
co
n
tr
o
ller
is
co
n
s
id
er
ed
to
b
e
an
i
m
p
o
r
ta
n
t
co
m
p
o
n
en
t
i
n
in
d
u
s
tr
ial
co
n
tr
o
l
s
y
s
te
m
s
.
T
h
is
i
s
b
ec
au
s
e
o
f
i
ts
ca
p
ab
ilit
y
o
f
r
ed
u
cin
g
t
h
e
s
tead
y
s
tate
er
r
o
r
an
d
en
h
an
c
in
g
t
h
e
d
y
n
a
m
ic
r
esp
o
n
s
e
an
d
o
th
er
s
tatic
ch
ar
ac
ter
i
s
t
ics.
T
h
e
P
I
D
co
n
tr
o
ller
is
ex
p
r
ess
ed
,
m
at
h
e
m
atica
ll
y
,
b
y
t
h
e
n
e
x
t e
q
u
at
io
n
[
3
6
]
:
(
)
=
p
e
(
t
)
+
i
∫
e
(
τ
)
d
τ
t
0
+
d
d
e
(
t
)
dt
(
1
)
W
h
er
e
e
(
t
)
is
th
e
s
y
s
te
m
er
r
o
r
,
p
i
s
th
e
p
r
o
p
o
r
tio
n
al
g
ain
,
i
is
th
e
in
teg
r
al
g
ai
n
,
d
is
th
e
d
er
iv
ativ
e
g
ai
n
an
d
(
)
is
th
e
o
u
tp
u
t o
f
t
h
e
co
n
tr
o
ller
.
3.
F
RACTI
O
N
AL
O
RD
E
R
C
O
NT
RO
L
L
E
R
T
h
e
f
r
ac
tio
n
al
ca
lc
u
l
u
s
i
s
i
m
p
le
m
en
ted
to
o
b
tain
th
e
s
o
lu
t
io
n
f
o
r
m
an
y
s
cien
tific
an
d
e
n
g
i
n
ee
r
i
n
g
ap
p
licatio
n
s
.
I
n
la
s
t
te
n
y
ea
r
s
it
is
b
ein
g
ac
k
n
o
w
led
g
ed
b
y
it
s
ab
ilit
y
to
y
ield
a
b
etter
m
o
d
e
lin
g
an
d
co
n
tr
o
l
in
m
an
y
d
y
n
a
m
ical
s
y
s
te
m
s
[
2
8
]
.
T
h
e
f
r
ac
tio
n
al
o
r
d
er
co
n
tr
o
ller
ex
p
lo
r
es
g
o
o
d
r
o
b
u
s
tn
e
s
s
a
n
d
g
i
v
e
s
b
etter
b
eh
av
io
r
d
u
e
to
tu
n
i
n
g
f
i
v
e
o
r
f
o
u
r
p
ar
am
e
ter
s
(
,
.
.
.
)
in
s
tead
o
f
th
r
ee
o
r
t
w
o
p
ar
am
eter
s
(
,
.
)
in
clas
s
ical
P
I
D
co
n
tr
o
ller
s
[
2
9
]
.
T
h
e
f
r
ac
tio
n
al
co
n
tr
o
ller
f
o
r
m
is
ex
p
r
es
s
ed
,
m
at
h
e
m
atica
l
l
y
,
as
f
o
llo
w
s
[
3
0
]
:
(
)
=
∗
(
)
+
∗
(
)
∗
−
∗
(
)
∗
(
2
)
W
h
er
e
E
(
s
)
d
en
o
tes
t
h
e
er
r
o
r
s
ig
n
al,
U
(
s
)
is
co
n
tr
o
l
s
i
g
n
al,
,
an
d
ar
e
p
r
o
p
o
r
tio
n
al,
in
t
eg
r
al
an
d
d
er
iv
ativ
e
co
e
f
f
icien
t
s
r
esp
e
ctiv
el
y
,
λ
an
d
δ
ar
e
p
o
w
er
o
f
’
s
’
in
i
n
te
g
r
al
ac
tio
n
an
d
d
er
iv
ati
v
e
ac
tio
n
r
esp
ec
tiv
el
y
.
On
e
o
f
t
h
e
m
et
h
o
d
s
to
r
ea
lize
th
e
f
r
ac
tio
n
al
o
r
d
er
co
n
tr
o
ller
s
i
s
k
n
o
w
n
a
s
t
h
e
O
u
s
ta
lo
u
p
m
et
h
o
d
[
3
1
]
.
T
h
is
m
et
h
o
d
r
elies o
n
th
e
ap
p
r
o
x
i
m
a
tio
n
o
f
a
f
u
n
ct
io
n
as
g
i
v
en
b
y
(
3
)
an
d
(
4
)
.
So
m
e
co
n
ti
n
u
o
u
s
f
il
ter
s
h
a
v
e
b
ee
n
s
u
m
m
ar
ized
in
[
3
1
]
.
Am
o
n
g
t
h
e
f
ilter
s
,
t
h
e
w
ell
-
estab
lis
h
ed
Ou
s
ta
lo
u
p
r
ec
u
r
s
iv
e
f
i
lter
h
a
s
an
ac
ce
p
tab
le
f
i
ttin
g
to
th
e
f
r
ac
tio
n
a
l
-
o
r
d
er
d
if
f
er
en
tia
t
o
r
s
.
Ass
u
m
e
t
h
a
t
th
e
ex
p
ec
ted
f
itti
n
g
r
a
n
g
e
i
s
(ω
b
, ω
h
)
.
T
h
e
f
ilter
ca
n
b
e
ex
p
r
ess
ed
as
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
A
p
p
lica
tio
n
o
f o
p
tima
l a
r
tifi
cia
l
in
tellig
en
ce
b
a
s
ed
t
u
n
ed
co
n
tr
o
ller
s
to
a
c
la
s
s
o
f .
.
.
(
Ma
g
d
y
A
.
S
.
A
b
o
elela
)
85
̂
(
)
=
∏
+
′
+
=
−
(
3
)
W
h
er
e
th
e
p
o
les,
ze
r
o
s
,
an
d
g
ain
o
f
t
h
e
f
i
lter
o
f
o
r
d
er
N
ca
n
b
e
ev
alu
ated
as
′
=
(
ℎ
)
+
+
1
2
(
1
−
)
2
+
1
=
(
ℎ
)
+
+
1
2
(
1
+
)
2
+
1
(
4
)
an
d
=
ℎ
T
h
u
s
,
an
y
s
i
g
n
al
y
(
t
)
ca
n
b
e
f
ilter
ed
b
y
th
i
s
f
i
lter
an
d
th
e
o
u
tp
u
t
o
f
t
h
e
f
il
ter
ca
n
b
e
tr
ea
ted
as
an
ap
p
r
o
x
i
m
atio
n
f
o
r
t
h
e
d
er
iv
ativ
e
p
ar
t o
f
t
h
e
FOP
I
D
w
ith
=
o
r
th
e
in
te
g
r
al
co
u
n
ter
p
ar
t
w
it
h
=
-
.
T
h
e
r
esu
lted
tr
an
s
f
er
f
u
n
cti
o
n
o
f
th
e
FOP
I
D
is
th
e
s
u
m
o
f
t
h
e
p
r
o
p
o
r
tio
n
al
ter
m
p
lu
s
th
e
f
ilte
r
ap
p
r
o
x
im
a
tio
n
o
f
t
h
e
i
n
teg
r
al
t
er
m
(
−
)
p
lu
s
th
e
d
er
iv
a
tiv
e
ter
m
(
)
.
4.
B
AT
I
NSP
I
RE
D
A
L
G
O
RI
T
H
M
(
B
I
A)
T
h
e
b
at
in
s
p
ir
ed
alg
o
r
ith
m
(
B
I
A
)
is
a
n
e
w
ar
ti
f
icia
l
in
tel
lig
e
n
ce
(
A
I
)
tec
h
n
iq
u
e.
I
t
is
b
ased
o
n
th
e
ec
h
o
lo
ca
tio
n
b
eh
a
v
io
r
o
f
b
ats
in
s
ea
r
ch
i
n
g
t
h
eir
v
ic
ti
m
s
[
3
5
-
3
6
]
.
T
h
ese
b
ats
lo
ca
te
i
ts
p
r
e
y
b
y
e
m
i
ttin
g
a
s
er
ies
o
f
u
ltra
s
o
u
n
d
p
u
l
s
es
a
n
d
lis
te
n
f
o
r
th
e
ec
h
o
es.
T
h
e
r
ef
lecte
d
u
ltra
s
o
u
n
d
w
a
v
es
h
av
e
d
if
f
er
en
t
lev
el
s
o
f
s
o
u
n
d
a
n
d
ti
m
e
d
ela
y
s
.
T
h
is
w
ill
e
n
ab
le
ea
ch
b
at
to
g
e
t
a
s
p
ec
i
f
ic
p
r
e
y
.
T
h
e
B
I
A
is
s
u
m
m
ar
ized
in
th
e
f
o
llo
w
i
n
g
s
tep
s
,
S
tep
1
:
A
ll b
at
s
u
s
e
ec
h
o
lo
ca
tio
n
to
ev
alu
a
te
th
e
d
is
tan
ce
a
n
d
id
en
t
if
y
b
et
w
e
e
n
p
r
e
y
an
d
b
ar
r
ier
.
S
tep
2
:
E
ac
h
b
at
f
lie
s
w
it
h
a
v
elo
cit
y
(
v
i
)
at
p
o
s
itio
n
(
x
i
)
,
h
av
in
g
f
ix
ed
f
r
eq
u
e
n
c
y
(f
min
)
v
ar
y
in
g
w
a
v
ele
n
g
t
h
(
λ
)
,
an
d
lo
u
d
n
es
s
(
L
o
)
to
s
ee
k
a
p
r
e
y
.
T
h
e
b
at
tu
n
e
s
t
h
e
f
r
e
q
u
en
c
y
o
f
it
s
e
m
it
ted
p
u
l
s
e
i
n
th
e
r
an
g
e
(
f
min
,
f
max
)
an
d
ad
j
u
s
t
s
t
h
e
r
a
te
o
f
p
u
l
s
e
e
m
is
s
io
n
(
r
)
i
n
th
e
r
an
g
e
o
f
[
0
,
1
]
ac
co
r
d
in
g
to
tar
g
et
clo
s
en
es
s
.
S
tep
3
:
Fre
q
u
en
c
y
,
lo
u
d
n
e
s
s
,
an
d
p
u
l
s
e
e
m
i
s
s
io
n
r
ate
o
f
ea
ch
b
at
is
v
ar
ied
.
S
tep
4
:
T
h
eir
lo
u
d
n
ess
ch
a
n
g
es
f
r
o
m
a
lar
g
e
v
al
u
e
L
o
to
a
m
i
n
i
m
u
m
co
n
s
tan
t
v
al
u
e
L
min
.
T
h
e
p
o
s
itio
n
x
i
an
d
v
elo
cit
y
v
i
o
f
ea
ch
b
at
ar
e
u
p
d
ate
d
d
u
r
in
g
th
e
o
p
tim
iza
tio
n
p
r
o
ce
s
s
.
T
h
e
p
o
s
itio
n
s
t
i
x
an
d
v
elo
cities
t
i
v
at
a
ti
m
e
s
tep
t
,
ar
e
co
m
p
u
ted
as
f
o
llo
w
s
:
]
1
0
[
,
)
(
m
i
n
m
a
x
m
i
n
f
f
f
f
i
(
5
)
i
t
i
t
i
t
i
f
x
x
v
v
)
(
*
1
(
6
)
t
i
t
i
t
i
v
x
x
1
(
7
)
W
h
er
e
is
a
r
an
d
o
m
v
al
u
e
d
er
iv
ed
f
r
o
m
a
u
n
i
f
o
r
m
d
is
tr
ib
u
t
io
n
f
u
n
ctio
n
.
T
h
e
cu
r
r
e
n
t
g
lo
b
al
b
est
lo
ca
tio
n
*
x
is
o
b
tain
ed
a
f
ter
co
m
p
ar
in
g
al
l
lo
ca
tio
n
s
a
m
o
n
g
al
l
b
ats.
Si
n
ce
th
e
v
elo
cit
y
is
g
i
v
e
n
i
i
i
f
v
,
a
v
ar
ian
ce
in
eit
h
er
f
i
o
r
λ
i
r
es
u
lt
s
i
n
a
v
elo
cit
y
ch
a
n
g
e.
T
h
e
alg
o
r
i
th
m
is
s
tar
ted
b
y
d
e
f
i
n
in
g
a
r
an
d
o
m
f
r
eq
u
en
c
y
]
[
m
a
x
m
i
n
f
f
f
i
f
o
r
ev
er
y
b
at.
T
h
e
b
est
s
o
lu
tio
n
is
s
elec
ted
b
et
w
ee
n
cu
r
r
en
t
s
o
lu
tio
n
s
in
t
h
e
lo
ca
l
s
ea
r
ch
.
T
h
u
s
b
y
u
s
i
n
g
r
a
n
d
o
m
w
al
k
,
a
n
e
w
s
o
lu
tio
n
f
o
r
ea
ch
b
at
is
d
ev
elo
p
ed
lo
ca
lly
.
]
1
,
1
[
,
t
o
l
d
n
e
w
L
x
x
(
8
)
W
h
er
e
is
a
r
a
n
d
o
m
n
u
m
b
er
a
n
d
L
t
i
s
t
h
e
m
ea
n
lo
u
d
n
ess
o
f
all
b
ats
at
th
is
t
i
m
e
s
tep
.
L
o
u
d
n
es
s
d
ec
r
ea
s
e
s
an
d
th
e
r
ate
p
u
ls
e
e
m
i
s
s
io
n
i
n
cr
ea
s
es
af
ter
a
b
at
g
et
its
p
r
e
y
th
e
n
an
y
co
n
v
e
n
ie
n
ce
v
a
lu
e
ca
n
b
e
s
elec
ted
f
o
r
lo
u
d
n
es
s
.
W
h
e
n
t
h
e
b
at
h
a
s
j
u
s
t
f
o
u
n
d
a
p
r
e
y
,
th
i
s
m
ea
n
s
th
at
lo
u
d
n
e
s
s
is
ze
r
o
an
d
t
h
e
b
a
t
te
m
p
o
r
ar
il
y
s
to
p
s
e
m
itti
n
g
an
y
s
o
u
n
d
.
T
h
is
is
g
o
v
er
n
ed
b
y
t
h
e
f
o
llo
w
i
n
g
eq
u
ati
o
n
s
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t,
Vo
l.
9
,
No
.
1
,
Ma
r
ch
2
0
2
0
:
8
3
–
92
86
1
0
,
1
t
i
t
i
L
L
0
),
1
(
0
1
t
i
t
i
e
r
r
(
9
)
As
th
e
ti
m
e
ap
p
r
o
ac
h
es
i
n
f
i
n
it
y
,
ze
r
o
lo
u
d
n
es
s
is
ac
h
iev
ed
an
d
0
i
t
i
.
T
h
e
s
tep
s
o
f
B
I
A
a
r
e
s
u
m
m
ar
ized
in
t
h
e
f
o
llo
w
i
n
g
co
d
e
[
3
6
]
.
5.
B
RAIN EM
O
T
I
O
NAL
L
E
A
RNIN
G
B
ASE
D
I
N
T
E
L
L
I
G
E
NT
CO
N
T
RO
L
L
E
RS (
B
E
L
B
I
C)
B
E
L
B
I
C
is
an
i
n
telli
g
e
n
t
co
n
t
r
o
ller
w
h
ic
h
is
p
r
o
p
o
s
ed
b
y
C
ar
o
L
u
ca
s
[
3
6
]
.
I
t
s
h
o
w
n
in
Fig
u
r
e
1
.
I
t
ad
o
p
ts
th
e
n
et
w
o
r
k
m
o
d
el
d
ev
elo
p
ed
b
y
Mo
r
en
an
d
B
alk
e
n
iu
s
to
m
i
m
ic
t
h
o
s
e
p
ar
ts
o
f
t
h
e
b
r
ain
w
h
ich
ar
e
k
n
o
w
n
to
p
r
o
d
u
ce
em
o
tio
n
(
n
a
m
el
y
,
t
h
e
a
m
y
g
d
ala
,
o
r
b
ito
f
r
o
n
tal
co
r
tex
,
t
h
ala
m
u
s
an
d
s
e
n
s
o
r
y
i
n
p
u
t c
o
r
tex
)
.
Fig
u
r
e
1
.
T
h
e
co
m
p
u
tatio
n
al
m
o
d
el
o
f
B
E
L
B
I
C
T
h
e
m
ai
n
p
ar
ts
t
h
at
ar
e
r
esp
o
n
s
ib
le
f
o
r
p
er
f
o
r
m
in
g
t
h
e
lear
n
in
g
al
g
o
r
ith
m
s
ar
e
o
r
b
ito
f
r
o
n
tal
co
r
te
x
an
d
a
m
y
g
d
ala.
T
h
ese
ar
e
s
h
o
w
n
i
n
Fig
u
r
es
2
a
n
d
3
.
T
h
e
B
E
L
B
I
C
h
as
s
o
m
e
s
e
n
s
o
r
y
i
n
p
u
t
s
.
O
n
e
o
f
th
e
d
esig
n
er
’
s
tas
k
s
i
s
to
s
p
ec
if
y
t
h
e
s
e
n
s
o
r
y
i
n
p
u
t
s
.
T
h
e
B
E
L
B
I
C
h
a
s
t
w
o
s
tates
f
o
r
ea
ch
s
en
s
o
r
y
in
p
u
t.
On
e
o
f
th
e
s
e
t
w
o
i
s
a
m
y
g
d
a
la’
s
o
u
t
p
u
t a
n
d
an
o
t
h
er
is
th
e
o
u
tp
u
t o
f
o
r
b
ito
f
r
o
n
tal
co
r
tex
.
Fig
u
r
e
2
.
Am
y
g
d
ala
i
n
ter
n
al
c
o
m
p
o
n
en
t
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
A
p
p
lica
tio
n
o
f o
p
tima
l a
r
tifi
cia
l
in
tellig
en
ce
b
a
s
ed
t
u
n
ed
co
n
tr
o
ller
s
to
a
c
la
s
s
o
f .
.
.
(
Ma
g
d
y
A
.
S
.
A
b
o
elela
)
87
Fig
u
r
e
3
.
Or
b
ito
f
r
o
n
tal
co
r
tex
in
ter
n
a
l c
o
m
p
o
n
e
n
ts
Fro
m
m
at
h
e
m
atica
l
v
ie
w
p
o
i
n
t,
th
is
co
n
v
er
ts
i
n
to
s
u
p
p
lem
en
tin
g
t
h
e
f
in
al
r
es
u
lt
ei
th
er
th
r
o
u
g
h
ad
d
itio
n
s
o
r
s
u
b
tr
ac
tio
n
r
esp
ec
tiv
el
y
.
I
t
is
ap
p
ar
en
t
t
h
at
o
r
b
ito
f
r
o
n
tal
p
ar
t
tak
e
s
ca
r
e
o
f
t
h
e
latter
a
n
d
a
m
y
g
d
ala
p
r
o
d
u
ce
s
t
h
e
s
ig
n
al
w
h
ic
h
aid
s
to
f
i
n
d
t
h
e
f
in
al
r
esu
lt.
L
i
k
e
w
i
s
e,
a
p
last
ic
co
n
n
ec
t
io
n
id
e
n
ti
f
ies
co
n
n
ec
tio
n
s
w
it
h
o
u
t a
n
y
a
d
j
u
s
tab
le
w
ei
g
h
ts
a
n
d
a
co
n
n
ec
tio
n
w
h
ich
ca
n
lear
n
i
n
d
icate
s
.
T
h
e
Am
y
g
d
a
la
o
u
tp
u
t i
s
A
an
d
it c
an
b
e
r
ep
r
esen
ted
as
=
*
∇
=
∗
∗
ma
x
(
0
,
−
∑
)
(
1
0
)
W
h
er
e:
is
th
e
w
e
ig
h
t
f
ac
to
r
o
f
a
m
y
g
d
a
la
f
o
r
in
p
u
t
n
u
m
b
er
I
an
d
is
th
e
s
en
s
o
r
y
i
n
p
u
t
n
u
m
b
er
i.
α
d
en
o
tes
th
e
lear
n
i
n
g
r
ate
p
ar
a
m
eter
wh
ich
is
u
s
ed
to
ad
j
u
s
t
th
e
lear
n
in
g
s
p
ee
d
.
I
ts
v
al
u
e
i
s
s
et
b
et
w
ee
n
0
(
n
o
lear
n
i
n
g
)
an
d
1
(
in
s
tan
t a
d
ap
tatio
n
)
.
T
h
e
Or
b
ito
f
r
o
n
tal
co
r
tex
o
u
tp
u
t is O
a
n
d
ca
n
b
e
g
i
v
en
a
s
=
*
Δ
=
∗
(
−
∑
−
∑
−
(
)
)
(
1
1
)
W
h
er
e
:
W
i
s
t
h
e
w
ei
g
h
t
o
f
t
h
e
o
r
b
ito
f
r
o
n
tal
co
r
te
x
f
o
r
th
e
r
elate
d
s
e
n
s
o
r
y
i
n
p
u
t
an
d
d
en
o
te
s
th
e
Or
b
ito
f
r
o
n
tal
lear
n
i
n
g
r
ate.
T
h
e
o
u
tp
u
t o
f
B
I
L
B
I
C
is
g
iv
e
n
as U
an
d
ca
n
b
e
d
en
o
ted
as
U=
Am
y
g
d
ala
o
u
tp
u
t
–
Or
b
ito
f
r
o
n
tal
co
r
tex
=
∑
−
∑
(
1
2
)
6.
AP
P
L
I
CA
T
I
O
N
T
h
e
m
et
h
o
d
o
lo
g
ies
d
escr
ib
ed
h
er
ein
ca
n
b
e
ap
p
lied
o
n
a
s
in
g
le
ar
ea
p
o
w
er
s
y
s
t
e
m
w
h
er
e
th
e
o
b
j
ec
tiv
e
is
to
m
ai
n
tai
n
t
h
e
w
o
r
k
i
n
g
f
r
eq
u
e
n
c
y
ch
a
n
g
e
a
t
a
p
er
m
i
s
s
ib
le
r
a
n
g
e
w
h
e
n
th
e
lo
ad
s
ar
e
ch
an
g
ed
s
u
d
d
en
l
y
o
v
er
o
r
u
n
d
er
t
h
e
p
lan
n
ed
v
alu
e
s
.
T
h
e
s
y
s
te
m
co
n
s
is
ts
o
f
t
h
r
ee
m
ai
n
co
m
p
o
n
en
t
s
.
T
h
ese
ar
e
th
e
g
o
v
er
n
er
,
th
e
tu
r
b
in
e
an
d
th
e
g
e
n
er
ato
r
an
d
lo
ad
.
T
h
e
b
l
o
ck
d
iag
r
a
m
s
i
m
p
le
m
e
n
ti
n
g
th
e
P
I
D
an
d
Hy
b
r
id
FOP
I
D
-
B
E
L
B
I
C
co
n
tr
o
ller
s
a
r
e
d
elin
ea
ted
i
n
Fi
g
u
r
es 4
a
n
d
5
.
T
h
e
p
ar
am
eter
s
f
o
r
t
h
ese
d
iag
r
a
m
s
ar
e
li
s
ted
i
n
T
ab
le
1
.
T
h
e
s
y
s
te
m
s
ar
e
s
u
b
j
ec
ted
to
a
s
u
d
d
en
lo
ad
ch
a
n
g
e
o
f
0
.
0
5
p
.
u
.
T
h
e
ch
ar
ac
ter
is
tics
o
f
th
e
tu
r
b
i
n
e
s
atu
r
atio
n
(
GR
C
)
,
th
e
GDB
an
d
th
e
ti
m
e
d
ela
y
as
n
o
n
-
li
n
e
ar
elem
e
n
ts
ar
e
d
is
p
la
y
ed
in
T
ab
le
2
.
No
ticea
b
ly
,
th
e
p
r
o
p
o
s
ed
Sim
u
li
n
k
-
b
ase
d
m
o
d
el
ca
n
clea
r
l
y
ac
co
m
m
o
d
ate
t
h
e
g
o
v
er
n
o
r
d
ea
d
b
an
d
s
(
GDB
s
)
,
th
e
g
en
er
atio
n
r
ate
co
n
s
tr
ain
t
s
(
GR
C
)
a
n
d
t
h
e
tr
an
s
p
o
r
t
d
ela
y
s
ar
e
s
h
o
w
n
i
n
Fi
g
u
r
e
s
4
an
d
5
.
Dea
d
b
an
d
s
ar
e
i
m
p
o
s
ed
i
n
t
h
e
m
o
d
el
u
s
i
n
g
b
ac
k
las
h
n
o
n
l
in
ea
r
itie
s
w
h
er
e
0
.
0
5
%
is
co
n
s
id
er
ed
.
T
h
e
GR
C
o
f
t
h
e
t
h
er
m
al
ar
ea
is
s
et
to
0
.
0
1
p
.
u
.
MW
/s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t,
Vo
l.
9
,
No
.
1
,
Ma
r
ch
2
0
2
0
:
8
3
–
92
88
Fig
u
r
e
4
.
T
h
e
s
i
m
u
la
tio
n
d
iag
r
a
m
o
f
t
h
e
L
FC
w
i
th
cla
s
s
ica
l
P
I
D
co
n
tr
o
ller
s
in
clu
d
in
g
th
e
e
m
b
ed
d
ed
s
y
s
te
m
n
o
n
l
in
e
ar
ities
Fig
u
r
e
5
.
T
h
e
s
i
m
u
la
tio
n
d
iag
r
a
m
o
f
t
h
e
L
FC
w
i
th
h
y
b
r
id
FO
P
I
D
an
d
B
E
L
B
I
C
co
n
tr
o
ller
s
in
clu
d
i
n
g
th
e
e
m
b
ed
d
ed
s
y
s
te
m
n
o
n
l
in
e
ar
ities
T
ab
le
1
.
T
h
e
s
i
m
u
latio
n
m
o
d
e
l p
ar
am
eter
s
P
a
r
a
me
t
e
r
U
n
i
t
s
V
a
l
u
e
S
t
e
a
m g
o
v
e
r
n
o
r
t
i
me
c
o
n
st
a
n
t
(
ℎ
)
se
c
o
n
d
s
0
.
0
8
S
t
e
a
m g
o
v
e
r
n
o
r
g
a
i
n
f
a
c
t
o
r
(
ℎ
)
-
1
T
u
r
b
i
n
e
t
i
me
c
o
n
st
a
n
t
(
)
se
c
o
n
d
s
0
.
3
T
u
r
b
i
n
e
g
a
i
n
f
a
c
t
o
r
(
)
-
1
M
a
ss
a
n
d
g
e
n
e
r
a
t
o
r
t
i
me
c
o
n
st
a
n
t
(
)
se
c
o
n
d
s
20
M
a
ss
a
n
d
g
e
n
e
r
a
t
o
r
g
a
i
n
f
a
c
t
o
r
(
)
-
1
2
0
G
o
v
e
r
n
o
r
sp
e
e
d
r
e
g
u
l
a
t
i
o
n
p
a
r
a
me
t
e
r
(
H
z
/
p
.
u
.
M
W
)
2
.
4
T
ab
le
2
.
T
h
e
ch
ar
ac
ter
is
tics
o
f
th
e
tu
r
b
i
n
e
s
at
u
r
atio
n
(
GR
C
)
,
th
e
GDB
an
d
th
e
t
i
m
e
d
ela
y
N
o
n
-
l
i
n
e
a
r
El
e
me
n
t
S
y
mb
o
l
e
D
a
t
a
T
u
r
b
i
n
e
G
R
C
S
a
t
u
r
a
t
e
d
a
t
±
0
.
0
1
[
p
.
u
M
W
/
se
c
o
n
d
]
T
i
me
d
e
l
a
y
1
-
2
se
c
o
n
d
s
G
D
B
0
.
0
5
%
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
A
p
p
lica
tio
n
o
f o
p
tima
l a
r
tifi
cia
l
in
tellig
en
ce
b
a
s
ed
t
u
n
ed
co
n
tr
o
ller
s
to
a
c
la
s
s
o
f .
.
.
(
Ma
g
d
y
A
.
S
.
A
b
o
elela
)
89
T
h
e
p
ar
am
eter
s
o
f
t
h
e
B
at
I
n
s
p
ir
ed
A
lg
o
r
ith
m
ar
e
g
iv
e
n
i
n
T
ab
le
3
[
3
9
]
.
T
ab
le
3
.
T
h
e
p
ar
am
eter
s
o
f
t
h
e
b
at
in
s
p
ir
ed
alg
o
r
ith
m
P
a
r
a
me
t
e
r
D
e
scri
p
t
i
o
n
V
a
l
u
e
n
P
o
p
u
l
a
t
i
o
n
s
i
z
e
10
-
40
N
N
u
mb
e
r
o
f
g
e
n
e
r
a
t
i
o
n
s
1
0
0
A
L
o
u
d
n
e
ss
0
.
5
r
P
u
l
se
r
a
t
e
0
.
5
Q
m
i
n
M
i
n
u
mu
m
f
r
e
q
u
e
n
c
y
0
Q
max
M
a
x
i
m
u
m
f
r
e
q
u
e
n
c
y
2
α
c
o
n
st
a
n
t
0
.
9
5
γ
c
o
n
st
a
n
t
0
.
9
T
h
e
o
p
tim
izatio
n
f
i
tn
e
s
s
f
u
n
ct
io
n
i
f
at
iter
atio
n
i
is
g
i
v
en
a
s
i
f
=
1
(
1
3
)
So
th
at
=
∫
2
(
)
∞
0
+
P
.
O
+
Settli
n
g
T
i
m
e
(
1
4
)
W
h
er
e
I
S
E
i
is
th
e
in
teg
r
al
-
s
q
u
ar
e
-
er
r
o
r
in
d
ex
at
iter
atio
n
i
,
e
i
is
th
e
ar
ea
co
n
tr
o
l
er
r
o
r
in
d
ex
(
A
C
E
)
at
iter
atio
n
i
,
P
.
O
is
th
e
p
er
ce
n
ta
g
e
o
v
er
s
h
o
o
t
o
f
t
h
e
f
r
eq
u
e
n
c
y
-
ti
m
e
r
e
s
p
o
n
s
e
c
u
r
v
e.
T
h
e
d
ef
i
n
itio
n
s
o
f
P
.
O
an
d
s
et
tli
n
g
ti
m
e
ar
e
d
ep
icted
in
[
7
]
.
7.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
f
r
eq
u
en
c
y
co
n
tr
o
l
s
i
n
g
le
ar
ea
p
o
w
er
s
y
s
te
m
w
it
h
G
R
C
,
GDB
,
an
d
ti
m
e
d
ela
y
n
o
n
lin
ea
r
itie
s
in
co
r
p
o
r
atin
g
t
h
e
P
I
D
an
d
H
y
b
r
id
FOP
I
D
-
B
E
L
B
I
C
co
n
tr
o
ll
er
s
h
a
s
b
ee
n
i
n
v
e
s
ti
g
ated
i
n
t
h
is
r
es
ea
r
c
h
.
T
h
e
B
at
I
n
s
p
ir
ed
A
l
g
o
r
ith
m
h
as
b
ee
n
u
tili
ze
d
to
tu
n
e
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
s
.
T
h
e
tu
n
i
n
g
p
r
o
ce
s
s
o
f
th
e
t
w
o
co
n
tr
o
ller
s
h
a
s
b
ee
n
ac
h
ie
v
ed
u
s
in
g
t
h
e
Ma
t
lab
/Si
m
u
lin
k
s
o
f
t
w
ar
e.
T
h
e
o
u
tco
m
e
s
o
f
t
h
e
tu
n
i
n
g
p
r
o
ce
d
u
r
e
u
s
i
n
g
th
e
I
n
teg
r
al
Sq
u
ar
e
E
r
r
o
r
cr
ite
r
io
n
ar
e
s
u
m
m
ar
ized
in
T
ab
le
4
.
T
ab
le
4
.
R
esu
lts
o
f
th
e
t
w
o
p
r
o
p
o
s
ed
co
n
tr
o
ller
s
C
o
n
t
r
o
l
l
e
r
P
a
r
a
me
t
e
r
s
P
I
D
-
-
-
-
0
.
5
4
1
.
8
3
0
-
-
-
-
I
S
E
1
6
.
5
7
4
6
α
β
F
O
P
I
D
-
B
E
L
B
I
C
0
.
5
4
1
.
8
3
0
.
8
6
0
.
2
5
0
.
3
2
4
.
7
3
e
-
05
4
.
5
0
e
-
05
I
S
E
1
2
.
1
9
2
9
As
s
tated
i
n
t
h
e
liter
at
u
r
e,
a
p
r
o
p
o
r
tio
n
al
co
n
tr
o
ller
(
)
w
il
l
h
av
e
th
e
e
f
f
ec
t
o
f
r
ed
u
cin
g
t
h
e
r
is
e
ti
m
e
an
d
w
ill
r
ed
u
ce
,
b
u
t
n
ev
er
elim
in
ate,
t
h
e
s
tead
y
-
s
tate
er
r
o
r
.
A
n
in
teg
r
al
co
n
tr
o
l
(
)
w
ill
h
av
e
t
h
e
ef
f
ec
t
o
f
eli
m
i
n
ati
n
g
th
e
s
tead
y
-
s
tat
e
er
r
o
r
,
b
u
t
it
m
a
y
m
a
k
e
t
h
e
tr
an
s
ie
n
t
r
e
s
p
o
n
s
e
w
o
r
s
e.
A
d
er
iv
ativ
e
co
n
tr
o
l
(
)
w
il
l
h
av
e
t
h
e
ef
f
ec
t
o
f
in
cr
ea
s
in
g
th
e
s
tab
ilit
y
o
f
th
e
s
y
s
te
m
,
r
ed
u
cin
g
th
e
o
v
er
s
h
o
o
t,
an
d
i
m
p
r
o
v
in
g
th
e
tr
an
s
ie
n
t
r
esp
o
n
s
e
[
7
]
.
T
h
is
i
s
clea
r
w
h
e
n
w
e
lo
o
k
at
th
e
f
r
eq
u
en
c
y
r
esp
o
n
s
e
o
f
t
h
e
s
y
s
te
m
w
i
th
o
u
t
co
n
tr
o
ller
(
b
y
s
etti
n
g
t
h
e
v
al
u
es
o
f
to
1
,
to
o
an
d
to
0
in
Fi
g
u
r
e
3
.
T
h
is
r
esp
o
n
s
e,
as
s
h
o
w
n
i
n
Fig
u
r
e
6
,
is
o
s
cillato
r
y
w
it
h
a
litt
le
d
a
m
p
in
g
e
f
f
ec
t.
T
h
is
w
il
l
e
x
p
lain
w
h
y
w
e
s
h
o
u
ld
s
ee
k
f
o
r
a
s
p
ec
ia
l
co
n
tr
o
ller
w
h
ich
w
i
ll d
a
m
p
t
h
i
s
o
s
cillatio
n
a
n
d
ac
h
ie
v
e
a
s
y
s
te
m
w
it
h
s
tead
y
-
s
tate
er
r
o
r
.
As s
tated
ea
r
lier
,
t
h
e
f
ir
s
t a
l
ter
n
ati
v
e
is
to
i
m
p
le
m
e
n
t t
h
e
P
I
D
co
n
tr
o
ller
.
T
h
e
d
if
f
er
en
ce
b
et
w
ee
n
P
I
D
an
d
P
I
D(
s
)
in
Fig
u
r
e
3
is
th
at
th
e
p
ar
a
m
eter
s
o
f
t
h
e
f
ir
s
t
co
n
tr
o
ller
(
,
,
an
d
)
a
r
e
tu
n
ed
u
s
i
n
g
th
e
B
I
A
b
u
t
th
o
s
e
o
f
t
h
e
s
ec
o
n
d
co
n
tr
o
ller
,
P
I
D(
s
)
,
ar
e
o
b
tain
ed
a
s
p
ec
ial
o
p
ti
m
izatio
n
tech
n
iq
u
e
a
s
s
o
ciate
d
w
it
h
t
h
is
b
lo
ck
i
n
Ma
tlab
.
T
h
e
f
r
eq
u
en
c
y
r
e
s
p
o
n
s
e
o
f
t
h
e
P
I
D
co
n
tr
o
ller
as
s
h
o
w
n
in
Fi
g
u
r
e
7
is
s
o
m
e
w
h
at
ac
ce
p
tab
le
b
u
t
th
er
e
ar
e
t
w
o
m
ai
n
f
ea
t
u
r
es.
T
h
e
f
ir
s
t
is
th
e
r
ip
p
le
ef
f
ec
t
w
h
en
tr
y
in
g
to
r
ea
ch
th
e
s
tead
y
s
ta
te.
Seco
n
d
is
th
e
h
ig
h
v
alu
e
o
f
I
SE
in
d
e
x
.
T
h
e
tu
n
ed
p
ar
am
eter
s
o
f
t
h
is
co
n
tr
o
ller
ar
e
s
h
o
w
n
i
n
T
ab
le
4
.
T
h
e
tu
n
in
g
p
r
o
ce
d
u
r
e
u
s
in
g
th
e
B
I
A
y
ield
s
ze
r
o
v
al
u
e
f
o
r
th
e
in
teg
r
al
g
ain
.
T
h
is
is
ex
p
ec
ted
s
in
ce
w
e
ar
e
tr
y
in
g
to
r
ed
u
ce
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t,
Vo
l.
9
,
No
.
1
,
Ma
r
ch
2
0
2
0
:
8
3
–
92
90
th
e
o
v
er
s
h
o
o
t
in
t
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
.
T
r
ials
h
av
e
b
ee
n
m
ad
e
to
lim
i
t
th
e
to
v
alu
es
g
r
ea
ter
th
an
ze
r
o
i
n
th
e
tu
n
i
n
g
p
r
o
ce
d
u
r
e
b
u
t th
is
l
ea
d
s
to
an
u
n
s
tab
le
s
y
s
te
m
.
On
th
e
co
n
tr
ar
y
,
th
e
h
y
b
r
id
FOP
I
D
-
B
E
L
B
I
C
co
n
tr
o
ller
is
s
h
o
w
n
i
n
Fi
g
u
r
e
8
.
T
h
e
tu
n
in
g
s
tep
h
as
b
ee
n
ac
h
iev
ed
u
s
in
g
t
h
e
B
I
A
.
T
h
e
r
esu
lts
o
f
t
h
e
tu
n
in
g
p
r
o
ce
d
u
r
e
y
ie
ld
5
p
a
r
am
eter
s
;
,
,
,
a
n
d
;
f
o
r
th
e
F
OP
I
D
co
n
tr
o
ller
an
d
2
p
ar
am
eter
s
;
α
an
d
β
;
f
o
r
th
e
B
E
L
B
I
C
.
T
h
e
esti
m
ated
v
alu
e
s
f
o
r
th
ese
7
p
ar
am
eter
s
ar
e
d
elin
ea
ted
i
n
T
ab
le
4
.
T
h
is
h
a
s
b
ee
n
ac
h
ie
v
ed
u
s
i
n
g
th
e
B
I
A
p
ar
a
m
eter
s
ettin
g
d
eli
n
ea
ted
in
T
ab
le
3
.
I
t
is
clea
r
th
at
th
is
h
y
b
r
id
FOP
I
D
-
B
E
L
B
I
C
w
ill
y
i
eld
a
s
m
a
ller
v
al
u
e
f
o
r
th
e
I
S
E
in
d
ex
co
m
p
ar
ed
w
it
h
t
h
e
co
n
v
en
t
io
n
al
P
I
D
co
n
tr
o
ller
.
T
h
is
,
o
f
co
u
r
s
e,
ca
b
b
e
ar
r
iv
ed
to
w
it
h
litt
le
h
i
g
h
co
m
p
u
tatio
n
ti
m
e.
T
h
e
f
r
eq
u
en
c
y
r
e
s
p
o
n
s
e
o
b
tai
n
ed
b
y
ap
p
l
y
in
g
th
e
clas
s
ical
P
I
D
co
n
tr
o
ller
an
d
t
h
e
h
y
b
r
i
d
FOP
I
D
-
B
E
L
B
I
C
is
d
i
s
p
la
y
ed
i
n
F
ig
u
r
es
6
an
d
7
.
T
h
e
t
w
o
c
u
r
v
es
ill
u
s
tr
ate
th
e
f
ac
t
th
at
w
e
ca
n
n
o
t
ar
r
iv
ed
,
ex
ac
tl
y
,
to
a
ze
r
o
s
tate
er
r
o
r
.
T
h
is
i
s
d
u
e
to
t
h
e
G
R
C
,
GB
D,
a
n
d
ti
m
e
d
ela
y
n
o
n
l
in
ea
r
itie
s
.
On
e
m
o
r
e
th
i
n
g
,
th
e
i
n
cr
ea
s
e
o
f
th
e
ti
m
e
d
ela
y
w
ill
r
esu
lt
i
n
u
n
s
tab
le
s
y
s
te
m
.
T
h
e
an
al
y
s
i
s
o
f
t
h
ese
e
f
f
ec
ts
w
ill
b
e
s
t
u
d
ied
i
n
an
o
th
er
en
d
ea
v
o
r
.
Fig
u
r
e
6
.
T
h
e
s
i
m
u
la
tio
n
r
es
u
l
ts
w
it
h
o
u
t c
o
n
tr
o
ller
w
it
h
ti
m
e
d
elay
o
f
1
.
5
s
ec
o
n
d
s
Fig
u
r
e
7
.
T
h
e
s
i
m
u
la
tio
n
r
es
u
l
ts
w
it
h
P
I
D
co
n
tr
o
ller
w
it
h
ti
m
e
d
ela
y
o
f
1
.
5
s
ec
o
n
d
s
Fig
u
r
e
8
.
T
h
e
s
i
m
u
la
tio
n
r
es
u
l
ts
w
it
h
h
y
b
r
id
FOP
I
D
-
B
E
L
B
I
C
co
n
tr
o
ller
w
it
h
ti
m
e
d
elay
o
f
1
.
5
s
ec
o
n
d
s
8.
CO
NCLU
SI
O
N
I
n
t
h
is
p
ap
er
,
th
e
ap
p
licatio
n
o
f
t
w
o
cla
s
s
e
s
o
f
co
n
tr
o
ller
s
to
a
s
i
n
g
le
ar
ea
lo
ad
f
r
eq
u
e
n
c
y
c
o
n
tr
o
l
h
as
b
ee
n
in
v
esti
g
ated
.
T
h
e
p
r
esen
ted
s
y
s
te
m
h
as
t
h
r
ee
s
o
u
r
ce
s
o
f
n
o
n
l
in
ea
r
itie
s
.
T
h
ese
ar
e
th
e
GR
C
,
GB
D,
an
d
ti
m
e
d
ela
y
.
T
h
e
f
ir
s
t
co
n
tr
o
ller
is
th
e
class
i
ca
l
P
I
D
co
n
tr
o
ller
w
h
i
le
th
e
s
ec
o
n
d
is
th
e
h
y
b
r
i
d
FOP
I
D
-
B
E
L
B
I
C
.
T
h
e
p
ar
am
eter
s
o
f
t
h
ese
t
wo
co
n
tr
o
ller
s
h
a
v
e
b
ee
n
o
p
ti
m
all
y
t
u
n
ed
u
s
in
g
t
h
e
B
I
A
.
R
es
u
lt
s
s
h
o
w
t
h
at
th
e
s
ec
o
n
d
co
n
tr
o
ller
w
ill
b
e
h
av
e
b
etter
t
h
an
t
h
e
f
ir
s
t
o
n
e.
T
h
is
is
b
ec
au
s
e
o
f
t
h
e
n
o
n
li
n
ea
r
it
y
n
at
u
r
e
o
f
th
e
s
ec
o
n
d
co
n
tr
o
ller
.
F
u
r
th
er
m
o
r
e,
th
e
e
f
f
ec
t
o
f
d
ea
li
n
g
with
th
e
t
h
r
ee
e
m
b
ed
d
ed
n
o
n
li
n
ea
r
ities
,
th
e
G
R
C
,
GB
D,
an
d
ti
m
e
d
ela
y
,
h
av
e
b
e
en
s
t
u
d
ied
b
u
t
m
o
r
e
d
etailed
r
esear
ch
is
r
ec
o
m
m
e
n
d
ed
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
A
p
p
lica
tio
n
o
f o
p
tima
l a
r
tifi
cia
l
in
tellig
en
ce
b
a
s
ed
t
u
n
ed
co
n
tr
o
ller
s
to
a
c
la
s
s
o
f .
.
.
(
Ma
g
d
y
A
.
S
.
A
b
o
elela
)
91
RE
F
E
R
E
NC
E
S
[1
]
L
.
Do
n
g
,
"
De
c
e
n
tralize
d
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
f
o
r
a
n
in
terc
o
n
n
e
c
ted
p
o
w
e
r
s
y
ste
m
w
it
h
n
o
n
li
n
e
a
rit
ies
,"
In
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
Ame
ric
a
n
C
o
n
tro
l
Co
n
fer
e
n
c
e
(
ACC)
,
2
0
1
6
.
[2
]
M
.
El
sisi,
M
.
S
o
li
m
a
n
,
M
.
A
.
S
.
A
b
o
e
lela
,
W
.
M
a
n
so
u
r,
"
G
S
A
-
b
a
se
d
d
e
sig
n
o
f
d
u
a
l
p
ro
p
o
rti
o
n
a
l
in
teg
ra
l
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
ll
e
r
s
f
o
r
n
o
n
l
in
e
a
r
h
y
d
ro
th
e
rm
a
l
p
o
w
e
r
s
y
ste
m
,
"
W
o
rld
Aca
d
e
my
o
f
S
c
ien
c
e
,
En
g
i
n
e
e
rin
g
,
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
9
,
p
p
.
1
2
4
2
-
1
2
4
8
,
2
0
1
5
.
[3
]
V
.
S
i
n
g
h
,
A
.
Ku
m
a
r
S
in
g
h
,
V.
Ch
a
u
h
a
n
,
a
n
d
A
.
Ku
m
a
r
Bh
a
ra
d
wa
j,
"
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
sin
g
le
a
re
a
p
o
we
r
s
y
ste
m
u
sin
g
J
A
Y
A
a
l
g
o
rit
h
m
,
"
In
ter
n
a
ti
o
n
a
l
Res
e
a
rc
h
J
o
u
rn
a
l
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
T
e
c
h
n
o
lo
g
y
(
IRJET
)
,
v
ol
.
4
,
n
o
.
7
,
2
0
1
7
.
[4
]
H.
Be
v
ra
n
i,
Ro
b
u
st
p
o
we
r sy
ste
m f
re
q
u
e
n
c
y
c
o
n
tr
o
l
,
S
p
ri
n
g
e
r
,
2
0
0
9
.
[5
]
D.
Ko
th
a
ri
a
n
d
I
.
Na
g
ra
th
,
P
o
we
r
sy
ste
m en
g
in
e
e
rin
g
,
Ne
w
Yo
rk
:
M
c
G
ra
w
-
Hill
,
2
0
0
8
.
[6
]
D.
X
u
e
,
Y.
Ch
e
n
,
a
n
d
D.
P
.
A
th
e
rto
n
,
L
i
n
e
a
r
fee
d
b
a
c
k
c
o
n
tr
o
l:
An
a
lys
is
a
n
d
d
e
sig
n
wit
h
M
AT
L
AB
,
P
h
il
a
d
e
lp
h
ia,
P
A
:
S
o
c
iety
f
o
r
In
d
u
strial
&
A
p
p
l
ied
M
a
th
e
m
a
ti
c
s
,
2
0
0
8
.
[7
]
K.
J.
Å
strö
m
,
K.
J.
A
strö
m
,
T
.
H
ä
g
g
lu
n
d
,
K.
J.
A
stro
m
,
T
.
Ha
g
g
lu
n
d
,
a
n
d
T
.
H.
Ha
g
g
lu
n
d
,
PID
c
o
n
tro
ll
e
rs
:
T
h
e
o
ry
,
d
e
sig
n
a
n
d
t
u
n
i
n
g
,
In
tern
a
ti
o
n
a
l
S
o
c
iety
f
o
r
M
e
a
su
re
m
e
n
t
a
n
d
Co
n
t
ro
l
,
1
9
9
5
.
[8
]
S
.
K.
P
a
n
d
e
y
,
S
.
R.
M
o
h
a
n
ty
,
a
n
d
N.
Kish
o
r,
"
A
li
tera
tu
re
su
rv
e
y
o
n
l
o
a
d
–
f
re
q
u
e
n
c
y
c
o
n
tro
l
f
o
r
c
o
n
v
e
n
ti
o
n
a
l
a
n
d
d
istri
b
u
ti
o
n
g
e
n
e
ra
ti
o
n
p
o
w
e
r
s
y
st
e
m
s
,"
Ren
e
wa
b
le a
n
d
S
u
sta
in
a
b
le
En
e
rg
y
Rev
iews
,
v
o
l.
2
5
,
p
p
.
3
1
8
-
3
3
4
,
2
0
1
3
.
[9
]
S
.
P
.
G
h
o
sh
a
l,
"
A
p
p
li
c
a
ti
o
n
o
f
GA
/
GA
-
S
A
b
a
se
d
f
u
z
z
y
a
u
to
m
a
ti
c
g
e
n
e
ra
ti
o
n
c
o
n
tro
l
o
f
a
m
u
lt
i
-
a
re
a
th
e
r
m
a
l
g
e
n
e
ra
ti
n
g
s
y
ste
m
,"
El
e
c
t.
Po
we
r S
y
st.
Res
.
,
v
o
l
.
7
0
,
p
p
.
1
1
5
-
1
2
7
,
2
0
0
4
.
[1
0
]
C.
Is
m
a
y
il
,
R.
S
.
Ku
m
a
r,
T
.
K.
S
i
n
d
h
u
,
"
Op
ti
m
a
l
f
ra
c
ti
o
n
a
l
o
rd
e
r
P
ID
c
o
n
tro
ll
e
r
f
o
r
a
u
to
m
a
ti
c
g
e
n
e
ra
ti
o
n
c
o
n
tr
o
l
o
f
tw
o
‐a
re
a
p
o
we
r
s
y
ste
m
s
,"
In
ter
n
a
ti
o
n
a
l
T
ra
n
s
a
c
ti
o
n
s o
n
El
e
c
trica
l
En
e
rg
y
S
y
ste
ms
,
2
0
1
4
.
[1
1
]
L
.
P
i
n
k
a
g
,
Z.
He
n
g
ju
n
,
a
n
d
L
.
Y
u
y
u
n
,
"
Ge
n
e
ti
c
a
lg
o
rit
h
m
o
p
ti
m
iza
ti
o
n
f
o
r
A
G
C
o
f
m
u
lt
i
-
a
re
a
p
o
w
e
r
s
y
ste
m
s
,"
In
Pro
c
.
o
f
I
EE
E
Reg
io
n
1
0
c
o
n
fer
e
n
c
e
o
n
c
o
m
p
u
ter
s,
c
o
mm
u
n
ica
ti
o
n
s,
c
o
n
tro
l
a
n
d
p
o
we
r
e
n
g
i
n
e
e
rin
g
(
T
ENCON’0
2
)
,
p
p
.
1
8
1
8
-
2
1
,
2
0
0
2
.
[1
2
]
H.
G
o
lp
ira,
H.
Be
v
r
a
n
i
,
"
A
p
p
li
c
a
ti
o
n
o
f
GA
o
p
ti
m
iza
ti
o
n
fo
r
a
u
to
m
a
ti
c
g
e
n
e
ra
ti
o
n
c
o
n
tr
o
l
d
e
sig
n
in
a
n
in
terc
o
n
n
e
c
ted
p
o
w
e
r
s
y
ste
m
,"
E
n
e
rg
y
Co
n
v
e
rs
io
n
a
n
d
M
a
n
a
g
e
me
n
t
,
v
o
l
.
5
2
,
p
p
.
2
2
4
7
-
2
2
5
5
,
2
0
1
1
.
[1
3
]
Y.
L
.
A
b
d
e
l
-
M
a
g
id
,
M
.
A
.
A
b
id
o
,
"
AG
C
tu
n
in
g
o
f
in
terc
o
n
n
e
c
ted
re
h
e
a
t
th
e
rm
a
l
s
y
ste
m
s
w
i
th
p
a
rti
c
le
sw
a
r
m
o
p
ti
m
iza
ti
o
n
,
"
1
0
th
IEE
E
in
ter
n
a
t
io
n
a
l
c
o
n
fer
e
n
c
e
o
n
e
lec
tro
n
ics
,
c
irc
u
it
s,
a
n
d
sy
ste
ms
,
v
o
l.
1
,
p
p
.
3
7
6
-
9
,
2
0
0
3
.
[1
4
]
H.
G
o
z
d
e
,
M
.
C.
T
a
p
lam
a
c
io
g
lu
,
I.
K
o
c
a
a
rsla
n
,
a
n
d
M
.
A
.
S
e
n
o
l,
"
P
a
rti
c
le
sw
a
r
m
o
p
ti
m
iza
ti
o
n
b
a
s
e
d
P
I
-
c
o
n
tro
ll
e
r
d
e
sig
n
to
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
a
t
w
o
a
r
e
a
r
e
h
e
a
t
th
e
r
m
a
l
p
o
w
e
r
s
y
ste
m
,"
J
.
T
h
e
rm
S
c
i
T
e
c
h
.
,
v
o
l.
3
0
,
n
o
.
1
,
p
p
.
1
3
-
2
1
,
2
0
1
0
.
[1
5
]
H.
S
h
a
b
a
n
i,
B.
V
a
h
id
i
,
a
n
d
M
.
E
b
ra
h
im
p
o
u
r,
"
A
ro
b
u
st
P
ID
c
o
n
tr
o
ll
e
r
b
a
se
d
o
n
im
p
e
rialist
c
o
m
p
e
ti
ti
v
e
a
lg
o
rit
h
m
f
o
r
lo
a
d
-
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
p
o
we
r
s
y
ste
m
s
,"
IS
A
T
ra
n
s
.
,
v
o
l.
5
2
,
n
o
.
1
,
p
p
.
8
8
-
9
5
,
2
0
1
3
.
[1
6
]
B.
P
a
r
a
m
a
siv
a
m
a
n
d
I.
A
.
Ch
id
a
m
b
a
ra
m
,
"
B
a
c
teria
l
f
o
ra
g
in
g
o
p
ti
m
iza
ti
o
n
b
a
se
d
l
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
in
terc
o
n
n
e
c
ted
p
o
w
e
r
s
y
st
e
m
s
w
i
th
sta
ti
c
s
y
n
c
h
ro
n
o
u
s
se
ries
c
o
m
p
e
n
sa
to
r
,"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
L
a
tes
t
T
re
n
d
s
in
Co
m
p
u
t
in
g
,
v
ol
.
1
,
n
o
.
2
,
2
0
1
0
.
[1
7
]
J.
Na
n
a
d
a
,
S
.
M
is
h
ra
,
a
n
d
L
.
C.
S
a
ik
a
,
"
M
a
id
e
n
a
p
p
li
c
a
ti
o
n
o
f
b
a
c
teria
l
f
o
ra
g
in
g
-
b
a
se
d
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
in
m
u
lt
i
-
a
re
a
a
u
to
m
a
ti
c
g
e
n
e
ra
ti
o
n
c
o
n
tr
o
l
,"
IEE
E
T
ra
n
s.
P
o
we
r S
y
st.
,
v
o
l.
2
4
,
n
o
.
2
,
p
p
.
6
0
2
-
6
0
9
,
2
0
0
9
.
[1
8
]
P
.
A
n
it
h
a
,
P
.
S
u
b
b
u
ra
j
a
n
d
K.
V
iv
e
k
Ku
m
a
r,
"
Ba
c
teria
l
f
o
ra
g
i
n
g
o
p
ti
m
iza
ti
o
n
b
a
se
d
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
in
terc
o
n
n
e
c
ted
p
o
w
e
r
s
y
ste
m
s
,"
I
n
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
A
d
v
a
n
c
e
d
Res
e
a
rc
h
in
Bi
o
lo
g
y
En
g
i
n
e
e
rin
g
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
(
IJ
AR
BE
S
T
)
,
v
o
l.
2
,
n
o
.
1
5
,
2
0
1
6
.
[1
9
]
S
.
Du
m
a
n
;
N.
Yo
ru
k
e
re
n
A
nd
I.
Ha
k
k
i
A
lt
a
s,
"
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
a
sin
g
le
a
re
a
p
o
we
r
s
y
ste
m
u
sin
g
g
ra
v
it
a
ti
o
n
a
l
se
a
rc
h
a
lg
o
ri
th
m
,
"
I
n
n
o
v
a
ti
o
n
s i
n
In
telli
g
e
n
t
S
y
ste
ms
a
n
d
Ap
p
li
c
a
ti
o
n
s (
INIS
T
A)
,
2
0
1
2
.
[2
0
]
S
.
Kr.
G
a
u
ta
m
a
n
d
N.
G
o
y
a
l,
"
I
m
p
ro
v
e
d
p
a
rti
c
le
s
wa
r
m
o
p
ti
m
iza
ti
o
n
b
a
se
d
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
in
a
sin
g
le
a
re
a
p
o
w
e
r
s
y
ste
m
,
"
An
n
u
a
l
IEE
E
In
d
i
a
Co
n
fer
e
n
c
e
(
INDICO
N)
,
2
0
1
0
.
[2
1
]
M
.
L
ü
y
,
İ.
Ko
c
a
a
rsl
a
n
,
E.
Ça
m
,
M
.
C.
T
a
p
la
m
a
c
io
ǧ
lu
,
"
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
in
a
sin
g
le
a
re
a
p
o
w
e
r
s
y
ste
m
b
y
a
rti
f
icia
l
n
e
u
ra
l
n
e
tw
o
rk
(
A
NN
),
"
In
Pr
o
c
e
e
d
in
g
s
o
f
t
h
e
4
th
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
T
P
E
,
p
p
.
2
6
-
2
9
,
2
0
0
8
.
[2
2
]
K.S
w
e
th
a
a
n
d
D.
V
ij
a
y
a
Ku
m
a
r
,
"
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
i
n
a
sin
g
le
a
re
a
p
o
w
e
r
s
y
ste
m
u
sin
g
o
p
ti
m
a
l
c
o
n
tro
l
d
e
sig
n
"
In
te
rn
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
S
c
ien
ti
fi
c
&
En
g
in
e
e
rin
g
Res
e
a
rc
h
,
v
o
l.
6
,
n
o
.
7
,
2
0
1
5
.
[2
3
]
Y.
R.
P
r
a
jap
a
ti
a
n
d
S
.
Y
.
P
ra
ja
p
a
ti
,
"
A
sin
g
le
a
re
a
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
(L
F
C):
Co
m
p
a
ra
ti
v
e
stu
d
y
b
a
se
d
o
n
in
teg
ra
l
a
n
d
f
u
z
z
y
lo
g
ic
c
o
n
tro
ll
e
r
,"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
L
a
t
e
st
T
e
c
h
n
o
l
o
g
y
in
En
g
in
e
e
rin
g
,
M
a
n
a
g
e
me
n
t
&
Ap
p
li
e
d
S
c
ie
n
c
e
(
IJ
L
T
EM
AS
)
,
v
o
l
.
5
,
n
o
.
1
,
2
0
1
6
.
[2
4
]
M
.
A
.
T
a
m
m
a
m
,
M
.
A
.
S
.
A
b
o
e
lela
,
M
.
A
.
M
o
u
sta
f
a
a
n
d
A
.
E
.
A
.
S
e
if
,
"
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tr
o
ll
e
r
d
e
sig
n
f
o
r
in
terc
o
n
n
e
c
ted
e
lec
tri
c
p
o
w
e
r
s
y
ste
m
,"
In
Pro
c
e
e
d
in
g
s
o
f
t
h
e
5
5
th
A
n
n
u
a
l
Po
we
r
In
d
u
stry
d
ivi
sio
n
S
y
mp
o
siu
m
POW
ID
,
2
0
1
2
.
[2
5
]
A
h
m
e
d
Hu
ss
e
in
,
S
.
S
a
d
e
e
m
S
a
li
h
a
n
d
Y.
G
h
a
z
i
G
h
a
s
m
,
"
I
m
p
le
m
e
n
tatio
n
o
f
p
ro
p
o
rti
o
n
a
l
-
i
n
teg
ra
l
-
o
b
se
rv
e
r
tec
h
n
iq
u
e
s
f
o
r
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
p
o
w
e
r
s
y
ste
m
,"
In
th
e
Pr
o
c
e
e
d
in
g
s
o
f
T
h
e
7
th
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
S
u
sta
in
a
b
le E
n
e
rg
y
In
fo
rm
a
t
io
n
T
e
c
h
n
o
l
o
g
y
,
2
0
1
7
.
[2
6
]
H.
El
a
y
d
i
a
n
d
M
.
W
a
d
i,
"
Op
ti
m
a
l
c
o
n
tro
l
ler
f
o
r
sin
g
le
a
re
a
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
v
ia
lq
r
a
n
d
l
e
g
e
n
d
re
w
a
v
e
let
f
u
n
c
t
io
n
,"
J
o
u
rn
a
l
o
f
Au
to
ma
ti
o
n
a
n
d
Co
n
tro
l
,
v
o
l.
3
,
n
o
.
2
,
p
p
.
43
-
4
7
,
2
0
1
5
.
[2
7
]
K.
S
.
S
.
Ra
m
a
k
rish
n
a
a
n
d
T
.
S
.
B
h
a
tt
i,
"
A
u
to
m
a
ti
c
g
e
n
e
ra
ti
o
n
c
o
n
t
ro
l
o
f
sin
g
le
a
re
a
p
o
w
e
r
s
y
ste
m
with
m
u
lt
i
-
so
u
rc
e
p
o
w
e
r
g
e
n
e
ra
ti
o
n
,"
Pro
c
e
e
d
in
g
s
o
f
th
e
I
n
stit
u
ti
o
n
o
f
M
e
c
h
a
n
ic
a
l
En
g
i
n
e
e
rs
Pa
rt
A:
J
o
u
rn
a
l
o
f
Po
we
r
a
n
d
E
n
e
rg
y
v
o
l.
2
2
2
,
n
o
.
1
,
p
p
.
1
-
1
1
,
2
0
0
8
.
[2
8
]
S
.
Da
s,
Fu
n
c
ti
o
n
a
l
fra
c
ti
o
n
a
l
c
a
lcu
lu
s
,
S
p
ri
n
g
e
r
S
c
ien
c
e
&
Bu
sin
e
s
s M
e
d
ia
,
2
0
1
1
.
[2
9
]
K.
B.
Old
h
a
m
a
n
d
J.
S
p
a
n
ier,
T
h
e
fra
c
ti
o
n
a
l
c
a
lcu
l
u
s:
T
h
e
o
ry
a
n
d
a
p
p
li
c
a
ti
o
n
s
o
f
d
if
fer
e
n
t
ia
ti
o
n
a
n
d
in
teg
r
a
ti
o
n
t
o
a
rb
it
ra
ry
o
rd
e
r
,
Un
it
e
d
S
tate
s: Do
v
e
r
P
u
b
l
ica
ti
o
n
s
,
2
0
0
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t,
Vo
l.
9
,
No
.
1
,
Ma
r
ch
2
0
2
0
:
8
3
–
92
92
[3
0
]
Zam
a
n
i
A
,
S
.
M
.
Ba
r
a
k
a
ti
a
n
d
S
.
Yo
u
so
f
i
-
Da
r
m
ian
,
"
De
si
g
n
o
f
a
f
ra
c
ti
o
n
a
l
o
rd
e
r
P
ID
c
o
n
tr
o
ll
e
r
u
sin
g
G
BM
O
a
lg
o
rit
h
m
f
o
r
lo
a
d
-
f
re
q
u
e
n
c
y
c
o
n
t
ro
l
w
it
h
g
o
v
e
rn
o
r
sa
tu
ra
ti
o
n
c
o
n
si
d
e
ra
ti
o
n
,"
IS
A
T
r
a
n
s.
,
v
o
l.
6
4
,
p
p
.
5
6
-
6
6
,
2
0
1
6
.
[3
1
]
P
a
n
a
n
d
S
.
Da
s,
"
F
ra
c
ti
o
n
a
l
o
r
d
e
r
lo
a
d
-
f
re
q
u
e
n
c
y
c
o
n
tro
l
o
f
in
t
e
rc
o
n
n
e
c
ted
p
o
w
e
r
s
y
ste
m
s
u
sin
g
c
h
a
o
ti
c
m
u
lt
i
-
o
b
jec
ti
v
e
o
p
ti
m
iza
ti
o
n
,"
J
o
u
rn
a
l
o
f
A
p
p
li
e
d
S
o
ft
C
o
mp
u
ti
n
g
,
v
o
l.
2
9
,
p
p
.
3
2
8
-
3
4
4
,
2
0
1
5
.
[3
2
]
S
.
A
.
T
a
h
e
r,
M.
H.
F
in
i,
a
n
d
S
F
.
A
li
a
b
a
d
i,
"
F
ra
c
ti
o
n
a
l
-
o
rd
e
r
P
ID
c
o
n
tro
l
ler
d
e
sig
n
f
o
r
L
F
C
i
n
e
lec
tri
c
p
o
w
e
r
s
y
ste
m
s u
sin
g
im
p
e
rialist
c
o
m
p
e
ti
ti
v
e
a
lg
o
rit
h
m
,"
Ai
n
S
h
a
ms
En
g
in
e
e
rin
g
J
o
u
r
n
a
l
,
v
o
l.
5
,
n
o
.
1
,
p
p
.
121
-
1
3
5
,
2
0
1
4
.
[3
3
]
M
.
R.
Da
stra
n
j,
M
.
Ro
u
h
a
n
i,
a
n
d
A
.
Ha
ji
p
o
o
r,
"
De
sig
n
o
f
o
p
ti
m
a
l
f
ra
c
ti
o
n
a
l
o
rd
e
r
P
ID
c
o
n
tr
o
ll
e
r
u
sin
g
P
S
O
a
lg
o
rit
h
m
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
C
o
mp
u
ter
T
h
e
o
ry
a
n
d
E
n
g
i
n
e
e
rin
g
,
p
p
.
4
2
9
-
4
3
2
,
2
0
1
2
.
[3
4
]
J.
Y.
Ca
o
,
J.
L
ian
g
,
a
n
d
B.
G
.
Ca
o
,
"
Op
ti
m
iza
ti
o
n
o
f
f
ra
c
ti
o
n
a
l
-
o
r
d
e
r
P
ID
c
o
n
tro
l
l
e
rs
b
a
se
d
o
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
s,
"
4
th
I
EE
E
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
a
c
h
in
e
L
e
a
rn
in
g
a
n
d
Cy
b
e
r
n
e
ti
c
s
,
v
o
l.
9
,
p
p
.
5
6
8
6
-
5
6
8
9
,
2
0
0
5
.
[3
5
]
S
.
M
.
Ka
m
a
li
Na
ll
a
d
u
ra
i
A
n
d
R.
S
.
D.
W
a
h
id
a
Ba
n
u
,
"
L
F
C
o
f
t
wo
in
terc
o
n
n
e
c
ted
p
o
w
e
r
s
y
ste
m
u
sin
g
in
telli
g
e
n
t
c
o
n
tro
ll
e
r
m
e
th
o
d
,"
U.P
.
B
.
S
c
i.
B
u
ll
.
,
S
e
rie
s C
, v
o
l.
7
7
,
n
o
.
1
,
2
0
1
5
.
[3
6
]
C.
L
u
c
a
s,
D.
S
h
a
h
m
irza
d
i,
a
n
d
N.
S
h
e
ik
h
o
les
lam
i,
"
In
tro
d
u
c
in
g
BE
L
BIC:
Bra
in
e
m
o
ti
o
n
a
l
lea
rn
in
g
b
a
se
d
in
telli
g
e
n
t
c
o
n
tro
ll
e
r,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
I
n
telli
g
e
n
t
A
u
to
m
a
ti
o
n
a
n
d
S
o
f
t
Co
mp
u
ti
n
g
,
v
o
l.
1
0
,
p
p
.
1
1
-
2
2
,
2
0
0
4
.
[3
7
]
F
.
Xu
e
,
Y.
Ca
i,
Y.
Ca
o
,
Z.
Cu
i
a
n
d
F
.
L
i,
"
Op
ti
m
a
l
p
a
ra
m
e
ter
se
tt
in
g
s
f
o
r
b
a
t
a
lg
o
rit
h
m
,"
In
t.
J
.
Bi
o
-
In
sp
ire
d
Co
mp
u
t
a
ti
o
n
, v
o
l.
7
,
n
o
.
2
,
2
0
1
5
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
M
a
g
d
y
A
.
S
.
ABO
EL
E
LA
h
a
s
b
e
e
n
g
ra
d
u
a
ted
f
ro
m
th
e
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
d
e
p
a
rtm
e
n
t
(P
o
w
e
r
a
n
d
M
a
c
h
i
n
e
s
se
c
ti
o
n
)
in
th
e
f
a
c
u
lt
y
o
f
e
n
g
in
e
e
rin
g
a
t
Ca
iro
Un
iv
e
rsity
w
it
h
Distin
c
ti
o
n
a
n
d
h
o
n
o
r
d
e
g
re
e
in
1
9
7
7
.
He
re
c
e
iv
e
d
h
is
M
.
S
c
.
d
e
g
re
e
in
a
u
t
o
m
a
ti
c
c
o
n
tro
l
f
r
o
m
Ca
iro
Un
iv
e
rsity
in
1
9
8
1
.
He
re
c
e
iv
e
d
h
is
P
h
.
D.
i
n
c
o
m
p
u
ter
a
id
e
d
sy
ste
m
e
n
g
in
e
e
rin
g
f
ro
m
th
e
sta
te
u
n
iv
e
rsity
o
f
G
h
e
n
t,
Be
l
g
iu
m
in
1
9
8
9
.
He
w
a
s
in
v
o
lv
e
d
i
n
th
e
M
IT
/CU
tec
h
n
o
lo
g
ica
l
p
lan
n
in
g
p
ro
g
ra
m
f
ro
m
1
9
7
8
t
o
1
9
8
4
.
He
h
a
s
b
e
e
n
a
p
p
o
i
n
te
d
a
s
d
e
m
o
n
stra
t
o
r,
a
ss
istan
t
p
ro
f
e
ss
o
r,
lec
tu
re
r,
a
ss
o
c
iate
p
ro
f
e
ss
o
r
a
n
d
p
ro
f
e
ss
o
r
a
ll
a
t
Ca
iro
Un
iv
e
rsity
w
h
e
r
e
h
e
i
s
c
u
rre
n
tl
y
e
n
ro
ll
e
d
.
He
h
a
s
g
iv
e
n
c
o
n
su
lt
a
n
c
y
in
in
f
o
r
m
a
ti
o
n
tec
h
n
o
lo
g
y
a
n
d
c
o
m
p
u
ter
sc
ien
c
e
m
a
in
ly
f
o
r
CA
P
S
a
u
d
i
A
ra
b
ia,
S
DA
En
g
in
e
e
rin
g
Ca
n
a
d
a
,
Je
ra
is
y
Co
m
p
u
ter
a
n
d
Co
m
m
u
n
ica
ti
o
n
S
e
rv
ice
s
a
n
d
o
th
e
r
in
stit
u
ti
o
n
s.
He
h
a
s
b
e
e
n
a
p
p
o
in
ted
a
s
a
v
isit
in
g
p
ro
f
e
ss
o
r
a
t
Ca
se
W
e
ste
rn
Re
se
r
v
e
Un
iv
e
r
sity
(US
A
),
Un
il
o
rin
u
n
iv
e
rsity
(
Nig
e
ria)
a
n
d
S
u
lt
a
n
Qa
b
o
o
s
Un
iv
e
rsit
y
(O
m
a
n
).
His
in
tere
st
is
A
rti
f
icia
l
In
telli
g
e
n
c
e
,
Au
to
m
a
ti
c
Co
n
tr
o
l
S
y
ste
m
s,
S
to
c
h
a
stic
M
o
d
e
ll
i
n
g
a
n
d
S
im
u
latio
n
,
Da
tab
a
se
,
De
c
isio
n
S
u
p
p
o
rt
S
y
ste
m
s,
M
a
n
a
g
e
m
e
n
t
In
f
o
rm
a
ti
o
n
S
y
ste
m
s,
a
n
d
A
p
p
li
c
a
ti
o
n
o
f
Co
m
p
u
ter
tec
h
n
o
lo
g
y
in
In
d
u
stry
.
He
h
a
s
p
u
b
li
sh
e
d
m
o
re
th
a
n
7
5
sc
ien
ti
f
ic article
s in
jo
u
r
n
a
ls an
d
c
o
n
f
e
re
n
c
e
p
ro
c
e
e
d
i
n
g
s.
Evaluation Warning : The document was created with Spire.PDF for Python.