I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
,
p
p
.
1
4
1
0
~
1
4
1
8
I
SS
N:
2
5
0
2
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
23
.i
3
.
pp
141
0
-
1
4
1
8
1410
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Desig
n of f
ra
c
tion
a
l order PID
cont
ro
ller f
o
r
AVR sy
stem using
wha
le optimiza
tio
n alg
o
rithm
L
a
y
la
H
.
Abo
o
d,
B
a
s
hra
K
a
dh
im
O
leiwi
De
p
a
rtme
n
t
o
f
Co
n
t
o
l
a
n
d
S
y
ste
m
En
g
i
n
e
e
rin
g
,
Un
i
v
e
rsity
o
f
Tec
h
n
o
lo
g
y
,
Ira
q
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Mar
22
,
2
0
2
1
R
ev
is
ed
J
u
l
24
,
2
0
2
1
Acc
ep
ted
J
u
l
28
,
2
0
2
1
In
th
is
p
a
p
e
r
a
ro
b
u
st
fra
c
ti
o
n
a
l
o
rd
e
r
P
ID
(F
OPID)
c
o
n
tr
o
ll
e
r
is
p
r
o
p
o
se
d
to
c
o
n
tro
l
th
e
a
u
to
m
a
ti
c
v
o
lt
a
g
e
r
e
g
u
lato
r
(AV
R)
sy
ste
m
,
th
e
t
u
n
in
g
o
f
t
h
e
c
o
n
tro
ll
e
r
g
a
i
n
s
a
re
d
o
n
e
u
si
n
g
wh
a
le
o
p
ti
m
iza
ti
o
n
a
l
g
o
rit
h
m
(
WOA)
a
n
d
in
teg
ra
l
t
ime
a
b
so
l
u
te
e
rro
r
(IT
AE)
c
o
st
f
u
n
c
ti
o
n
is
a
d
o
p
ted
to
a
c
h
iev
e
a
n
e
fficie
n
t
p
e
rfo
rm
a
n
c
e
.
T
h
e
tran
si
e
n
t
a
n
a
ly
sis
wa
s
d
o
n
e
a
n
d
c
o
m
p
a
re
d
with
c
o
n
v
e
n
ti
o
n
a
l
P
ID
i
n
term
s
o
f
o
v
e
rsh
o
o
t,
se
tt
li
n
g
ti
m
e
,
rise
ti
m
e
,
a
n
d
p
e
a
k
ti
m
e
to
e
x
p
lai
n
t
h
e
su
p
e
ri
o
rit
y
o
f
t
h
e
p
r
o
p
o
se
d
c
o
n
tro
l
ler.
F
in
a
ll
y
,
a
ro
b
u
stn
e
ss
a
n
a
ly
sis is
d
o
n
e
b
y
a
d
d
in
g
e
x
ter
n
a
l
d
istu
r
b
a
n
c
e
s
to
th
e
sy
ste
m
a
n
d
ch
a
n
g
i
n
g
t
h
e
sy
ste
m
p
a
ra
m
e
ter
s
b
y
±
2
0
%
fro
m
it
s
o
ri
g
i
n
a
l
v
a
lu
e
,
th
e
c
o
n
tro
ll
e
r
o
v
e
rc
o
m
e
s
th
e
d
ist
u
rb
a
n
c
e
s
sig
n
a
ls
with
les
s
th
a
n
0
.
2
5
s
a
n
d
fa
c
e
s
th
e
c
h
a
n
g
e
s
o
f
t
h
e
sy
ste
m
v
a
lu
e
s
a
n
d
re
tu
rn
i
n
g
t
h
e
re
sp
o
n
se
wit
h
in
(
0
.7
-
1)
se
c
a
n
d
led
th
e
sy
ste
m
to
th
e
d
e
sire
d
re
sp
o
n
se
e
fficie
n
tl
y
.
Th
e
n
u
m
e
rica
l
sim
u
latio
n
s
sh
o
we
d
t
h
a
t
th
e
sm
a
rt
WOA
o
ffe
rs
sa
ti
sfy
in
g
re
su
lt
s
a
n
d
fa
ste
r
re
sp
o
n
se
re
flec
ted
c
lea
rly
o
n
t
h
e
ro
b
u
st
a
n
d
sta
b
le
p
e
rfo
rm
a
n
c
e
o
f
t
h
e
p
ro
p
o
se
d
c
o
n
tr
o
ll
e
r
in
imp
ro
v
i
n
g
th
e
tra
n
sie
n
t
a
n
a
ly
sis
o
f
A
VR
sy
ste
m
re
sp
o
n
se
.
K
ey
w
o
r
d
s
:
AVR s
y
s
tem
Fra
ctio
n
al
o
r
d
er
co
n
tr
o
ller
s
W
h
ale
o
p
tim
izatio
n
alg
o
r
ith
m
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
:
L
ay
la
H.
Ab
o
o
d
Dep
ar
tm
en
t o
f
C
o
n
tr
o
l a
n
d
Sy
s
tem
E
n
g
in
ee
r
in
g
Un
iv
er
s
ity
o
f
T
ec
h
n
o
lo
g
y
B
ag
h
d
ad
,
I
r
aq
E
m
ail:
6
0
0
6
6
@
u
o
tech
n
o
l
o
g
y
.
ed
u
.
iq
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
s
y
s
tem
o
f
s
u
p
p
ly
in
g
p
o
w
er
n
etwo
r
k
v
o
ltag
es
h
as
a
n
o
m
in
al
v
alu
e
lev
el.
A
n
y
d
if
f
er
en
ce
in
th
is
s
u
p
p
lied
v
o
ltag
e
v
alu
e
will c
au
s
e
an
in
f
lu
en
ce
in
th
e
d
y
n
am
i
cs o
f
all
p
o
wer
n
etwo
r
k
s
d
is
tr
ib
u
ted
.
T
h
is
ca
s
e
o
f
ch
an
g
in
g
v
alu
es
will
r
ef
lect
o
n
th
e
s
y
s
tem
's
p
er
f
o
r
m
an
ce
a
n
d
its
lo
n
g
ev
ity
.
T
h
e
ef
f
ec
t
will
ap
p
ea
r
clea
r
ly
o
n
th
e
p
o
we
r
an
d
f
in
ally
o
n
th
e
r
ea
l
s
y
s
tem
s
u
p
p
ly
in
g
d
esire
d
v
o
ltag
es.
T
o
o
v
er
co
m
e
th
is
m
atter
,
an
au
to
m
ati
c
v
o
ltag
e
r
eg
u
lato
r
(
AVR)
is
ap
p
lied
[
1
]
,
[
2
]
.
As
its
n
am
e
r
ef
er
r
in
g
,
AVR
is
a
d
ev
ice
u
s
ed
in
g
en
er
atio
n
s
tatio
n
s
th
at
s
u
p
p
o
r
t
th
e
v
o
ltag
e
v
alu
e
lev
els
as
wan
ted
v
al
u
es
in
s
p
ite
o
f
an
y
v
ar
iatio
n
t
h
at
m
ay
o
cc
u
r
r
b
y
s
tab
ilizin
g
th
e
v
o
ltag
e
v
alu
e
in
th
e
ex
citatio
n
p
ar
t,
th
e
n
c
o
n
tr
o
llin
g
ex
citatio
n
v
o
ltag
e
v
alu
e
will
lead
t
o
r
eg
u
late
th
e
o
u
tp
u
t
g
e
n
er
atin
g
v
o
ltag
e
as
d
esire
d
v
al
u
es
to
ac
h
iev
e
a
s
tab
le
an
d
r
eliab
l
e
v
o
ltag
e
s
u
p
p
l
y
in
g
s
y
s
tem
[
3
]
.
T
h
e
AVR
s
u
f
f
er
s
f
r
o
m
s
o
m
e
p
o
in
ts
th
at
ap
p
ea
r
e
d
in
its
o
u
t
p
u
t
r
esp
o
n
s
e
lik
e
o
s
cillatio
n
,
o
v
er
s
h
o
o
t,
an
d
an
er
r
o
r
in
its
v
alu
e
in
th
e
s
tead
y
s
tate,
s
o
f
o
r
s
o
lv
in
g
all
th
ese
p
o
in
ts
a
clo
s
ed
lo
o
p
with
an
ef
f
icien
t
co
n
tr
o
ller
will
r
em
o
v
e
t
h
ese
u
n
d
esire
d
v
al
u
es
s
o
it
ca
n
b
e
s
ee
n
th
at
m
an
y
r
esear
ch
er
s
p
r
o
p
o
s
ed
d
if
f
er
e
n
t
co
n
tr
o
llin
g
a
p
p
r
o
ac
h
es
to
r
ea
ch
to
s
tab
ilit
y
in
r
esp
o
n
s
e
an
d
r
o
b
u
s
tn
ess
in
th
e
b
eh
a
v
io
r
o
f
AVR
s
y
s
tem
[
4
]
,
lik
e
u
s
in
g
th
e
class
ical
PID
co
n
tr
o
ller
with
n
ew
o
p
tim
izatio
n
m
eth
o
d
t
o
tu
n
e
its
g
ai
n
f
o
r
r
ea
ch
in
g
t
o
ac
cu
r
ate
an
d
s
u
itab
le
v
alu
e
th
at
d
r
iv
e
s
s
tab
le
r
esp
o
n
s
e,
in
[
5
]
r
es
ea
r
ch
er
a
p
p
ly
th
r
ee
o
p
tim
iza
tio
n
m
eth
o
d
w
h
ale
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Desig
n
o
f fra
c
tio
n
a
l o
r
d
er P
I
D
co
n
tr
o
ller
fo
r
A
V
R
s
ystem
…
(
La
yla
H.
A
b
o
o
d
)
1411
o
p
tim
izatio
n
(
W
O)
,
s
y
m
b
io
tic
o
r
g
an
is
m
s
ea
r
ch
(
SOS),
p
a
r
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
an
d
f
in
ally
h
y
b
r
id
b
etwe
en
PS
O
-
SOS
tu
n
in
g
m
eth
o
d
s
,
f
in
ally
co
m
p
ar
ed
b
etwe
en
all
th
ese
m
eth
o
d
s
to
ch
o
o
s
e
th
e
b
est
o
f
th
em
also
in
[
6
]
-
[
9
]
th
e
PID
co
n
tr
o
ller
with
d
if
f
er
e
n
t
o
p
tim
izatio
n
m
eth
o
d
is
u
s
ed
t
o
tu
n
e
th
e
g
ain
s
f
o
r
a
s
tab
le
d
esire
d
r
esp
o
n
s
e,
wh
ile
in
[
1
0
]
-
[
1
4
]
s
u
g
g
est
a
co
n
tr
o
ller
with
an
im
p
r
o
v
em
en
t
in
its
s
tr
u
c
tu
r
e
d
ep
en
d
in
g
o
n
th
e
m
ath
em
atics
o
f
f
r
ac
tio
n
al
ca
lcu
lu
s
ca
lled
f
r
ac
tio
n
al
o
r
d
e
r
PID
(
FOPID)
wh
ich
ac
h
iev
e
ef
f
icien
t
r
esp
o
n
s
e
as
co
m
p
ar
ed
with
o
th
er
c
o
n
tr
o
ller
s
.
I
n
[
1
5
]
a
co
m
b
i
n
atio
n
b
etwe
en
Fu
zz
y
an
d
PID
co
n
tr
o
ller
is
ap
p
lied
in
a
way
o
f
co
m
b
in
e
f
u
zz
y
with
p
r
o
p
o
r
tio
n
al
(
FP
)
a
n
d
f
u
zz
y
wit
h
in
teg
r
ati
o
n
(
FI)
a
n
d
f
u
zz
y
w
ith
d
if
f
er
en
tial
(
FD)
to
b
e
(
FP
+
FI
+
FD)
,
th
en
f
o
r
r
ea
ch
in
g
r
o
b
u
s
t
r
esp
o
n
s
e
a
g
en
etic
alg
o
r
ith
m
(
GA)
is
co
m
b
in
ed
with
an
d
PS
O
(
HGAPSO)
i
s
ad
o
p
ted
wh
ile
in
[
1
6
]
a
two
r
o
b
u
s
t
m
eth
o
d
i
s
u
s
ed
to
r
eg
u
late
th
e
AVR
r
esp
o
n
s
e,
f
u
zz
y
an
d
f
u
zz
y
ty
p
e2
with
PI
co
n
tr
o
ller
is
p
r
o
p
o
s
ed
th
e
n
u
s
ed
d
if
f
e
r
en
t
tu
n
in
g
m
eth
o
d
s
to
a
d
ju
s
t
th
e
v
alu
es
o
f
th
e
co
n
tr
o
ller
g
ai
n
s
to
ac
h
iev
e
s
tab
le
r
esp
o
n
s
e
an
d
f
in
ally
co
m
p
ar
e
b
etwe
en
th
e
m
to
f
in
d
t
h
e
s
u
itab
le
way
th
at
ac
h
iev
es r
o
b
u
s
tn
ess
an
d
f
ast d
esire
d
r
esp
o
n
s
e.
T
h
e
co
n
tr
ib
u
tio
n
o
f
t
h
is
p
ap
er
is
th
e
u
s
e
o
f
W
OA
f
o
r
tu
n
i
n
g
o
f
FOPID
co
n
t
r
o
ller
p
ar
am
eter
s
.
T
h
is
m
eth
o
d
h
as
a
u
n
iq
u
e
an
d
s
m
ar
t
s
ea
r
ch
an
aly
s
is
also
h
av
e
less
p
ar
am
eter
wh
en
ap
p
lied
th
en
g
iv
e
f
ast
an
d
ac
cu
r
ate
r
esu
lts
o
f
FOPID
c
o
n
tr
o
ller
p
ar
a
m
eter
s
,
als
o
th
e
FOPID
co
n
tr
o
ller
with
it
s
f
iv
e
d
esig
n
cr
iter
ia
(
P
,
I
,
D
,
λ
,
)
g
iv
e
a
h
ig
h
d
e
g
r
ee
o
f
f
r
ee
d
o
m
wh
en
tu
n
n
in
g
its
p
ar
am
ete
r
s
th
en
th
e
ch
ar
ac
ter
is
tics
o
f
tim
e
r
esp
o
n
s
e
f
o
r
FOPID
co
n
tr
o
lle
r
is
co
m
p
ar
ed
with
class
ical
PID
co
n
tr
o
ller
an
d
with
o
th
e
r
co
n
t
r
o
ller
s
tu
n
e
d
with
d
if
f
er
en
t
o
p
tim
izatio
n
m
eth
o
d
s
,
f
in
ally
d
is
cu
s
s
th
e
co
n
tr
o
ller
r
o
b
u
s
tn
ess
b
ased
o
n
p
a
r
am
eter
u
n
ce
r
tain
ty
an
d
e
x
ter
n
al
d
is
tu
r
b
an
ce
s.
T
h
e
r
est
o
f
th
is
p
ap
er
is
ar
r
an
g
e
d
as
s
h
o
w
n
in
:
Sectio
n
2
p
r
es
en
ts
th
e
m
o
d
elin
g
o
f
th
e
AVR
s
y
s
tem
,
Sectio
n
3
ex
p
lai
n
s
th
e
FOPID
co
n
tr
o
ller
an
d
in
Sectio
n
4
th
e
p
r
o
p
o
s
e
d
W
OA
m
eth
o
d
is
d
em
o
n
s
tr
ated
.
Sectio
n
5
a
s
im
u
latio
n
an
d
d
is
cu
s
s
io
n
r
esu
lts
ar
e
r
ep
o
r
ted
an
d
in
Sectio
n
6
a
r
o
b
u
s
tn
ess
an
aly
s
is
is
ex
p
lain
ed
an
d
f
in
al
ly
,
in
S
ec
tio
n
7
a
co
n
cl
u
s
io
n
o
f
th
e
s
tu
d
y
is
d
is
cu
s
s
ed
.
2.
AVR
SYS
T
E
M
M
O
DE
L
I
N
G
T
h
e
AVR
s
y
s
tem
co
m
p
r
is
es
o
f
f
o
u
r
p
ar
ts
with
n
am
es
am
p
lifie
r
,
ex
citer
,
g
e
n
er
ato
r
,
an
d
s
en
s
o
r
p
ar
ts
all
th
ese
p
ar
ts
co
n
s
is
t
o
f
a
tr
a
n
s
f
er
f
u
n
ctio
n
with
f
ir
s
t
o
r
d
er
ty
p
e
as
in
d
icate
d
in
Fig
u
r
e
1
.
T
h
e
p
ar
am
eter
s
(
T
an
d
k
)
ar
e
th
e
tim
e
an
d
g
ain
c
o
n
s
tan
ts
th
at
ar
e
k
n
o
wn
f
o
r
ea
c
h
tr
an
s
f
er
f
u
n
ctio
n
s
p
a
r
t
o
f
th
e
AVR
s
y
s
tem
.
T
h
e
v
alu
es
o
f
th
ese
co
n
s
tan
ts
u
s
ed
in
th
is
s
tu
d
y
ar
e
lis
ted
in
T
ab
le
1
[
1
7
]
-
[
1
9
]
:
Fig
u
r
e
1
.
AVR s
y
s
tem
b
lo
ck
d
iag
r
am
T
ab
le
1
.
T
h
e
p
er
f
o
r
m
a
n
ce
v
al
u
es o
f
AVR p
ar
ts
A
V
R
P
a
r
t
P
a
r
a
me
t
e
r
V
a
l
u
e
A
mp
l
i
f
i
e
r
Ka
1
0
.
0
Ta
0
.
1
Ex
c
i
t
e
r
Ke
1
Te
0
.
4
G
e
n
e
r
a
t
o
r
Kg
1
Tg
1
S
e
n
s
o
r
Ks
1
Ts
0
.
0
1
T
h
en
th
e
clo
s
ed
lo
o
p
tr
an
s
f
er
f
u
n
ctio
n
will b
e
[
5
]
:
∆
(
)
∆
(
)
=
0
.
1
+
10
0
.
0004
4
+
0
.
0454
3
+
0
.
555
2
+
1
.
51
+
11
(
1
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
4
1
0
-
1
4
1
8
1412
3.
F
RACTI
O
N
AL
O
RD
E
R
P
I
D
CO
NT
RO
L
L
E
R
T
h
is
co
n
tr
o
ller
is
an
en
h
a
n
ce
d
f
o
r
m
o
f
c
lass
ical
PID
co
n
tr
o
ller
b
ec
au
s
e
it
d
e
p
en
d
s
o
n
th
e
f
r
ac
tio
n
al
v
alu
e
o
f
two
PID
p
ar
am
eter
s
(
d
er
iv
ativ
e
an
d
in
teg
r
al
)
in
s
tead
o
f
in
te
g
er
v
al
u
es,
th
is
f
r
ac
tio
n
al
p
ar
am
eter
is
(
an
d
λ
)
d
u
e
t
o
th
is
th
e
tu
n
in
g
p
ar
am
eter
will
b
e
f
iv
e
in
s
tead
o
f
th
r
ee
,
th
e
e
x
tr
a
p
ar
am
eter
s
will
en
s
u
r
e
r
o
b
u
s
tn
ess
in
th
e
r
esp
o
n
s
e
o
f
th
e
s
y
s
tem
an
d
im
p
r
o
v
e
its
p
er
f
o
r
m
a
n
ce
.
T
h
e
tr
a
n
s
f
er
f
u
n
c
tio
n
o
f
th
e
FOPID
co
n
tr
o
ller
will b
e
as sh
o
wn
:
F
O
PID
=
P
+
I
1
λ
+
D
(
2
)
T
h
e
tu
n
n
i
n
g
p
a
r
am
eter
s
will b
e
(
P
,
I
,
D
,
λ
,
)
.
T
h
e
v
alu
e
o
f
th
e
two
f
r
ac
tio
n
al
p
ar
am
ete
r
s
λ
an
d
μ
ca
n
b
e
r
ea
l o
r
in
teg
er
s
.
,
if
λ
=1
,
μ
=1
th
en
a
class
ical
PID
i
s
o
b
tain
ed
b
u
t if
o
n
e
o
f
t
h
em
i
s
1
an
d
th
e
o
th
er
is
0
th
en
it b
e
a
class
ical
PI
co
n
tr
o
ller
(
if
λ
=1
,
μ
=0
)
an
d
class
ical
PD c
o
n
tr
o
ller
(
if
λ
=
0
,
μ
=
1
)
r
esp
ec
tiv
ely
.
T
h
e
FOPID
co
n
tr
o
ller
b
l
o
ck
d
iag
r
am
is
ex
p
lain
ed
in
Fig
u
r
e
2
[
2
0
]
,
[
2
1
]
.
Fig
u
r
e
2
.
FOPID
co
n
tr
o
ller
b
l
o
ck
d
iag
r
am
4.
WH
AL
E
O
P
T
I
M
I
Z
A
T
I
O
N
AL
G
O
RI
T
H
M
T
h
e
wle
o
p
tim
izatio
n
alg
o
r
ith
m
is
an
in
tellig
en
t
m
eth
o
d
p
r
esen
ted
b
y
Mir
jili
li
an
d
L
ewis
[
2
2
]
,
[
2
3
]
,
it
tr
an
s
lates
th
e
b
io
lo
g
ical
b
eh
av
io
r
o
f
wh
ales
wh
en
f
in
d
in
g
th
eir
p
r
ey
,
th
ey
h
av
e
a
s
p
ec
ial
s
tr
ateg
y
in
h
u
n
tin
g
th
e
s
m
all
f
is
h
es
o
n
th
e
s
ea
s
u
r
f
ac
e
b
y
g
e
n
er
atin
g
s
p
ec
if
ic
b
u
b
b
les
with
a
cir
cu
lar
p
ath
th
en
th
e
h
u
n
tin
g
p
r
o
ce
s
s
is
d
o
n
e
in
th
r
ee
s
tep
s
as
s
h
o
wn
in
:
1
-
E
n
cir
clin
g
p
r
a
y
:
T
h
e
wh
ale
ca
n
s
p
ec
if
y
th
e
ar
ea
o
f
th
e
p
r
e
y
a
n
d
th
en
s
tar
t
to
en
cir
cle
th
em
.
W
OA
ca
n
n
o
t
ex
p
ec
t
th
e
p
lace
d
ir
ec
tly
,
th
e
W
OA
ex
p
ec
ts
th
at
th
e
o
p
tim
u
m
p
ath
o
b
tain
ed
f
o
r
f
in
d
i
n
g
th
e
p
r
e
y
s
o
f
ar
is
th
e
o
p
tim
al
s
o
lu
t
io
n
o
r
n
ea
r
b
y
,
th
e
n
th
e
o
th
er
wh
ales
tr
y
to
u
p
d
ate
th
eir
p
lace
s
b
ased
o
n
p
r
ey
lo
ca
tio
n
(
b
est p
ath
f
o
u
n
d
)
.
T
h
is
s
tep
is
d
escr
ib
ed
as sh
o
wn
:
⃗
⃗
=|
.
∗
⃗
⃗
⃗
⃗
-
(
)
|
(
3
)
(
+
1
)
=
∗
⃗
⃗
⃗
⃗
(
)
−
.
⃗
⃗
⃗
⃗
⃗
(
4
)
T
h
e
r
elatio
n
f
o
r
ca
lcu
late
th
e
c
o
ef
f
icien
t
v
ec
to
r
s
an
d
ar
e:
=
2
.
⃗
⃗
⃗
−
(
5
)
=
2
.
(
6
)
W
h
er
e
is
a
r
an
d
o
m
v
alu
e
v
e
cto
r
[
0
,
1
]
an
d
h
as
a
v
alu
e
f
r
o
m
2
to
0
an
d
it
is
r
ed
u
ce
d
lin
ea
r
ly
d
u
r
in
g
t
h
e
iter
atio
n
s
o
f
th
e
s
e
ar
ch
.
Var
io
u
s
p
o
s
itio
n
s
n
ea
r
th
e
b
est
p
o
s
itio
n
ca
n
b
e
o
b
tain
ed
b
ased
o
n
an
d
v
ec
to
r
s
v
alu
es
th
en
(
4
)
ca
n
b
e
u
p
d
ated
b
y
a
n
y
ag
e
n
t
n
ea
r
th
e
cu
r
r
e
n
t
b
est
p
o
s
itio
n
an
d
th
e
p
r
ey
ca
n
b
e
en
cir
cled
.
2
-
B
u
b
b
le
-
n
et
h
u
n
ti
n
g
p
r
o
ce
s
s
:
in
th
is
s
tep
,
wh
ales
s
p
ec
if
y
an
d
attac
k
th
eir
p
r
ey
b
ased
o
n
two
ap
p
r
o
ac
h
es:
th
e
f
ir
s
t
o
n
e
is
en
cir
clin
g
th
e
p
r
ey
in
s
h
r
i
n
k
in
g
m
ec
h
an
is
m
in
wh
ic
h
th
e
v
ec
to
r
v
alu
e
is
ch
an
g
ed
to
f
in
d
v
a
r
io
u
s
n
ea
r
p
o
s
itio
n
to
war
d
th
e
o
p
tim
al
wh
ale
p
ath
b
y
ch
a
n
g
in
g
⃗
⃗
⃗
v
ec
to
r
v
alu
e,
at
t
h
is
p
o
in
t
s
h
r
in
k
in
g
th
e
p
lace
s
o
f
th
e
wh
ales
to
war
d
o
p
tim
al
p
ath
is
d
o
n
e.
T
h
e
s
ec
o
n
d
s
tep
is
to
s
im
u
late
th
e
m
ec
h
a
n
is
m
o
f
th
e
b
u
b
b
le
n
et
attac
k
in
g
m
eth
o
d
,
th
e
alg
o
r
ith
m
ad
o
p
ts
a
s
p
ir
al
m
ec
h
an
is
m
f
o
r
u
p
d
atin
g
p
lace
s
th
en
f
in
d
s
th
e
d
if
f
e
r
en
ce
b
etwe
en
p
r
ey
p
lace
an
d
o
th
e
r
wh
ale'
s
p
lace
s
,
an
d
it
is
ex
p
r
ess
ed
m
ath
e
m
atica
lly
as
s
h
o
wn
b
elo
w:
(
+
1
)
=
′
⃗
⃗
⃗
⃗
⃗
.
.
(
2
+
∗
⃗
⃗
⃗
⃗
(
)
(
7
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Desig
n
o
f fra
c
tio
n
a
l o
r
d
er P
I
D
co
n
tr
o
ller
fo
r
A
V
R
s
ystem
…
(
La
yla
H.
A
b
o
o
d
)
1413
W
h
er
e
′
ex
p
lain
th
e
d
if
f
er
en
c
e
b
etwe
en
th
e
p
r
e
y
p
lace
(
n
e
ar
est
wh
ale)
an
d
th
e
ith
o
n
e
wh
ile
b
r
ep
r
esen
ts
th
e
lo
g
ar
ith
m
ic
s
p
i
r
al
s
h
ap
e
an
d
is
a
r
an
d
o
m
v
alu
e
[
-
1
,
1
]
.
No
w
to
m
im
ic
t
h
e
r
ea
l
b
e
h
av
io
r
a
p
r
o
b
a
b
ilit
y
o
f
5
0
%
is
ass
u
m
e
d
to
u
p
d
ates
wh
ales
p
lace
s
(
e
ith
er
s
h
r
in
k
i
n
g
o
r
s
p
ir
al)
m
ec
h
an
is
m
d
u
r
in
g
t
h
e
s
ea
r
ch
iter
atio
n
s
an
d
it is
ex
p
r
ess
ed
as sh
o
wn
b
elo
w:
∗
⃗
⃗
⃗
⃗
(
)
−
.
⃗
⃗
⃗
⃗
⃗
if
P<0
.
5
(
+
1
)
=
(8
)
′
⃗
⃗
⃗
⃗
⃗
.
.
(
2
+
∗
⃗
⃗
⃗
⃗
(
)
if
P ≥
0
.
5
3
-
Pre
y
s
ea
r
ch
s
tep
:
As
ex
p
lain
ed
in
th
is
alg
o
r
ith
m
wh
ales
h
av
e
a
s
p
ec
ial
an
d
u
n
iq
u
e
m
eth
o
d
f
o
r
attac
k
in
g
p
r
o
ce
s
s
,
in
t
h
e
p
r
ed
atio
n
an
o
th
er
s
p
ec
if
ic
ag
en
t
will
s
ea
r
ch
r
an
d
o
m
ly
an
d
th
e
co
ef
f
icien
t
v
ec
to
r
v
alu
e
is
ass
u
m
ed
in
th
e
r
a
n
g
e
[
-
1
,
1
]
,
d
if
f
er
e
n
t
wh
a
les
ar
e
co
m
p
elled
to
s
ea
r
ch
f
ar
f
r
o
m
th
e
r
ef
er
e
n
ce
wh
ale
to
d
etec
t
m
o
r
e
p
r
ey
.
T
h
e
u
p
d
atin
g
p
r
o
ce
s
s
n
o
w
is
d
o
n
e
b
ased
o
n
th
e
r
an
d
o
m
ly
n
ew
wh
ale
ad
o
p
ted
an
d
it
ca
n
b
e
ex
p
r
ess
ed
as sh
o
wn
:
⃗
⃗
=
|
.
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
-
(
)
|
(
9
)
(
+
1
)
=
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
−
.
⃗
⃗
⃗
⃗
⃗
(
1
0
)
w
h
e
r
e
i
s
a
r
a
n
d
o
m
w
h
a
l
e
o
b
t
a
i
n
e
d
d
u
r
i
n
g
t
h
e
s
e
a
r
c
h
p
r
o
c
e
s
s
o
f
t
h
e
c
u
r
r
e
n
t
p
o
p
u
l
a
t
i
o
n
.
T
h
e
f
l
o
w
c
h
a
r
t
o
f
W
O
A
i
s
e
x
p
l
a
i
n
e
d
i
n
F
i
g
u
r
e
3
[
2
4
]
,
[
2
5
]
.
W
O
A
a
d
o
p
t
s
a
s
e
t
o
f
r
a
n
d
o
m
n
o
m
i
n
e
e
d
e
c
i
s
i
o
n
s
(
p
o
p
u
l
a
t
i
o
n
)
a
n
d
u
t
i
l
i
z
e
s
t
h
r
e
e
s
t
e
p
s
t
o
u
p
d
a
t
e
a
n
d
m
o
d
i
f
y
t
h
e
p
l
a
c
e
o
f
n
o
m
i
n
e
e
d
e
c
i
s
i
o
n
s
i
n
e
a
c
h
s
t
e
p
,
a
s
e
x
p
l
a
i
n
e
d
a
b
o
v
e
(
E
n
c
i
r
c
l
i
n
g
,
s
e
a
r
c
h
i
n
g
t
h
e
n
f
i
n
a
l
l
y
s
p
i
r
a
l
u
p
d
a
t
i
n
g
p
l
a
c
e
s
)
,
t
h
e
f
i
r
s
t
t
w
o
s
t
e
p
s
d
e
p
e
n
d
o
n
(
P
a
n
d
|
A
|
)
p
a
r
a
m
e
t
e
r
s
a
n
d
t
h
e
f
i
n
a
l
s
t
e
p
d
e
p
e
n
d
o
n
l
y
o
n
P
p
a
r
a
m
e
t
e
r
t
o
u
p
d
a
t
e
i
t
s
p
l
a
c
e
s
t
o
a
n
o
p
t
i
m
a
l
p
a
t
h
i
n
f
i
n
d
i
n
g
p
r
e
y
.
Fig
u
r
e
3
.
Flo
wch
ar
t
o
f
W
OA
alg
o
r
ith
m
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
4
1
0
-
1
4
1
8
1414
5.
SI
M
UL
A
T
I
O
N
R
E
S
UL
T
S
I
n
th
is
s
ec
tio
n
th
e
s
im
u
latio
n
r
esu
lts
f
o
r
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
p
r
esen
ted
,
all
s
im
u
lati
o
n
is
d
o
n
e
u
s
in
g
MA
T
L
AB
/Si
m
u
lin
k
to
test
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
FOPID
co
n
tr
o
ller
b
ased
o
n
W
OA
th
en
co
m
p
ar
e
it
with
th
e
clas
s
ical
PID
co
n
tr
o
ller
wh
ich
tu
n
ed
u
s
in
g
W
OA
also
,
th
e
in
itial
p
ar
am
eter
o
f
W
OA
is
lis
ted
in
T
ab
le
2
.
T
ab
le
2
.
W
OA
Par
am
eter
s
v
a
l
u
e
D
e
scri
p
t
i
o
n
50
N
o
.
O
f
p
o
p
u
l
a
t
i
o
n
30
M
a
x
i
m
u
m
n
u
m
b
e
r
o
f
i
t
e
r
a
t
i
o
n
5
D
i
me
n
si
o
n
T
h
en
to
test
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
co
n
tr
o
ller
in
tr
ac
k
in
g
d
esire
d
o
u
tp
u
t
v
alu
e
,
a
p
er
f
o
r
m
an
ce
in
d
ex
(
f
itn
ess
f
u
n
ctio
n
)
is
u
s
ed
to
test
th
e
er
r
o
r
co
n
tin
u
o
u
s
ly
.
I
n
th
is
p
ap
er
,
in
teg
r
al
tim
e
ab
s
o
lu
te
er
r
o
r
(
I
T
AE
)
was
ad
o
p
ted
as
a
f
itn
ess
f
u
n
ctio
n
an
d
it
is
s
h
o
wn
in
(
1
1
)
[
2
6
]
,
u
s
ed
in
W
OA
to
tu
n
e
th
e
c
o
n
tr
o
ller
g
ain
s
an
d
ac
h
iev
e
s
tab
le
s
y
s
tem
r
esp
o
n
s
e,
th
e
f
itn
ess
f
u
n
ctio
n
f
o
r
th
e
s
y
s
tem
i
s
in
d
icate
d
in
Fig
u
r
e
4
an
d
th
e
b
lo
ck
d
iag
r
am
o
f
th
e
s
y
s
tem
s
h
o
wn
i
n
Fig
u
r
e
5
.
=
∫
|
e
|
∞
0
(
1
1
)
Fig
u
r
e
4
.
I
T
AE
f
itn
ess
f
u
n
ctio
n
b
eh
a
v
io
r
f
o
r
o
p
tim
al
FOPID
co
n
tr
o
ller
Fig
u
r
e
5
.
FOPID
co
n
tr
o
ller
f
o
r
AVR s
y
s
tem
b
ased
o
n
W
OA
T
o
s
h
o
w
th
e
s
y
s
tem
p
er
f
o
r
m
an
ce
b
ased
o
n
o
p
tim
al
FOPI
D
co
n
tr
o
ller
a
co
m
p
ar
is
o
n
with
class
ical
PID
is
d
o
n
e
(
tu
n
ed
u
s
in
g
W
OA
al
s
o
)
,
Fig
u
r
e
6
in
d
icate
s
th
e
s
y
s
tem
r
esp
o
n
s
e
f
o
r
th
e
o
p
ti
m
al
co
n
tr
o
ller
s
PID
an
d
FOPID,
an
d
th
e
g
ain
s
o
f
th
e
o
p
tim
al
co
n
tr
o
ller
s
ar
e
lis
ted
in
T
ab
le
3
.
T
h
e
s
tep
r
esp
o
n
s
e
r
esu
lts
f
o
r
th
e
two
co
n
tr
o
ller
s
is
s
h
o
wn
in
T
a
b
le
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Desig
n
o
f fra
c
tio
n
a
l o
r
d
er P
I
D
co
n
tr
o
ller
fo
r
A
V
R
s
ystem
…
(
La
yla
H.
A
b
o
o
d
)
1415
Fig
u
r
e
6
.
T
e
r
m
in
al
v
o
ltag
e
r
es
p
o
n
s
es f
o
r
o
p
tim
al
co
n
tr
o
ller
s
T
ab
le
3
.
Op
tim
al
co
n
tr
o
ller
s
Gain
s
tu
n
ed
u
s
in
g
W
OA
C
o
n
t
r
o
l
l
e
r
C
o
n
t
r
o
l
l
e
r
G
a
i
n
s
K
p
K
I
K
D
λ
μ
F
O
P
I
D
0
.
8
9
6
1
0
.
5
1
5
0
.
4
5
8
0
.
9
4
8
1
.
1
2
7
P
I
D
0
.
9
4
.
1
1
3
0
.
3
8
7
T
ab
le
4
.
Step
r
esp
o
n
s
e
r
esu
lts
f
o
r
o
p
tim
al
co
n
tr
o
ller
s
C
o
n
t
r
o
l
l
e
r
P
e
a
k
Ti
me(s
)
R
i
se
T
i
me(s
)
S
e
t
t
l
e
i
n
g
Ti
m(
s)
M
p
(%)
F
O
P
I
D
0
.
2
7
0
.
1
4
0
5
0
.
2
1
3
1
.
2
8
P
I
D
0
.
8
0
.
3
4
5
5
0
.
5
5
7
1
1
.
3
8
T
h
e
d
if
f
er
en
ce
b
etwe
en
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
an
d
class
ical
PID
co
n
tr
o
ller
ap
p
ea
r
s
i
n
th
e
s
tep
r
esp
o
n
s
e
an
aly
s
is
,
th
is
i
s
d
u
e
to
th
e
b
en
ef
its
o
f
f
r
ac
tio
n
al
m
ath
em
atic
ef
f
ec
t
o
n
s
y
s
tem
r
esp
o
n
s
e
as
s
h
o
wn
it
h
as
f
ast
s
et
tlin
g
tim
e
with
3
8
%
f
aster
th
an
th
e
clas
s
ical
PID
co
n
tr
o
ller
an
d
th
e
s
m
all
o
v
er
s
h
o
o
t
(
1
.
2
4
)
wh
ich
ac
h
iev
e
a
s
tab
le
an
d
ef
f
icien
t
d
esire
d
r
esp
o
n
s
e.
I
n
T
a
b
le
5
a
co
m
p
ar
is
o
n
with
o
th
e
r
co
n
t
r
o
ller
s
is
ex
p
lain
ed
b
ased
o
n
p
ar
am
eter
s
o
f
r
esp
o
n
s
e
an
aly
s
is
,
as
s
h
o
wn
f
r
o
m
th
e
an
aly
s
is
th
e
FOPID
co
n
tr
o
ller
is
f
aster
th
an
PID
[8
]
,
[
9
]
,
f
u
zz
y
PI,
a
n
d
f
u
zz
y
2
PI
[
1
5
]
co
n
tr
o
ller
s
in
tr
ac
k
in
g
th
e
d
esire
d
v
alu
e
with
f
aster
s
ettlin
g
tim
e
(
0
.
2
1
3
s
)
with
s
m
all
o
v
er
s
h
o
o
t
v
alu
e
b
u
t
if
co
m
p
ar
ed
with
[
6
]
it
ca
n
b
e
s
ee
n
th
at
it
h
av
e
v
er
y
s
m
all
o
v
er
s
h
o
o
t
v
alu
e
b
u
t
also
h
av
e
s
lo
w
s
ettlin
g
tim
e,
th
e
p
r
o
p
o
s
ed
FOPID
is
f
aster
th
an
[
6
]
b
y
n
e
ar
ly
4
7
.
2
5
%,
th
is
d
if
f
er
en
ce
d
u
e
to
th
e
s
m
ar
t
W
OA
th
at
tu
n
e
th
e
g
ain
s
o
f
th
e
co
n
tr
o
ller
to
o
p
tim
u
m
v
alu
es
th
en
lead
th
e
s
y
s
tem
to
r
ea
ch
to
t
h
e
d
esire
d
r
esp
o
n
s
e.
T
ab
le
5
.
R
esp
o
n
s
e
an
al
y
s
is
co
m
p
ar
is
o
n
with
o
t
h
er
co
n
tr
o
ller
s
O
p
t
i
mi
z
a
t
i
o
n
–
C
o
n
t
r
o
l
l
e
r
set
t
l
i
n
g
t
i
m
e
(
s)
R
i
se
t
i
me(s
)
O
v
e
r
sh
o
o
t
(
%)
W
O
A
-
P
I
D
0
.
5
5
7
0
.
3
4
5
5
1
1
.
3
8
S
S
A
-
P
I
D
[
8
]
0
.
5
5
1
0
.
0
9
8
1
1
5
.
5
A
EO
-
P
I
D
[
9
]
1
.
0
3
6
0
0
.
1
0
6
5
2
2
.
6
7
7
P
S
O
-
F
u
z
z
y
P
I
[
1
5
]
1
.
2
7
5
0
.
5
3
7
0
P
S
O
–
F
u
z
z
y
2
P
I
[
1
5
]
1
.
3
5
8
0
.
5
2
9
s
0
CS
-
F
O
P
I
D
[
6
]
0
.
4
5
0
7
0
.
1
0
4
2
0
.
0
0
1
4
P
r
o
p
o
s
e
d
W
O
A
-
F
O
P
I
D
0
.
2
1
3
0
.
1
4
0
5
1
.
2
8
T
o
o
b
tain
th
e
c
o
n
tr
o
ller
ef
f
o
r
t
s
f
o
r
th
e
two
co
n
tr
o
ller
s
(
PID
an
d
FOPOID
)
th
e
e
n
er
g
y
an
d
m
ax
im
u
m
co
n
tr
o
l
s
ig
n
al
is
ca
lcu
lated
as
s
h
o
wn
in
T
ab
le
6
,
it
e
x
p
lain
s
t
h
at
th
e
FOPID
co
n
tr
o
ller
h
as
t
h
e
h
ig
h
est
co
n
tr
o
l
ef
f
o
r
t.
I
t
ap
p
ea
r
s
wo
r
s
t
v
alu
e
s
b
u
t
it
is
co
m
p
letely
n
o
r
m
al
d
u
e
t
o
th
e
f
astes
t
r
esp
o
n
s
e
a
s
s
h
o
wn
in
T
a
b
le
4
b
ec
au
s
e
th
e
co
n
tr
o
ller
ex
er
ts
m
o
r
e
ef
f
o
r
t
f
o
r
g
iv
in
g
a
f
aster
tr
an
s
ien
t
r
esp
o
n
s
e
wh
ile
in
P
I
D
co
n
tr
o
ller
wh
ich
is
lo
w
ef
f
o
r
t c
o
n
s
u
m
in
g
,
h
as th
e
s
lo
west r
esp
o
n
s
e
as in
d
icate
d
in
th
e
r
esu
lts
o
b
tain
e
d
.
T
ab
le
6
.
C
o
n
tr
o
l e
f
f
o
r
t a
n
aly
s
i
s
f
o
r
PID
an
d
FOPID
co
n
tr
o
ller
s
U
max
En
e
r
g
y
C
o
n
t
r
o
l
l
e
r
3
8
2
7
6
.
1
1
P
I
D
1
1
3
5
4
9
2
.
5
F
O
P
I
D
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
4
1
0
-
1
4
1
8
1416
6.
RO
B
US
T
NE
SS
AN
AL
Y
SI
S
R
o
b
u
s
tn
ess
an
aly
s
is
is
d
o
n
e
to
ch
ec
k
th
e
s
y
s
tem
r
esp
o
n
s
e
b
a
s
ed
o
n
two
m
atter
s
th
e
f
ir
s
t
o
n
e
is
wh
en
th
e
v
o
ltag
e
is
ch
an
g
ed
d
u
r
in
g
wo
r
k
in
g
p
r
o
p
e
r
ly
,
it
m
ea
n
s
th
er
e
is
a
d
if
f
er
en
ce
lik
e
m
o
r
e
t
h
an
n
ee
d
e
d
d
esire
d
v
alu
e
o
r
less
th
an
it
d
u
e
to
ch
an
g
in
g
lo
a
d
o
r
s
ig
n
al
a
d
d
ed
o
r
d
ec
r
ea
s
ed
f
r
o
m
o
th
e
r
d
ev
ice
s
,
at
th
is
p
o
in
t
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
m
u
s
t
r
ejec
t
an
y
ex
ter
n
al
d
is
tu
r
b
an
ce
s
m
ay
f
ac
e
th
e
s
y
s
tem
an
d
s
av
e
th
e
d
esire
d
v
alu
e
as
n
ee
d
ed
.
Fig
u
r
e
7
s
h
o
w
th
e
b
e
h
av
io
r
o
f
co
n
tr
o
ller
with
n
e
g
ativ
e
an
d
p
o
s
itiv
e
d
is
tu
r
b
an
ce
s
ig
n
al
.
Fig
u
r
e
7
.
R
esp
o
n
s
e
o
f
AVR s
y
s
tem
with
d
is
tu
r
b
an
ce
s
ig
n
als
As
s
h
o
wn
in
Fig
u
r
e
7
th
e
n
eg
ativ
e
d
is
tu
r
b
an
ce
s
ig
n
al
is
ad
d
ed
at
tim
e
1
.
5
s
th
e
r
esp
o
n
s
e
i
s
af
f
ec
ted
b
u
t
th
e
co
n
tr
o
ller
r
etu
r
n
s
th
e
r
esp
o
n
s
e
to
th
e
d
esire
d
v
alu
e
in
a
s
h
o
r
t
p
er
io
d
(
0
.
2
2
8
s
)
th
en
ad
d
in
g
p
o
s
itiv
e
d
is
tu
r
b
an
ce
s
ig
n
al
at
tim
e
3
s
wh
ich
also
af
f
ec
ted
th
e
r
esp
o
n
s
e
b
u
t
t
h
e
co
n
tr
o
ller
s
o
lv
es
t
h
is
d
ev
iatio
n
in
th
e
r
esp
o
n
s
e
with
in
0
.
2
1
3
s
a
n
d
r
ea
ch
to
th
e
d
esire
d
v
al
u
e,
th
is
r
ef
lects
th
e
a
b
ilit
y
o
f
th
e
co
n
tr
o
ller
to
o
v
er
c
o
m
e
an
y
n
o
is
e
m
ay
f
ac
e
t
h
e
s
y
s
tem
an
d
s
o
lv
e
it
with
in
a
s
h
o
r
t
p
er
io
d
.
T
h
e
s
ec
o
n
d
m
atter
h
ap
p
en
s
wh
en
th
e
AVR
s
y
s
tem
p
ar
am
eter
s
ar
e
ch
an
g
e
d
d
u
r
in
g
wo
r
k
in
g
(
it
m
ea
n
K
an
d
T
)
f
o
r
an
y
p
ar
ts
th
at
th
e
AVR
s
y
s
tem
co
n
s
is
t
s
o
f
,
h
er
e
a
ch
an
g
e
in
th
e
am
p
lifie
r
p
ar
t
is
a
p
p
lied
t
o
th
e
A
VR
s
y
s
tem
with
±
2
0
%
f
r
o
m
its
o
r
ig
in
al
v
alu
e,
F
ig
u
r
e
8
ex
p
lain
s
th
e
r
esp
o
n
s
e
o
f
th
e
c
o
n
tr
o
ller
b
ased
o
n
th
e
d
if
f
er
en
ce
h
ap
p
e
n
ed
in
th
e
A
VR
s
y
s
tem
.
(
a)
(
b
)
Fig
u
r
e
8
.
(
a
)
wh
en
ch
an
g
in
g
t
h
e
tim
e
co
n
s
tan
t o
f
am
p
lifie
r
p
ar
t w
ith
±
2
0
% f
r
o
m
its
o
r
ig
i
n
al
v
alu
e
an
d
(
b
)
wh
en
ch
an
g
in
g
th
e
g
ain
c
o
n
s
tan
t o
f
am
p
lifie
r
p
ar
t w
ith
±
2
0
% f
r
o
m
its
o
r
ig
in
al
v
alu
e
Fro
m
Fig
u
r
e
8
ab
o
v
e
th
e
ef
f
ec
t
o
f
ch
an
g
in
g
th
e
tim
e
an
d
g
ai
n
co
n
s
tan
ts
o
f
th
e
am
p
lifie
r
p
a
r
t
ap
p
ea
r
s
o
n
th
e
b
e
h
av
io
r
o
f
th
e
AVR
s
y
s
tem
b
u
t
it
is
clea
r
th
at
wh
en
ch
a
n
g
in
g
th
e
tim
e
th
e
s
y
s
tem
n
ee
d
s
1
s
ec
to
r
etu
r
n
t
o
its
d
esire
d
v
alu
e
w
h
ile
ch
an
g
i
n
g
its
g
ai
n
v
alu
e
i
s
r
etu
r
n
ed
to
th
e
d
esire
d
v
alu
e
af
ter
0
.
7
s
ec
t
h
is
r
ef
lects th
e
r
o
b
u
s
tn
ess
o
f
th
e
s
y
s
tem
co
n
tr
o
lled
u
s
in
g
th
e
p
r
o
p
o
s
ed
o
p
tim
al
FO
PID
co
n
tr
o
ller
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Desig
n
o
f fra
c
tio
n
a
l o
r
d
er P
I
D
co
n
tr
o
ller
fo
r
A
V
R
s
ystem
…
(
La
yla
H.
A
b
o
o
d
)
1417
7.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
esen
ts
a
r
o
b
u
s
t
FOPID
co
n
tr
o
ller
to
co
n
tr
o
l
t
h
e
AVR
s
y
s
tem
u
s
in
g
a
s
m
ar
t
p
ar
am
eter
tu
n
in
g
alg
o
r
ith
m
b
ased
o
n
W
OA
th
at
m
in
im
izin
g
th
e
er
r
o
r
an
d
tr
ac
k
in
g
th
e
d
esire
d
r
esp
o
n
s
e,
a
co
m
p
ar
is
o
n
with
th
e
clas
s
ical
PID
co
n
tr
o
ller
tu
n
ed
with
d
if
f
er
en
t
m
eth
o
d
s
an
d
with
o
th
er
co
n
tr
o
ller
s
lik
e
f
u
zz
y
PI
an
d
f
u
zz
y
2
PI.
T
h
e
r
o
b
u
s
tn
ess
an
aly
s
is
i
s
u
tili
ze
d
in
two
way
s
t
h
e
f
ir
s
t
o
n
e
is
d
o
n
e
b
y
ad
d
in
g
d
is
tu
r
b
an
ce
s
s
ig
n
al
in
d
if
f
er
e
n
t
v
alu
es
an
d
d
if
f
er
e
n
t
tim
e
d
u
r
in
g
s
im
u
latin
g
th
e
AVR
s
y
s
tem
,
th
e
p
r
o
p
o
s
ed
c
o
n
tr
o
ller
s
o
lv
e
th
is
is
s
u
e
an
d
r
ejec
t
th
ese
s
ig
n
als
th
en
r
etu
r
n
to
th
e
s
tab
le
b
e
h
a
v
io
r
o
f
th
e
s
y
s
tem
with
in
s
h
o
r
t
p
er
io
d
ef
f
icien
tly
an
d
th
e
s
ec
o
n
d
way
is
b
y
ch
an
g
in
g
th
e
s
y
s
tem
p
ar
am
eter
s
with
±
2
0
%
f
r
o
m
its
o
r
i
g
in
a
l
v
alu
e
t
o
t
est
th
e
s
y
s
tem
b
eh
av
io
r
b
ased
o
n
th
is
ch
an
g
e
,
th
e
s
y
s
tem
s
u
f
f
er
s
f
r
o
m
lo
w
o
v
er
s
h
o
o
t
b
u
t
its
r
ea
c
h
d
esire
d
v
alu
e
i
n
a
tim
e
r
an
g
e
b
etwe
en
(
0
.
7
-
1
)
s
ec
.
RE
F
E
R
E
NC
E
S
[1
]
N.
K.
Ra
y
,
S
.
K.
M
o
h
a
p
a
tra
a
n
d
S
.
S
.
Da
sh
,
"
G
ra
v
it
a
ti
o
n
a
l
S
e
a
rc
h
Alg
o
rit
h
m
fo
r
O
p
ti
m
a
l
T
u
n
n
in
g
o
f
c
o
n
tr
o
ll
e
r
p
a
ra
m
e
ters
in
AV
R
s
y
ste
m
,
"
2
0
2
0
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
C
o
mp
u
ta
ti
o
n
a
l
In
tel
li
g
e
n
c
e
fo
r
S
ma
rt
P
o
we
r
S
y
ste
m a
n
d
S
u
sta
i
n
a
b
le E
n
e
rg
y
(
CIS
PS
S
E)
,
2
0
2
0
,
p
p
.
1
-
6
,
d
o
i:
1
0
.
1
1
0
9
/C
IS
P
S
S
E
4
9
9
3
1
.
2
0
2
0
.
9
2
1
2
1
9
7
.
[2
]
K.
P
.
M
o
h
a
n
t
y
,
B
.
K.
S
a
h
u
,
a
n
d
S
.
P
a
n
d
a
,
"
T
u
n
i
n
g
a
n
d
a
ss
e
ss
m
e
n
t
o
f
p
ro
p
o
r
ti
o
n
a
l
–
i
n
teg
ra
l
–
d
e
riv
a
ti
v
e
c
o
n
tr
o
ll
e
r
fo
r
a
n
a
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
sy
ste
m
e
m
p
lo
y
i
n
g
l
o
c
a
l
Un
imo
d
a
l
S
a
m
p
li
n
g
Alg
o
rit
h
m
,
"
El
e
c
tric
Po
we
r
Co
mp
o
n
e
n
ts
a
n
d
S
y
ste
ms
,
v
o
l
.
4
2
,
n
o
.
9
,
p
p
.
9
5
9
-
9
6
9
,
2
0
1
4
,
d
o
i:
1
0
.
1
0
8
0
/
1
5
3
2
5
0
0
8
.
2
0
1
4
.
9
0
3
5
4
6
.
[3
]
E.
Çe
li
k
,
"
I
n
c
o
r
p
o
ra
ti
o
n
o
f
sto
c
h
a
stic
fra
c
tal
se
a
r
c
h
a
lg
o
rit
h
m
i
n
to
e
fficie
n
t
d
e
sig
n
o
f
P
ID
c
o
n
tro
ll
e
r
f
o
r
a
n
a
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
s
y
ste
m
,
"
Ne
u
ra
l
C
o
mp
u
ti
n
g
a
n
d
Ap
p
li
c
a
ti
o
n
s
,
v
o
l.
3
0
,
n
o
.
6
,
p
p
.
1
9
9
1
-
2
0
0
2
,
2
0
1
8
,
d
o
i
:
1
0
.
1
0
0
7
/s
0
0
5
2
1
-
0
1
7
-
3
3
3
5
-
7
.
[4
]
M
.
A.
S
a
h
i
b
,
"
A
n
o
v
e
l
o
p
ti
m
a
l
P
ID
p
lu
s
se
c
o
n
d
o
r
d
e
r
d
e
ri
v
a
ti
v
e
c
o
n
tr
o
ll
e
r
f
o
r
AV
R
sy
ste
m
,
”
E
n
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
a
n
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
,
v
o
l
.
1
8
,
p
p
.
1
9
4
-
2
0
6
,
2
0
1
5
,
d
o
i:
1
0
.
1
0
1
6
/j
.
jes
tch
.
2
0
1
4
.
1
1
.
0
0
6
.
[5
]
B.
Oz
g
e
n
c
,
M
.
S
.
Ay
a
s
a
n
d
I.
H.
Altas
,
"
A
H
y
b
ri
d
Op
ti
m
iza
ti
o
n
A
p
p
r
o
a
c
h
t
o
De
sig
n
Op
ti
m
a
ll
y
T
u
n
e
d
P
ID
Co
n
tr
o
ll
e
r
f
o
r
a
n
AV
R
S
y
ste
m
,
"
2
0
2
0
I
n
ter
n
a
ti
o
n
a
l
Co
n
g
re
ss
o
n
Hu
ma
n
-
C
o
mp
u
ter
In
ter
a
c
ti
o
n
,
O
p
ti
miza
ti
o
n
a
n
d
Ro
b
o
ti
c
A
p
p
li
c
a
ti
o
n
s (HORA)
,
2
0
2
0
,
p
p
.
1
-
5
,
d
o
i:
1
0
.
1
1
0
9
/HORA
4
9
4
1
2
.
2
0
2
0
.
9
1
5
2
8
9
8
.
[6
]
A.
S
i
k
a
n
d
e
r
a
n
d
P
.
T
h
a
k
u
r
,
"
A
n
e
w
c
o
n
tro
l
d
e
sig
n
stra
teg
y
fo
r
a
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lat
o
r
i
n
p
o
w
e
r
sy
ste
m
,
"
I
S
A
tra
n
sa
c
ti
o
n
s
,
v
o
l.
1
0
0
,
p
p
.
2
3
5
-
2
4
3
,
2
0
2
0
,
d
o
i:
1
0
.
1
0
1
6
/
j.
isa
tra.2
0
1
9
.
1
1
.
0
3
1
.
[7
]
B.
He
k
imo
ğ
lu
a
n
d
S
.
E
k
in
c
i,
"
G
ra
ss
h
o
p
p
e
r
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
fo
r
a
u
t
o
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lat
o
r
sy
ste
m
,
"
2
0
1
8
5
th
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
El
e
c
trica
l
a
n
d
El
e
c
tro
n
ic
E
n
g
i
n
e
e
rin
g
(ICEE
E)
,
2
0
1
8
,
p
p
.
1
5
2
-
1
5
6
,
d
o
i
:
1
0
.
1
1
0
9
/IC
EE
E2
.
2
0
1
8
.
8
3
9
1
3
2
0
.
[8
]
I.
A.
Kh
a
n
e
t
,
e
t
a
l
.
,
"
S
a
l
p
sw
a
rm
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
-
b
a
se
d
fra
c
ti
o
n
a
l
o
rd
e
r
P
ID co
n
tro
l
ler fo
r
d
y
n
a
m
ic res
p
o
n
se
a
n
d
sta
b
il
it
y
e
n
h
a
n
c
e
m
e
n
t
o
f
a
n
a
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
sy
ste
m
,
"
El
e
c
tro
n
ics
,
v
o
l
.
8
,
n
o
.
1
2
,
p
.
1
4
7
2
,
2
0
1
9
,
d
o
i:
1
0
.
3
3
9
0
/ele
c
tro
n
ics
8
1
2
1
4
7
2
.
[9
]
M.
Ća
las
a
n
,
M
.
M
ice
v
,
Z.
Dj
u
ro
v
ic,
a
n
d
H.
Ab
d
e
lme
g
e
e
d
,
"
Arti
f
icia
l
e
c
o
sy
ste
m
-
b
a
se
d
o
p
ti
m
iza
ti
o
n
f
o
r
o
p
ti
m
a
l
tu
n
i
n
g
o
f
ro
b
u
st
P
ID
c
o
n
tro
ll
e
rs
i
n
AV
R
sy
ste
m
s
with
li
m
it
e
d
v
a
lu
e
o
f
e
x
c
it
a
ti
o
n
v
o
lt
a
g
e
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
E
d
u
c
a
ti
o
n
, v
o
l.
1
3
,
p
.
0
0
2
0
7
2
0
9
2
0
9
4
0
6
0
5
,
2
0
2
0
,
d
o
i:
1
0
.
1
1
7
7
/0
0
2
0
7
2
0
9
2
0
9
4
0
6
0
5
.
[1
0
]
J.
Bh
o
o
k
y
a
a
n
d
R.
K.
Ja
to
th
,
"
Op
ti
m
a
l
F
OPID/P
ID
c
o
n
tr
o
ll
e
r
p
a
ra
m
e
ters
tu
n
in
g
f
o
r
t
h
e
AV
R
sy
ste
m
b
a
se
d
o
n
si
n
e
-
c
o
sin
e
-
a
lg
o
ri
th
m
,
"
Evo
l
u
ti
o
n
a
ry
In
telli
g
e
n
c
e
,
v
o
l.
2
,
n
o
.
2
,
p
p
.
7
2
5
-
7
3
3
,
2
0
1
9
,
d
o
i:
1
0
.
1
0
0
7
/s
1
2
0
6
5
-
0
1
9
-
0
0
2
9
0
-
x.
[1
1
]
J.
S
u
n
,
L.
Wu
a
n
d
X.
Ya
n
g
,
"
Op
ti
m
a
l
F
ra
c
ti
o
n
a
l
Or
d
e
r
P
ID
C
o
n
tro
l
ler
De
sig
n
f
o
r
AV
R
S
y
ste
m
Ba
se
d
o
n
Im
p
ro
v
e
d
G
e
n
e
ti
c
Alg
o
rit
h
m
,
"
2
0
2
0
IEE
E
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
s
in
El
e
c
trica
l
E
n
g
in
e
e
rin
g
a
n
d
Co
mp
u
ter
Ap
p
li
c
a
ti
o
n
s( A
E
ECA
)
,
2
0
2
0
,
p
p
.
3
5
1
-
3
5
5
,
d
o
i:
1
0
.
1
1
0
9
/AE
ECA4
9
9
1
8
.
2
0
2
0
.
9
2
1
3
4
7
3
.
[1
2
]
B.
Bo
u
ro
u
b
a
,
S
.
Lad
a
c
i,
a
n
d
H.
S
c
h
u
lt
e
,
"
O
p
ti
m
a
l
d
e
si
g
n
o
f
fra
c
ti
o
n
a
l
o
r
d
e
r
P
Iλ
Dμ
c
o
n
tro
ll
e
r
f
o
r
a
n
AV
R
sy
ste
m
u
sin
g
An
t
Li
o
n
Op
ti
m
ize
r
,
"
IFA
C
-
Pa
p
e
rs
On
li
n
e
,
v
o
l
.
5
2
,
p
p
.
2
0
0
-
2
0
5
,
2
0
1
9
.
[1
3
]
.
A.
G
.
S
u
rib
a
b
u
a
n
d
B.
T.
C
h
iran
j
e
e
v
i,
"
Im
p
lem
e
n
tatio
n
o
f
fra
c
ti
o
n
a
l
o
rd
e
r
P
ID co
n
tr
o
ll
e
r
fo
r
a
n
AV
R
sy
ste
m
u
sin
g
G
A
a
n
d
ACO
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s
"
I
FAC
-
Pa
p
e
rs
On
li
n
e,
v
o
l.
4
9
,
n
o
.
1
,
p
p
.
4
5
6
-
4
6
1
,
2
0
1
6
,
d
o
i
:
1
0
.
1
0
1
6
/
j.
ifac
o
l.
2
0
1
9
.
1
1
.
3
0
4
.
[1
4
]
J.
Bh
o
o
k
y
a
a
n
d
R.
K.
Ja
t
o
th
,
"
Im
p
ro
v
e
d
Ja
y
a
a
lg
o
rit
h
m
-
b
a
se
d
F
OPID/P
ID
f
o
r
AV
R
sy
ste
m
,
"
COM
PE
L
-
T
h
e
in
ter
n
a
t
io
n
a
l
j
o
u
r
n
a
l
fo
r
c
o
m
p
u
t
a
ti
o
n
a
n
d
m
a
th
e
ma
ti
c
s
in
e
lec
trica
l
a
n
d
e
lec
tro
n
ic
e
n
g
i
n
e
e
rin
g
,
1
M
a
y
,
2
0
2
0
,
d
o
i:
1
0
.
1
1
0
8
/CO
M
P
EL
-
08
-
2
0
1
9
-
0
3
1
9
.
[1
5
]
H.
S
h
a
y
e
g
h
i
,
A.
Yo
u
n
e
si,
a
n
d
Y.
Ha
sh
e
m
i,
"
Op
ti
m
a
l
d
e
sig
n
o
f
a
ro
b
u
st
d
isc
re
te
p
a
ra
ll
e
l
F
P
+
F
I+
F
D
c
o
n
tro
ll
e
r
f
o
r
th
e
a
u
t
o
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
sy
ste
m
,
"
I
n
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
P
o
we
r
&
E
n
e
rg
y
S
y
ste
ms
,
v
o
l.
6
7
,
p
p
.
66
-
7
5
,
2
0
1
5
,
d
o
i:
1
0
.
1
0
1
6
/j
.
ij
e
p
e
s.2
0
1
4
.
1
1
.
0
1
3
.
[1
6
]
M
.
M
o
d
a
b
b
e
rn
ia,
B.
Aliza
d
e
h
,
A.
S
a
h
a
b
,
a
n
d
M
.
M
.
M
o
g
h
a
d
d
a
m
,
"
De
sig
n
i
n
g
t
h
e
R
o
b
u
st
F
u
z
z
y
P
I
a
n
d
F
u
z
z
y
Ty
p
e
-
2
P
I
Co
n
tro
ll
e
rs
b
y
M
e
tah
e
u
risti
c
Op
ti
m
izin
g
Alg
o
rit
h
m
s
fo
r
AV
R
S
y
ste
m
,
"
IET
E
J
o
u
rn
a
l
o
f
Res
e
a
rc
h
,
p
p
.
1
-
1
5
,
2
0
2
0
,
d
o
i:
1
0
.
1
0
8
0
/
0
3
7
7
2
0
6
3
.
2
0
2
0
.
1
7
6
9
5
1
0
.
[1
7
]
B.
He
k
imo
ğ
l
u
,
"
S
i
n
e
-
c
o
sin
e
a
lg
o
r
it
h
m
-
b
a
se
d
o
p
ti
m
iza
ti
o
n
fo
r
a
u
t
o
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
s
y
ste
m
,
"
T
ra
n
sa
c
ti
o
n
s
o
f
th
e
In
stit
u
te
o
f
M
e
a
su
re
me
n
t
a
n
d
Co
n
tro
l
,
vol
.
4
1
,
n
o
.
4
,
p
p
.
1
7
6
1
-
1
7
7
1
,
2
0
1
9
,
d
o
i:
1
0
.
1
1
7
7
/0
1
4
2
3
3
1
2
1
8
8
1
1
4
5
3
.
[1
8
]
Y.
Ba
tma
n
i.
a
n
d
H.
G
o
lp
îra,
"
A
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lat
o
r
d
e
sig
n
u
si
n
g
a
m
o
d
ifi
e
d
a
d
a
p
ti
v
e
o
p
ti
m
a
l
a
p
p
ro
a
c
h
,
"
El
e
c
trica
l
Po
we
r a
n
d
En
e
rg
y
S
y
st
e
ms
,
v
o
l.
1
0
4
,
p
p
.
3
4
9
-
3
5
7
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/j
.
ij
e
p
e
s.2
0
1
8
.
0
7
.
0
0
1
.
[1
9
]
R.
Ru
c
h
it
a
,
R.
Ku
m
a
r,
R.
Ku
m
a
r
a
n
d
K.
S
h
a
rm
a
,
"
Co
m
p
a
ra
ti
v
e
An
a
ly
sis
o
f
O
p
ti
m
iza
ti
o
n
Tec
h
n
iq
u
e
s
fo
r
Co
n
tr
o
ll
i
n
g
a
n
AV
R
S
y
ste
m
,
"
2
0
1
9
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Rec
e
n
t
Ad
v
a
n
c
e
s
in
En
e
rg
y
-
e
ff
ici
e
n
t
Co
m
p
u
ti
n
g
a
n
d
Co
mm
u
n
ica
t
io
n
(ICRA
ECC)
,
2
0
1
9
,
p
p
.
1
-
5
,
d
o
i:
1
0
.
1
1
0
9
/ICR
AECC4
3
8
7
4
.
2
0
1
9
.
8
9
9
5
1
3
0
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
4
1
0
-
1
4
1
8
1418
[2
0
]
B.
A.
Ob
a
id
,
A.
L
.
S
a
leh
,
a
n
d
A
.
K.
Ka
d
h
im,
"
Re
so
lv
i
n
g
o
f
o
p
ti
m
a
l
fra
c
ti
o
n
a
l
P
ID
c
o
n
tro
l
ler
fo
r
DC
m
o
to
r
d
riv
e
b
a
se
d
o
n
a
n
ti
-
wi
n
d
u
p
b
y
i
n
v
a
siv
e
we
e
d
o
p
ti
m
iza
ti
o
n
tec
h
n
i
q
u
e
,
"
I
n
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
,
v
o
l.
15
,
n
o
.
1
,
p
p
.
9
5
-
1
0
3
,
2
0
1
9
,
d
o
i:
1
0
.
1
1
5
9
1
/i
j
e
e
c
s.v
1
5
.
i
1
.
p
p
9
5
-
1
0
3
.
[2
1
]
X.
Li
,
Y.
Wan
g
,
N.
Li
,
M
.
Ha
n
,
T
.
Yi
n
g
g
a
n
,
a
n
d
F
.
Li
u
,
"
Op
ti
m
a
l
fra
c
ti
o
n
a
l
o
r
d
e
r
P
ID
c
o
n
tr
o
ll
e
r
d
e
sig
n
fo
r
a
u
to
m
a
ti
c
v
o
lt
a
g
e
re
g
u
lato
r
sy
st
e
m
b
a
se
d
o
n
re
fe
re
n
c
e
m
o
d
e
l
u
sin
g
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
c
h
i
n
e
L
e
a
rn
in
g
a
n
d
Cy
b
e
rn
e
ti
c
s
,
v
o
l.
8
,
n
o
.
5,
p
p
.
1
5
9
5
-
1
6
0
5
,
2
0
1
7
,
d
o
i
:
1
0
.
1
0
0
7
/s
1
3
0
4
2
-
0
1
6
-
0
5
3
0
-
2
.
[2
2
]
S.
M
irj
a
li
li
a
n
d
A.
Lew
is,
"
T
h
e
wh
a
le
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
,
"
A
d
v
a
n
c
e
s
in
e
n
g
in
e
e
rin
g
so
ft
w
a
re
,
v
o
l.
9
5
,
p
p
.
5
1
-
6
7
,
2
0
1
6
,
d
o
i:
1
0
.
1
0
1
6
/j
.
a
d
v
e
n
g
so
ft.
2
0
1
6
.
0
1
.
0
0
8
.
[2
3
]
F
.
S
.
G
h
a
re
h
c
h
o
p
o
g
h
a
n
d
H
.
G
h
o
li
z
a
d
e
h
,
"
A
c
o
m
p
re
h
e
n
si
v
e
su
rv
e
y
:
W
h
a
le
Op
ti
m
iza
ti
o
n
Al
g
o
rit
h
m
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
s
,
"
S
wa
rm
a
n
d
Evo
lu
ti
o
n
a
ry
C
o
mp
u
ta
t
io
n
,
v
o
l.
4
8
,
p
p
.
1
-
2
4
,
2
0
1
9
,
d
o
i:
1
0
.
1
0
1
6
/j
.
sw
e
v
o
.
2
0
1
9
.
0
3
.
0
0
4
.
[2
4
]
A.
Ku
m
a
r
a
n
d
S.
S
u
h
a
g
,
"
Wh
a
le
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
tu
n
e
d
fra
c
ti
o
n
a
l
o
rd
e
r
P
Iλ
Dμ
c
o
n
tro
l
ler
fo
r
lo
a
d
fre
q
u
e
n
c
y
c
o
n
tro
l
o
f
m
u
lt
i
-
s
o
u
rc
e
p
o
we
r
sy
ste
m
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Bi
o
-
In
s
p
ire
d
C
o
mp
u
ta
ti
o
n
,
v
o
l.
1
3
n
o
.
4
,
p
p
.
2
0
9
-
2
2
1
,
2
0
1
9
,
d
o
i:
1
0
.
1
5
0
4
/I
JBIC.2
0
1
9
.
1
0
0
1
5
3
.
[2
5
]
M
.
O.
Ok
wu
a
n
d
L.
K.
Tar
ti
b
u
,
"
M
e
tah
e
u
risti
c
Op
ti
m
iza
ti
o
n
:
Na
tu
re
-
I
n
sp
ired
Al
g
o
ri
th
m
s
S
wa
rm
a
n
d
Co
m
p
u
tati
o
n
a
l
I
n
telli
g
e
n
c
e
,
T
h
e
o
ry
a
n
d
Ap
p
li
c
a
ti
o
n
s
,
"
S
p
ri
n
g
e
r
N
a
tu
re
,
v
o
l
.
9
2
7
,
2
0
2
0
.
[2
6
]
L.
H.
Ab
o
o
d
,
E.
H.
Ka
ra
m
a
n
d
A.
H.
Iss
a
,
"
F
P
G
A
Im
p
lem
e
n
tatio
n
o
f
S
i
n
g
le
Ne
u
r
o
n
P
ID
Co
n
tro
ll
e
r
fo
r
De
p
th
o
f
An
e
sth
e
sia
Ba
se
d
o
n
P
S
O
,
"
2
0
1
8
T
h
ird
S
c
ien
ti
f
ic Co
n
fer
e
n
c
e
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
(
S
CEE
)
,
2
0
1
8
,
p
p
.
2
4
7
-
2
5
2
,
d
o
i:
1
0
.
1
1
0
9
/S
CE
E.
2
0
1
8
.
8
6
8
4
1
8
6
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
La
y
l
a
H
.
Abo
o
d
re
c
e
iv
e
d
h
e
r
B.
E
n
g
.
a
n
d
M
.
S
c
.
a
n
d
P
HD
d
e
g
re
e
s
i
n
El
e
c
tro
n
ic
a
n
d
Co
m
m
u
n
ica
ti
o
n
E
n
g
in
e
e
rin
g
fr
o
m
th
e
U
n
iv
e
rsit
y
o
f
Tec
h
n
o
lo
g
y
-
Ba
g
h
d
a
d
.
S
h
e
is
c
u
rre
n
tl
y
a
n
Ac
a
d
e
m
ic
st
a
ff
m
e
m
b
e
r
in
th
e
De
p
a
rtme
n
t
o
f
Co
n
tr
o
l
a
n
d
S
y
st
e
m
En
g
in
e
e
rin
g
,
Un
i
v
e
rsity
o
f
Tec
h
n
o
l
o
g
y
,
B
a
g
h
d
a
d
,
Ira
q
H
e
r
re
se
a
rc
h
in
tere
st
is
Artifi
c
ial
In
telli
g
e
n
t,
Op
t
imiz
a
ti
o
n
Tec
h
n
iq
u
e
,
M
o
d
e
li
n
g
&
S
imu
lati
o
n
,
a
n
d
F
P
G
A an
d
Emb
e
d
d
e
d
s
y
ste
m
s.
Ba
shra
K
a
d
h
im
O
leiwi
Cha
b
o
r
Alwa
wi
,
b
o
r
n
in
Ba
g
h
d
a
d
-
Ira
q
,
c
o
m
p
lete
d
a
M
a
ste
r
d
e
g
r
e
e
in
M
e
c
h
a
tro
n
ics
En
g
in
e
e
ri
n
g
/
C
o
n
tr
o
l
a
n
d
S
y
ste
m
s
En
g
i
n
e
e
rin
g
De
p
a
rtme
n
t
a
t
Un
iv
e
rsity
o
f
Tec
h
n
o
l
o
g
y
(UO
T)
Ba
g
d
a
d
-
Ira
q
.
S
h
e
fin
is
h
e
d
h
e
r
P
h
D
d
e
g
re
e
a
t
Co
n
tro
l
E
n
g
i
n
e
e
rin
g
De
p
a
rtme
n
t
(RS
T),
S
ie
g
e
n
Un
i
v
e
rsity
,
G
e
rm
a
n
y
.
S
h
e
is
c
u
rre
n
tl
y
wo
rk
i
n
g
a
s
a
fa
c
u
lt
y
m
e
m
b
e
r
in
c
o
n
tro
l
a
n
d
sy
ste
m
s
e
n
g
i
n
e
e
rin
g
d
e
p
a
rtme
n
t
a
t
UO
T.
M
y
re
se
a
rc
h
in
tere
sts
a
re
De
e
p
lea
rn
in
g
,
M
a
c
h
in
e
lea
rn
i
n
g
,
Artifi
c
ial
i
n
telli
g
e
n
c
e
sy
ste
m
s,
I
o
T,
O
p
ti
m
iza
ti
o
n
,
Im
a
g
e
p
r
o
c
e
ss
in
g
,
Ro
b
o
ti
c
s,
P
a
th
p
la
n
n
i
n
g
,
Au
t
o
m
a
ti
o
n
,
c
o
n
tro
l,
M
icro
c
o
n
tr
o
ll
e
rs an
d
S
e
n
so
rs.
Evaluation Warning : The document was created with Spire.PDF for Python.