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
.
2
,
A
u
g
u
s
t
2
0
2
1
,
p
p
.
65
7
~
66
4
I
SS
N:
2
5
0
2
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
23
.i
2
.
pp
65
7
-
66
4
657
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Im
plementing
o
p
t
imiza
tion o
f
PID
co
ntroller
for
DC
mo
tor
speed co
nt
ro
l
Ya
s
ir
G
.
Ra
s
hid
1
,
Ahm
ed
M
o
ha
m
m
ed
Abdu
l H
us
s
a
in
2
1
De
p
a
rtme
n
t
o
f
El
e
c
tro
n
ic E
n
g
i
n
e
e
rin
g
,
C
o
ll
e
g
e
o
f
E
n
g
i
n
e
e
rin
g
,
Un
iv
e
rsity
o
f
Di
y
a
la,
Diy
a
la,
Ira
q
2
De
p
a
rt
m
e
n
t
o
f
El
e
c
tri
c
a
l
E
n
g
i
n
e
e
rin
g
,
C
o
ll
e
g
e
o
f
E
n
g
i
n
e
e
rin
g
,
Un
iv
e
rsity
o
f
Ba
g
h
d
a
d
,
Ba
g
h
d
a
d
,
Ira
q
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Mar
4
,
2
0
2
1
R
ev
is
ed
May
1
,
2
0
2
1
Acc
ep
ted
Ma
y
5
,
2
0
2
1
Th
e
p
o
in
t
o
f
t
h
is
p
a
p
e
r
p
re
se
n
ts
a
n
o
p
t
imiz
a
ti
o
n
tec
h
n
iq
u
e
wh
ich
is
flex
ib
le
a
n
d
q
u
ick
tu
n
i
n
g
b
y
u
si
n
g
a
g
e
n
e
ti
c
a
lg
o
rit
h
m
(G
A)
to
o
b
tain
th
e
o
p
ti
m
u
m
p
ro
p
o
rti
o
n
a
l
-
i
n
teg
ra
l
-
d
e
riv
a
ti
v
e
(
P
ID
)
p
a
ra
m
e
ters
fo
r
sp
e
e
d
c
o
n
tro
l
o
f
a
se
p
a
ra
tely
e
x
c
it
e
d
DC
m
o
to
r
a
s
a
b
e
n
c
h
m
a
rk
f
o
r
p
e
rfo
rm
a
n
c
e
a
n
a
ly
sis.
T
h
e
o
p
ti
m
iza
ti
o
n
m
e
th
o
d
is
u
se
d
fo
r
se
a
rc
h
in
g
fo
r
t
h
e
p
r
o
p
e
r
v
a
lu
e
o
f
P
ID
p
a
ra
m
e
ters
.
Th
e
sp
e
e
d
c
o
n
tro
l
ler
o
f
DC
m
o
to
r
u
sin
g
P
ID
tu
n
i
n
g
m
e
th
o
d
s
in
c
lu
d
e
s
th
re
e
ty
p
e
s:
M
ATALB
P
ID
tu
n
n
e
r
a
p
p
.
,
m
o
d
if
ied
Zi
e
g
l
e
r
-
Nic
h
o
ls
m
e
th
o
d
a
n
d
g
e
n
e
ti
c
a
l
g
o
rit
h
m
(G
A).
P
ID
c
o
n
tr
o
ll
e
r
p
a
ra
m
e
ters
(Kp
,
Ki
Kd
)
will
b
e
o
b
tai
n
e
d
b
y
G
A
to
p
ro
d
u
c
e
o
p
ti
m
a
l
p
e
rfo
rm
a
n
c
e
f
o
r
th
e
DC
m
o
to
r
c
o
n
tro
l
sy
ste
m
.
S
im
u
latio
n
re
su
lt
s
i
n
d
ica
t
e
t
h
a
t
th
e
tu
n
in
g
m
e
th
o
d
o
f
P
ID
b
y
u
sin
g
a
g
e
n
e
ti
c
a
lg
o
rit
h
m
is
sh
o
wn
to
c
re
a
te
th
e
fi
n
e
st
re
su
lt
in
sy
ste
m
p
e
rfo
rm
a
n
c
e
su
c
h
a
s
se
tt
li
n
g
t
ime
,
rise
ti
m
e
,
p
e
rc
e
n
tag
e
o
f
o
v
e
rsh
o
o
t
a
n
d
ste
a
d
y
sta
te
e
rro
r.
Th
e
M
A
TL
AB/S
imu
li
n
k
s
o
ftwa
re
is
u
se
d
to
m
o
d
e
l
a
n
d
sim
u
late
t
h
e
p
r
o
p
o
se
d
DC m
o
to
r
c
o
n
tro
l
ler sy
ste
m
.
K
ey
w
o
r
d
s
:
DC
m
o
to
r
Gen
etic
alg
o
r
ith
m
MA
T
AL
B
PID
tu
n
n
er
ap
p
M
o
d
i
f
i
e
d
Z
i
e
g
l
e
r
-
N
i
c
h
o
ls
t
u
n
in
g
PID
co
n
tr
o
ller
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
:
Yasir
G.
R
ash
id
Dep
ar
tm
en
t o
f
E
lectr
o
n
ic
E
n
g
in
ee
r
in
g
,
C
o
lleg
e
o
f
E
n
g
in
ee
r
i
n
g
Un
iv
er
s
ity
o
f
Diy
ala
B
aq
u
b
ah
,
Diy
ala,
I
r
aq
E
m
ail:
y
ass
er
g
h
az
ee
_
en
g
e@
u
o
d
iy
ala.
ed
u
.
iq
1.
I
NT
RO
D
UCT
I
O
N
DC
Mo
to
r
is
b
r
o
ad
ly
u
s
ed
i
n
in
d
u
s
tr
ial
ap
p
licatio
n
s
s
u
ch
as
s
teel
r
o
llin
g
m
ills
,
elec
tr
ic
cr
an
es,
r
o
b
o
tic
m
an
i
p
u
lato
r
s
an
d
ele
ctr
ic
v
eh
icles,
b
ec
au
s
e
o
f
its
p
r
ec
is
e,
lo
w
co
s
t,
wid
e,
s
im
p
le
an
d
ea
s
iest
to
co
n
tr
o
l
[
1
]
,
[
2
]
.
Gen
er
ally
,
D
C
m
o
to
r
co
n
tr
o
l
s
y
s
te
m
m
u
s
t
h
av
e
h
ig
h
p
er
f
o
r
m
an
ce
s
u
ch
as
lo
ad
r
eg
u
latio
n
r
esp
o
n
s
e
an
d
g
o
o
d
d
y
n
am
ic
s
p
ee
d
c
o
m
m
an
d
tr
ac
k
i
n
g
.
T
o
a
ch
iev
e
h
i
g
h
p
er
f
o
r
m
an
ce
f
o
r
a
DC
m
o
to
r
co
n
tr
o
l
s
y
s
tem
,
o
p
tim
al
PID
co
n
tr
o
ller
p
ar
am
eter
s
ar
e
r
eq
u
ir
ed
,
wh
ich
tr
ad
itio
n
al
PID
ca
n
n
o
t
p
r
o
v
id
e
,
s
o
f
t
co
m
p
u
tatio
n
h
as b
ee
n
u
s
ed
wid
ely
in
th
e
last
two
d
ec
ad
es.
El
-
Dee
n
,
Ma
h
m
o
u
d
,
a
n
d
E
l
-
Sa
wi
[3
]
p
r
esen
t a
s
o
f
t
co
m
p
u
tin
g
tech
n
iq
u
e
th
at
u
s
es
a
g
en
etic
alg
o
r
ith
m
(
GA)
to
d
ec
id
e
th
e
o
p
tim
al
p
ar
a
m
eter
s
o
f
PID
co
n
tr
o
ller
s
f
o
r
a
DC
m
o
to
r
as
a
b
en
ch
m
ar
k
f
o
r
p
e
r
f
o
r
m
an
c
e
ev
alu
atio
n
.
T
h
e
p
r
o
p
o
s
ed
g
en
etic
alg
o
r
ith
m
(
GA)
is
co
m
p
ar
ed
t
o
th
e
ac
tiv
e
s
et
o
p
tim
izatio
n
alg
o
r
ith
m
(
ASOA)
in
th
is
p
ap
er
.
Ag
ar
wal
et
a
l
.
[
4
]
,
co
m
p
ar
es
an
d
an
aly
ze
s
th
e
r
o
b
u
s
tn
ess
o
f
as
g
r
ay
wo
lf
-
o
p
tim
ized
,
a
FOPID
s
ch
em
e
is
ap
p
lied
to
a
f
r
ac
tio
n
al
-
o
r
d
er
p
r
o
p
o
r
tio
n
al
-
in
te
g
r
al
-
d
e
r
iv
ativ
e
(
FOPID)
o
n
PID
c
o
n
tr
o
ller
f
o
r
d
c
m
o
to
r
s
p
ee
d
co
n
tr
o
l.
B
ased
o
n
th
e
g
en
etic
alg
o
r
ith
m
[
5
]
,
g
en
er
ates
an
o
p
tim
ally
en
g
in
ee
r
ed
b
r
u
s
h
less
DC
m
o
to
r
s
p
ee
d
co
n
tr
o
l
c
o
n
t
r
o
ller
(
GA)
.
A
PID
co
n
tr
o
ller
f
o
r
B
L
DC
m
o
to
r
c
o
n
tr
o
l
d
e
v
ice
e
m
p
l
o
y
s
th
e
in
teg
r
al
s
q
u
ar
ed
er
r
o
r
(
I
SE)
an
d
in
teg
r
al
a
b
s
o
lu
te
er
r
o
r
(
I
AE
)
e
r
r
o
r
cr
iter
io
n
.
I
n
th
is
p
ap
er
,
a
g
e
n
etic
alg
o
r
ith
m
(
GA)
o
p
tim
izatio
n
s
tr
ateg
y
f
o
r
a
d
ju
s
tin
g
PID
tu
n
in
g
p
ar
am
eter
s
f
o
r
a
s
ep
ar
ately
ex
cited
DC
m
o
to
r
s
p
ee
d
c
o
n
tr
o
l
is
p
r
o
p
o
s
ed
.
I
t
is
cr
itical
to
o
b
tain
th
e
b
est
s
o
lu
tio
n
s
o
th
at
th
e
co
n
tr
o
ller
h
as
th
e
f
astes
t
an
d
m
o
s
t
s
tab
le
r
esp
o
n
s
e
tim
e.
So
m
e
im
p
o
r
t
an
t
ad
v
an
tag
es
o
f
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
.
2
,
Au
g
u
s
t 2
0
2
1
:
65
7
-
66
4
658
u
s
in
g
a
PID
-
g
en
etic
alg
o
r
ith
m
ca
n
b
e
g
en
er
alize
d
as
f
aster
r
esp
o
n
s
e
tim
e,
s
m
aller
o
v
er
s
h
o
o
t,
r
ed
u
ce
d
s
tead
y
s
tate
er
r
o
r
,
r
ed
u
ce
d
o
s
cillatio
n
s
an
d
im
p
r
o
v
e
d
o
u
tp
u
t
d
is
tu
r
b
an
ce
r
ejec
tio
n
[
6
]
-
[
8
]
.
T
o
ac
h
iev
e
th
e
r
esu
lts
o
b
tain
ed
b
y
th
e
PID
-
g
e
n
etic
alg
o
r
ith
m
,
co
m
p
ar
ed
it
with
th
e
MA
T
AL
B
PID
tu
n
n
er
ap
p
.
an
d
th
e
m
o
d
if
ied
Z
ieg
ler
-
Nich
o
ls
(
MZ
N)
m
eth
o
d
.
T
h
e
m
ain
g
o
al
o
f
th
is
wo
r
k
is
to
r
ed
u
ce
s
ettlin
g
tim
e,
o
v
e
r
s
h
o
o
t,
s
tead
y
-
s
tate
er
r
o
r
,
a
n
d
v
elo
city
g
ain
b
y
u
s
in
g
a
PID
co
n
tr
o
ller
,
wh
ic
h
is
a
g
en
er
ic
f
ee
d
b
ac
k
co
n
tr
o
ller
.
2.
DC
M
O
T
O
R
M
A
T
H
E
M
AT
I
CAL
M
O
DE
L
T
h
e
DC
m
o
to
r
th
at
will
b
e
s
tu
d
ied
in
th
is
p
ap
er
is
o
f
th
e
s
ep
ar
ately
ex
cited
(
SEDC)
ty
p
e,
an
d
f
o
cu
s
in
g
o
n
s
p
ee
d
c
o
n
tr
o
l
o
f
DC
m
o
to
r
.
T
h
e
s
ch
em
atic
o
f
t
h
e
S
E
DC
m
o
to
r
is
s
h
o
wn
in
Fi
g
u
r
e
1
[9
]
-
[
1
1
]
.
Fig
u
r
e
1
.
T
h
e
s
ch
em
atic
d
iag
r
am
o
f
SEDC m
o
to
r
Usi
n
g
th
e
Kir
ch
h
o
f
f
'
s
law,
we
ca
n
g
et
th
e
f
o
llo
win
g
e
q
u
atio
n
o
b
tain
ed
:
V
a
=
I
a
R
a
+
L
a
d
I
a
dt
+
E
b
(
1
)
E
b
=
K
b
ω
I
f
(
2
)
T
=
K
t
I
a
I
f
(
3
)
T
=
J
d
ω
dt
+
B
ω
+
T
L
(
4
)
wh
er
e:
=
ar
m
atu
r
e
i
n
d
u
ctan
ce
(
H)
=
ar
m
atu
r
e
r
esis
tan
ce
(
Ω
)
=
ar
m
atu
r
e
v
o
ltag
e
(
V
)
E
b
=
b
ac
k
elec
tr
o
m
o
tiv
e
f
o
r
ce
(
e.
m
.
f
.
)
(
V)
ia
=
ar
m
atu
r
e
c
u
r
r
en
t
(
A)
T
L
=
L
o
ad
to
r
q
u
e
(
Nm
)
B
m
=
Vis
co
u
s
f
r
ictio
n
co
ef
f
ici
en
t (
Nm
s
/r
ad
)
if
=
Field
cu
r
r
en
t
(
A)
J
=
R
o
to
r
in
er
tia
(
k
g
m
2
)
=
T
o
r
q
u
e
co
n
s
tan
t (
Nm
-
s
/r
ad
)
=
B
ac
k
em
f
co
n
s
tan
t (
Vs/
r
ad
)
T
h
e
T
r
an
s
f
er
f
u
n
ctio
n
T
.
F
o
f
th
e
ar
m
atu
r
e
-
c
o
n
tr
o
lled
D
C
m
o
to
r
g
iv
en
b
y
(
5
)
.
B
lo
c
k
d
iag
r
am
ex
p
r
ess
ed
in
(
6
)
is
f
o
llo
win
g
in
Fig
u
r
e
2
.
T
h
e
DC
m
o
to
r
t
est
m
o
d
el
p
ar
a
m
eter
s
f
o
r
th
is
s
tu
d
y
ar
e
g
iv
e
n
in
T
ab
le
1
.
n
o
w,
th
e
D.
C
.
m
o
t
o
r
ca
n
b
e
r
e
p
r
esen
ted
b
y
T
.
F sh
o
wn
in
(
6
)
.
ω
(
s
)
V
a
(
s
)
=
K
t
(
Js
+
B
m
)
(
R
a
+
L
a
s
)
+
K
t
K
b
(
5
)
ω
(
s
)
V
a
(
s
)
=
K
t
(
L
a
J
)
s
2
+
(
R
a
J
+
L
a
B
m
)
s
+
(
R
a
B
m
+
K
t
K
b
)
(
6
)
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
I
mp
leme
n
tin
g
o
p
timiz
a
tio
n
o
f
P
I
D
co
n
tr
o
ller
fo
r
DC
mo
to
r
s
p
ee
d
co
n
tr
o
l
(
Ya
s
ir
G.
R
a
s
h
id
)
659
Fig
u
r
e
2
.
DC
Mo
to
r
B
lo
ck
Diag
r
am
T
ab
le
1
.
I
m
p
lem
en
tatio
n
p
ar
a
m
eter
s
o
f
DC
m
o
to
r
[
1
2
]
P
a
r
a
me
t
e
r
s
V
a
l
u
e
A
r
mat
u
r
e
i
n
d
u
c
t
a
n
c
e
(
H
e
n
r
y
)
L
=
0
.
1
2
1
5
H
A
r
mat
u
r
e
r
e
s
i
st
a
n
c
e
(
o
h
m)
R
=
1
1
.
2
Ω
R
o
t
o
r
i
n
e
r
t
i
a
(
k
g
m
2
)
J
m
=
0
.
0
2
2
1
5
k
g
-
m
2
V
i
sco
u
s
f
r
i
c
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
(
N
m
s/
r
a
d
)
B
m
=
0
.
0
0
2
9
5
3
N
m
-
s/
r
a
d
M
o
t
o
r
t
o
r
q
u
e
c
o
n
s
t
a
n
t
(
N
m/
A
)
K
t
=
1
.
2
8
N
m/
A
B
a
c
k
e
mf
c
o
n
st
a
n
t
(
V
s
/
r
a
d
)
K
b
=
1
.
2
8
V
s/
r
a
d
S
p
e
e
d
1
5
0
0
r
p
m
T
h
u
s
,
th
e
f
in
al
o
f
T.F
is
s
h
o
w
n
in
(
7
).
w
(
s
)
V
a
(
s
)
=
1
.
28
0
.
0027
s
2
+
0
.
2481s
+
1
.
671
(
7
)
3.
P
I
D
CO
NT
RO
L
L
E
R
T
h
e
p
r
o
p
o
r
tio
n
al
-
in
teg
r
al
-
d
er
i
v
ativ
e
(
PID
)
c
o
n
tr
o
ller
is
s
im
p
le
to
u
s
e
a
n
d
s
et
u
p
,
an
d
it
is
wid
ely
u
s
ed
in
in
d
u
s
tr
ial
ap
p
licatio
n
s
f
o
r
s
p
ee
d
co
n
t
r
o
l
o
f
d
c
m
o
to
r
s
d
u
e
to
its
p
r
o
p
er
co
n
tr
o
l
p
er
f
o
r
m
an
ce
a
n
d
lack
o
f
co
m
p
lex
ity
in
d
esig
n
[8
]
,
[
13
]
,
[
1
4
]
.
T
h
e
PID
co
n
tr
o
ller
f
o
r
m
is
s
h
o
wn
in
(
8
).
G(
s
)
=
K
p
+
K
i
s
+
K
d
s
(
8
)
W
h
er
e
G(
s
)
is
th
e
tr
an
s
f
er
f
u
n
ctio
n
o
f
PID
,
K
p
,
K
i
an
d
K
d
in
d
icate
p
ar
am
eter
g
ain
o
f
PID
.
T
o
im
p
r
o
v
e
th
e
p
er
f
o
r
m
an
ce
o
f
an
y
s
y
s
tem
,
th
er
e
m
u
s
t
b
e
p
r
o
p
er
co
n
tr
o
ller
tu
n
i
n
g
.
T
h
e
s
ettin
g
o
f
th
e
p
r
o
p
er
p
ar
am
eter
v
al
u
e
o
f
a
co
n
tr
o
lle
r
in
d
icate
s
tu
n
in
g
it.
T
h
e
r
esp
o
n
s
e
o
f
t
h
e
s
y
s
tem
b
ec
o
m
es
u
n
s
tab
le
an
d
p
o
o
r
,
if
im
p
r
o
p
e
r
v
alu
e
o
f
g
ain
p
ar
a
m
eter
s
o
f
a
co
n
t
r
o
ller
is
u
s
e
d
[
1
5
]
,
[
1
6
]
.
T
h
er
ef
o
r
e,
im
p
l
em
en
tatio
n
o
f
PID
T
u
n
in
g
is
cr
itical
to
th
e
co
n
tr
o
ller
tu
n
in
g
s
u
itab
le
to
in
d
u
ce
th
e
f
av
o
r
ed
r
esp
o
n
s
e.
Fig
u
r
e
3
illu
s
tr
ates
th
e
s
p
ee
d
co
n
tr
o
l
s
y
s
tem
f
o
r
DC
m
o
to
r
u
s
in
g
a
PID
co
n
tr
o
lle
r
.
T
u
n
i
n
g
o
f
PID
co
n
tr
o
l
c
an
b
e
d
o
n
e
b
y
m
an
y
m
eth
o
d
s
.
T
h
is
p
a
p
er
d
is
cu
s
s
es th
r
ee
m
eth
o
d
s
th
at
will b
e
u
s
e
d
:
Fig
u
r
e
3
.
A
PID
co
n
tr
o
l D
C
m
o
to
r
s
p
ee
d
s
y
s
tem
3.
1
.
M
AT
AL
B
P
I
D
t
un
ner
a
pp
B
y
u
tili
zin
g
PID
T
u
n
er
Ap
p
licatio
n
in
MA
T
AL
B
R
2
0
1
8
a
s
o
f
twar
e
will
o
b
tain
g
ain
p
ar
am
eter
s
o
f
PID
co
n
tr
o
ller
Kp
=
7
.
6
3
2
,
Ki
=
9
5
.
7
3
3
,
Kd
=
0
.
0
3
8
3
an
d
N=
3
8
2
.
9
9
8
.
Fig
u
r
e
4
d
ep
icts
th
e
r
esp
o
n
s
e
o
f
th
e
DC
m
o
r
o
r
t
r
ail
an
d
e
r
r
o
r
,
as we
ll a
s
th
e
tim
e
ch
ar
ac
ter
is
tics
.
[
17
]
-
[
19
].
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
.
2
,
Au
g
u
s
t 2
0
2
1
:
65
7
-
66
4
660
3.
2
.
M
o
dified
Z
ieg
ler
-
Nicho
ls
m
et
ho
d
Dep
en
d
in
g
o
n
th
e
ch
ien
-
h
r
o
n
es
-
r
eswick
(
C
H
R
)
alg
o
r
ith
m
h
as
b
ee
n
o
b
tain
ed
.
T
h
e
m
o
d
if
ied
Z
ieg
ler
-
Nich
o
ls
(
MZ
N)
tu
n
in
g
f
o
cu
s
es
o
n
d
is
tu
r
b
an
ce
r
ej
ec
tio
n
.
I
n
a
d
d
itio
n
,
r
esp
o
n
s
e
an
d
o
v
e
r
s
h
o
o
t
ca
n
ac
co
m
m
o
d
ate
o
n
e
o
f
th
e
q
u
a
litativ
e
s
p
ec
if
icatio
n
s
T
h
e
MZ
N
m
eth
o
d
is
m
o
r
e
p
o
wer
f
u
l
co
m
p
a
r
ed
t
o
th
e
class
ical
Z
ieg
ler
-
Nich
o
ls
tu
n
in
g
,
th
e
tim
e
co
n
s
tan
t
T
o
f
th
e
p
lan
t
will
b
e
u
s
ed
.
T
h
e
MZ
N
tu
n
in
g
f
o
r
m
u
las
ar
e
g
iv
en
in
T
ab
le
2
[
20
]
-
[
2
1
]
.
F
r
o
m
r
esp
o
n
s
e
cu
r
v
e
o
f
T
.
F
i
n
(
7
)
as
s
h
o
wn
i
n
Fig
u
r
e
5
c
an
b
e
o
b
tain
ed
th
e
p
ar
am
eter
s
a,
L
an
d
T
,
a=
0
.
0
3
4
3
,
L
=
0
.
0
0
7
7
,
T
=
0
.
2
2
5
9
.
W
e
w
ill
g
et:
K
p
=
2
7
.
7
,
K
i
=K
p
/T
i
=8
7
.
5
8
6
an
d
K
d
=K
p
*T
d
=0
.
1
0
0
2
.
T
ab
le
2
.
MZ
N
tu
n
in
g
f
o
r
m
u
las [
1
9
]
C
o
n
t
r
o
l
l
e
r
Ty
p
e
K
p
T
i
T
d
P
0
.
7
/
a
PI
0
.
6
/
a
T
P
I
D
0
.
9
5
/
a
1
.
4
T
0
.
4
7
L
Fig
u
r
e
4
.
R
esp
o
n
s
e
o
f
PID
tu
n
n
er
ap
p
.
f
o
r
DC
m
o
to
r
Fig
u
r
e
5
.
R
esp
o
n
s
e
c
u
r
v
e
f
o
r
MZ
N
3
.
3
.
G
enet
ic
a
lg
o
rit
h
m
f
o
r
P
I
D
t
un
ing
A
g
en
etic
alg
o
r
ith
m
is
an
o
p
tim
izatio
n
tech
n
iq
u
e
wh
ich
is
an
o
f
f
s
h
o
o
t
o
f
n
atu
r
al
s
elec
tio
n
ap
p
lied
to
th
e
ef
f
ec
t
o
f
cr
ea
tin
g
d
iv
er
s
it
y
[
3
]
.
T
h
e
s
tar
tin
g
p
o
p
u
latio
n
co
n
tain
s
th
e
n
u
m
b
er
o
f
ch
r
o
m
o
s
o
m
es,
wh
ich
ar
e
u
s
ed
as
p
r
o
b
lem
-
s
o
lv
in
g
to
o
l
s
,
wh
ich
ar
e
th
en
test
ed
ac
c
o
r
d
in
g
to
th
eir
a
b
ilit
y
to
e
x
ec
u
te
th
e
s
o
lu
tio
n
.
Dep
en
d
in
g
o
n
th
e
f
itn
ess
o
f
e
ac
h
p
er
s
o
n
,
th
r
ee
co
m
m
o
n
p
r
o
ce
s
s
es
ar
e
p
er
f
o
r
m
ed
:
s
elec
tio
n
,
cr
o
s
s
o
v
er
,
a
n
d
m
u
tatio
n
[
2
2
]
,
[
2
3
]
.
On
ce
th
ese
th
r
ee
s
im
p
le
o
p
e
r
atio
n
s
a
r
e
ap
p
lied
,
n
ew
in
d
iv
id
u
als
c
an
r
esu
lt
i
n
b
etter
s
o
lu
tio
n
s
.
T
h
e
p
a
r
a
m
e
t
e
r
s
o
f
p
o
p
u
l
a
t
i
o
n
s
i
z
e
,
c
r
o
s
s
o
v
e
r
r
at
e
(
Pc
)
,
m
u
t
a
t
i
o
n
r
a
t
e
(
P
m
)
a
n
d
t
h
e
n
u
m
b
e
r
o
f
g
e
n
e
r
a
t
i
o
n
s
a
r
e
t
h
e
s
t
a
r
t
i
n
g
p
o
i
n
t
s
f
o
r
G
A
.
B
y
s
e
q
u
e
n
t
i
al
l
y
s
e
t
ti
n
g
t
h
e
P
I
D
p
a
r
a
m
e
t
e
r
s
,
k
p
,
k
i
,
a
n
d
k
d
,
t
h
e
p
o
p
u
l
a
t
i
o
n
i
s
e
n
c
o
d
e
d
i
n
b
i
n
a
r
y
s
t
r
i
n
g
s
d
e
f
i
n
e
d
as
t
h
e
w
ay
t
h
a
t
i
t
is
T
h
e
f
i
t
n
ess
o
f
e
ac
h
c
h
r
o
m
o
s
o
m
e
i
s
c
a
l
c
u
l
a
te
d
b
y
t
a
k
i
n
g
i
ts
tw
o
-
d
im
e
n
s
i
o
n
a
l
s
t
r
i
n
g
s
a
n
d
t
r
a
n
s
f
o
r
m
i
n
g
t
h
e
m
i
n
t
o
r
e
a
l
v
a
l
u
e
s
,
a
n
d
r
e
p
l
a
c
i
n
g
t
h
e
m
w
i
t
h
o
b
j
e
c
t
i
v
e
(
f
i
t
n
es
s
)
f
u
n
c
t
i
o
n
.
I
n
t
h
i
s
s
t
u
d
y
,
w
e
w
i
l
l
b
e
u
s
i
n
g
a
n
o
p
t
i
m
i
z
a
ti
o
n
t
o
o
l
i
n
M
A
T
L
A
B
[
2
4
]
,
[
2
5
]
.
T
h
e
G
A
p
a
r
a
m
e
t
e
r
s
i
n
t
h
i
s
s
t
u
d
y
a
r
e
s
h
o
w
n
i
n
T
a
b
l
e
3
.
As
i
l
l
u
s
t
r
at
e
d
in
F
i
g
u
r
e
6
,
t
h
e
G
A
S
t
e
p
F
l
o
w
ch
a
r
t
s
h
o
w
s
.
T
ab
le
3
.
Par
am
eter
s
ettin
g
o
f
g
en
etic
alg
o
r
ith
m
P
a
r
a
me
t
e
r
V
a
l
u
e
Lo
w
e
r
b
o
u
n
d
[
K
p
K
i
K
d
]
[
0
0
0
]
U
p
p
e
r
b
o
u
n
d
[
K
p
K
i
K
d
]
[
1
0
0
5
0
5
]
P
o
p
u
l
a
t
i
o
n
s
20
G
e
n
e
r
a
t
i
o
n
s G
80
P
o
p
u
l
a
t
i
o
n
t
y
p
e
D
o
u
b
l
e
v
e
c
t
o
r
C
r
o
ss
o
v
e
r
r
a
t
e
P
c
0
.
8
M
u
t
a
t
i
o
n
r
a
t
e
P
m
0
.
0
1
El
i
t
e
c
o
u
n
t
5
S
e
l
e
c
t
i
o
n
f
u
n
c
t
i
o
n
S
t
o
c
h
a
st
i
c
u
n
i
f
o
r
m
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
I
mp
leme
n
tin
g
o
p
timiz
a
tio
n
o
f
P
I
D
co
n
tr
o
ller
fo
r
DC
mo
to
r
s
p
ee
d
co
n
tr
o
l
(
Ya
s
ir
G.
R
a
s
h
id
)
661
Fig
u
r
e
6
.
Flo
wch
ar
t
f
o
r
o
p
tim
al
PID
tu
n
in
g
b
ased
o
n
g
en
eti
c
alg
o
r
ith
m
[
2
5
]
4.
SI
M
UL
A
T
I
O
N
R
E
S
UL
T
S
Fig
u
r
e
7
s
h
o
ws
s
p
ee
d
co
n
tr
o
l
o
f
th
e
DC
m
o
to
r
s
y
s
tem
in
Ma
tlab
Simu
lin
k
f
o
r
v
ar
i
o
u
s
PID
tu
n
in
g
m
eth
o
d
s
.
I
n
t
h
is
s
im
u
latio
n
t
ak
es
v
ar
io
u
s
ca
s
es
:
c
ase
i
)
:
n
o
-
lo
ad
o
p
er
atio
n
.
(
at
t=
1
s
)
;
ca
s
e
ii
)
:
f
u
ll
-
lo
ad
o
p
er
atio
n
(
at
t=3
s
)
T
L
=
3
0
0
N
m
;
ca
s
e
iii
)
:
c
h
an
g
e
r
o
tatio
n
s
p
ee
d
.
(
at
t=5
s
)
.
As
s
h
o
wn
in
Fig
u
r
es
8
(
MA
T
AL
B
PID
tu
n
n
er
ap
p
.
)
a
n
d
9
(
MZ
N)
,
co
m
p
ar
ed
to
Fig
u
r
e
1
0
(
P
I
D
-
g
en
etic
alg
o
r
ith
m
)
tu
n
in
g
m
eth
o
d
c
o
n
tr
o
l
with
co
n
v
en
tio
n
al
PID
m
eth
o
d
s
with
in
th
e
d
esire
d
s
p
ee
d
o
f
N
=1
5
0
0
r
p
m
,
At
t=1
s
,
th
e
m
o
t
o
r
'
s
s
p
ee
d
r
esp
o
n
s
e
cu
r
v
e
r
ea
c
h
es
a
s
tead
y
s
tate
in
a
s
h
o
r
t
p
er
io
d
o
f
tim
e
with
n
o
o
v
er
s
h
o
o
t;
at
t=3
s
,
wh
en
th
e
m
o
to
r
is
r
u
n
n
in
g
at
f
u
ll
lo
ad
,
th
e
s
p
ee
d
r
esp
o
n
s
e
cu
r
v
e
d
ec
r
ea
s
es
s
lig
h
tly
an
d
r
etu
r
n
s
to
th
e
d
esire
d
s
p
ee
d
m
o
r
e
q
u
ick
ly
.
T
h
e
s
y
s
tem
s
h
o
ws
g
r
ea
t
d
y
n
am
ic
ch
ar
ac
ter
is
tics
an
d
th
e
r
o
b
u
s
tn
ess
i
s
g
r
ea
tly
im
p
r
o
v
ed
.
Fi
g
u
r
e
1
1
s
h
o
ws
th
e
co
m
p
ar
is
o
n
o
f
th
e
s
p
ee
d
r
esp
o
n
s
e
cu
r
v
e
o
f
a
m
o
to
r
b
y
u
s
in
g
v
ar
io
u
s
tu
n
in
g
m
et
h
o
d
s
o
f
PID
co
n
tr
o
ller
,
as
it
ca
n
b
e
s
ee
n
th
at
th
e
p
er
f
o
r
m
an
ce
o
f
ea
ch
m
eth
o
d
is
d
if
f
er
en
t
in
s
ettlin
g
tim
e
T
s
,
r
i
s
e
tim
e
T
r
an
d
p
ea
k
o
v
er
s
h
o
o
t
M
p
.
PID
tu
n
in
g
p
r
o
d
u
ce
s
a
s
lo
wer
r
esp
o
n
s
e
b
u
t
h
as
a
lo
wer
p
er
ce
n
tag
e
o
f
o
v
er
s
h
o
o
t
th
an
m
o
d
i
f
ied
Z
ieg
ler
-
Nich
o
ls
tu
n
in
g
.
T
h
e
g
en
etic
alg
o
r
ith
m
tu
n
in
g
m
eth
o
d
p
r
o
v
id
es
b
etter
r
esp
o
n
s
e
co
m
p
ar
e
d
with
co
n
v
en
tio
n
al
m
eth
o
d
s
.
I
n
T
a
b
l
e
4
s
h
o
ws th
e
p
er
f
o
r
m
a
n
ce
o
f
ea
ch
m
eth
o
d
.
Fig
u
r
e
7
.
Simu
lin
k
m
o
d
el
o
f
v
ar
io
u
s
PID
tu
n
in
g
m
eth
o
d
s
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
.
2
,
Au
g
u
s
t 2
0
2
1
:
65
7
-
66
4
662
T
ab
le
4
.
C
o
m
p
a
r
is
o
n
b
etwe
en
th
e
p
er
f
o
r
m
an
ce
o
f
v
ar
io
u
s
PI
D
tu
n
in
g
m
et
h
o
d
s
Tu
n
i
n
g
me
t
h
o
d
M
p
%
T
r
(
s)
T
s
(
s)
S
t
e
a
d
y
st
a
t
e
e
r
r
o
r
Tu
n
e
r
A
d
d
s
1
8
.
3
7
0
.
1
5
1
.
4
3
0
M
ZN
9
.
6
5
0
.
1
2
1
.
2
6
0
GA
0
0
.
0
5
6
1
.
1
2
0
Fig
u
r
e
8
.
Sp
ee
d
v
er
s
u
s
tim
e
w
ith
r
ef
er
en
ce
s
p
ee
d
o
f
PID
co
n
tr
o
ller
b
ased
o
n
PID
tu
n
n
e
r
ap
p
Fig
u
r
e
9
.
Sp
ee
d
v
er
s
u
s
tim
e
w
ith
r
ef
er
en
ce
s
p
ee
d
o
f
PID
co
n
tr
o
ller
b
ased
o
n
MZN
Fig
u
r
e
10
.
Sp
ee
d
v
e
r
s
u
s
tim
e
with
r
ef
er
en
ce
s
p
ee
d
o
f
PID
c
o
n
tr
o
ller
b
ased
o
n
GA
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
I
mp
leme
n
tin
g
o
p
timiz
a
tio
n
o
f
P
I
D
co
n
tr
o
ller
fo
r
DC
mo
to
r
s
p
ee
d
co
n
tr
o
l
(
Ya
s
ir
G.
R
a
s
h
id
)
663
Fig
u
r
e
1
1
.
Sp
ee
d
v
e
r
s
u
s
tim
e
with
r
ef
er
en
ce
s
p
ee
d
o
f
PID
c
o
n
tr
o
ller
b
ased
o
n
Z
-
N,
tu
n
n
er
ap
p
.
a
n
d
GA
5.
CO
NCLU
SI
O
N
A
DC
m
o
to
r
s
p
ee
d
co
n
tr
o
l
u
s
in
g
g
en
etic
alg
o
r
ith
m
o
p
tim
iz
atio
n
to
d
eter
m
in
e
th
e
p
r
o
p
er
v
alu
e
g
ain
o
f
PID
p
ar
am
eter
is
p
r
esen
ted
in
th
is
p
ap
er
.
As
well,
co
m
p
ar
es
its
p
er
f
o
r
m
an
ce
with
co
n
v
en
tio
n
al
m
eth
o
d
s
MA
T
AL
B
PID
tu
n
n
er
ap
p
.
a
n
d
Mo
d
if
ied
Z
ieg
ler
-
Nich
o
ls
.
T
h
e
r
esu
lts
o
b
tain
ed
b
y
PID
-
g
en
etic
alg
o
r
ith
m
co
m
p
ar
ed
to
o
th
er
m
eth
o
d
s
,
s
h
o
w
a
h
ig
h
-
p
er
f
o
r
m
an
ce
r
esp
o
n
s
e
f
o
r
DC
m
o
to
r
s
u
ch
as
le
s
s
s
ettl
in
g
tim
e,
less
r
is
e
tim
e,
r
ed
u
ce
d
s
tead
y
s
tate
er
r
o
r
an
d
n
o
o
v
er
s
h
o
o
t
r
ate.
T
h
e
PID
-
GA
tu
n
in
g
m
eth
o
d
a
s
a
s
p
ee
d
co
n
tr
o
ller
f
o
r
t
h
e
DC
m
o
to
r
is
a
v
er
y
ef
f
ec
tiv
e
m
eth
o
d
.
T
h
e
p
r
o
p
o
s
ed
s
y
s
tem
's
p
er
f
o
r
m
an
ce
is
im
p
r
o
v
ed
a
n
d
r
ea
ch
es
t
h
e
r
eq
u
ir
ed
r
eq
u
i
r
em
en
ts
.
RE
F
E
R
E
NC
E
S
[1
]
D.
S
o
m
wa
n
sh
i
,
M
.
B
u
n
d
e
le,
G
.
Ku
m
a
r,
a
n
d
G
.
P
a
ra
sh
a
r,
“
Co
m
p
a
riso
n
o
f
f
u
z
z
y
-
P
ID
a
n
d
P
ID
c
o
n
tro
ll
e
r
f
o
r
sp
e
e
d
c
o
n
tro
l
o
f
DC
m
o
to
r
u
si
n
g
Lab
VIEW
,
”
Pro
c
e
d
i
a
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
1
5
2
,
p
p
.
2
5
2
-
2
6
0
,
2
0
1
9
,
d
o
i:
1
0
.
1
0
1
6
/j
.
p
ro
c
s.
2
0
1
9
.
0
5
.
0
1
9
.
[2
]
S
.
Ek
i
n
c
i,
B.
He
k
imo
ğ
l
u
,
a
n
d
D.
Iz
c
i,
“
Op
p
o
siti
o
n
b
a
se
d
He
n
ry
g
a
s
so
lu
b
il
it
y
o
p
ti
m
iza
ti
o
n
a
s
a
n
o
v
e
l
a
lg
o
rit
h
m
fo
r
P
ID
c
o
n
tro
l
o
f
DC
m
o
to
r,
”
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
,
a
n
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
,
v
o
l.
2
4
,
n
o
.
2
,
2
0
2
1
,
d
o
i:
1
0
.
1
0
1
6
/j
.
jes
tch
.
2
0
2
0
.
0
8
.
0
1
1
.
[3
]
T.
El
-
De
e
n
,
A.
A.
H
.
M
a
h
m
o
u
d
,
a
n
d
A.
R.
El
-
S
a
wi,
“
Op
t
ima
l
P
ID
tu
n
in
g
fo
r
DC
m
o
to
r
sp
e
e
d
c
o
n
tr
o
ll
e
r
b
a
se
d
o
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
”
I
n
t.
Rev
.
Au
t
o
m.
Co
n
tr
o
l
,
v
o
l.
8
,
n
o
.
1
,
p
p
.
8
0
-
8
5
,
2
0
1
5
,
d
o
i:
1
0
.
1
5
8
6
6
/i
re
a
c
o
.
v
8
i
1
.
4
8
3
9
.
[4
]
J.
Ag
a
rwa
l,
G
.
P
a
rm
a
r,
R.
G
u
p
ta,
a
n
d
A.
S
i
k
a
n
d
e
r,
“
An
a
l
y
sis
o
f
g
re
y
wo
lf
o
p
ti
m
ize
r
b
a
se
d
fra
c
ti
o
n
a
l
o
r
d
e
r
P
ID
c
o
n
tro
ll
e
r
in
sp
e
e
d
c
o
n
tr
o
l
o
f
DC
m
o
to
r,
”
M
icr
o
sy
ste
m
T
e
c
h
n
o
lo
g
ies
,
v
o
l.
2
4
,
n
o
.
1
2
,
p
p
.
4
9
9
7
-
5
0
0
6
,
2
0
1
8
,
d
o
i:
1
0
.
1
0
0
7
/s0
0
5
4
2
-
0
1
8
-
3
9
2
0
-
4.
[5
]
M
.
A.
I
b
ra
h
im,
A
.
K.
M
a
h
m
o
o
d
,
a
n
d
N.
S
.
S
u
lt
a
n
,
“
Op
ti
m
a
l
P
ID
c
o
n
tro
ll
e
r
o
f
a
b
r
u
sh
les
s
d
c
m
o
to
r
u
sin
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
m
(IJ
PE
DS
)
,
v
o
l.
1
0
,
n
o
.
2
,
p
.
8
2
2
,
2
0
1
9
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
p
e
d
s
.
v
1
0
.
i
2
.
p
p
8
2
2
-
8
3
0
.
[6
]
R
.
V
.
Ja
i
n
,
M
.
V
.
A
wa
r
e
,
a
n
d
A
.
S
.
J
u
n
g
h
a
r
e
,
“
T
u
n
i
n
g
o
f
F
r
a
c
t
i
o
n
a
l
O
r
d
e
r
P
I
D
c
o
n
t
r
o
l
l
e
r
u
s
i
n
g
p
a
r
t
i
c
l
e
s
w
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
t
e
c
h
n
i
q
u
e
f
o
r
D
C
m
o
t
o
r
s
p
e
e
d
c
o
n
t
r
o
l
,
”
2
0
1
6
I
E
E
E
1
s
t
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
P
o
w
e
r
E
l
e
c
t
r
o
n
i
c
s
,
I
n
t
e
l
l
i
g
e
n
t
C
o
n
t
r
o
l
a
n
d
E
n
e
r
g
y
S
y
s
t
e
m
s
(
IC
P
E
I
C
E
S
)
,
2
0
1
6
,
p
p
.
1
-
4
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
P
E
I
C
E
S
.
2
0
1
6
.
7
8
5
3
0
7
0
.
[7
]
L.
S
y
a
fa
a
h
,
W
id
ian
to
,
I
.
P
a
k
a
y
a
,
D.
S
u
h
a
r
d
i,
a
n
d
M
.
Irfa
n
,
“
P
ID d
e
sig
n
s u
si
n
g
DE
a
n
d
P
S
O alg
o
r
it
h
m
s fo
r
d
a
m
p
in
g
o
sc
il
latio
n
s
in
a
DC
m
o
t
o
r
sp
e
e
d
,
”
4
th
I
n
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
El
e
c
tric
a
l
E
n
g
i
n
e
e
rin
g
,
Co
mp
u
ter
S
c
ien
c
e
a
n
d
In
fo
rm
a
t
ics
(EE
CS
I)
,
v
o
l.
2
0
1
7
-
D
e
c
e
m
b
e
r,
n
o
.
S
e
p
tem
b
e
r
,
2
0
1
7
,
p
p
.
1
9
-
21
,
d
o
i:
1
0
.
1
1
0
9
/
EE
CS
I.
2
0
1
7
.
8
2
3
9
1
3
8
.
[8
]
G
.
A.
S
a
lma
n
,
A.
S
.
Ja
fa
r,
a
n
d
A.
I.
Ism
a
e
l,
“
Ap
p
li
c
a
ti
o
n
o
f
a
rti
ficia
l
in
telli
g
e
n
c
e
tec
h
n
iq
u
e
s
fo
r
LF
C
a
n
d
AV
R
sy
ste
m
s
u
sin
g
P
ID
c
o
n
tro
ll
e
r,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
P
o
we
r
E
lec
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
(IJ
PE
DS
)
,
v
o
l.
1
0
,
n
o
.
3
,
p
p
.
1
6
9
4
,
2
0
1
9
,
d
o
i:
1
0
.
1
1
5
9
1
/i
j
p
e
d
s.
v
1
0
.
i
3
.
p
p
1
6
9
4
-
1
7
0
4
.
[9
]
K
.
M
ish
ra
,
V.
K
.
Ti
wa
ri,
R.
Ku
m
a
r,
a
n
d
T
.
Ve
rm
a
,
“
S
p
e
e
d
C
o
n
tro
l
o
f
DC
M
o
t
o
r
Us
in
g
Art
ifi
c
i
a
l
Be
e
Co
lo
n
y
Op
ti
m
iza
ti
o
n
Tec
h
n
iq
u
e
,
”
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Co
n
tro
l,
Au
t
o
ma
t
io
n
,
Ro
b
o
ti
c
s
a
n
d
Emb
e
d
d
e
d
S
y
ste
ms
(CAR
E)
,
v
o
l.
1
,
n
o
.
3
,
2
0
1
3
,
p
p
.
6
8
-
7
5
,
d
o
i:
1
0
.
1
3
1
8
9
/
u
jee
e
.
2
0
1
3
.
0
1
0
3
0
2
.
[1
0
]
G
.
F
a
ra
h
a
n
i
a
n
d
K.
Ra
h
m
a
n
i,
“
S
p
e
e
d
c
o
n
tro
l
o
f
a
se
p
a
ra
tely
e
x
c
i
ted
DC
m
o
t
o
r
u
sin
g
n
e
w
p
ro
p
o
s
e
d
fu
z
z
y
n
e
u
ra
l
a
lg
o
rit
h
m
b
a
se
d
o
n
F
OPID
c
o
n
t
ro
ll
e
r,
”
J
o
u
rn
a
l
o
f
Co
n
tro
l
,
A
u
t
o
ma
ti
o
n
a
n
d
El
e
c
trica
l
S
y
ste
m
s
,
v
o
l.
3
0
,
n
o
.
5
,
p
p
.
7
2
8
-
7
4
0
,
2
0
1
9
,
d
o
i:
1
0
.
1
0
0
7
/s
4
0
3
1
3
-
0
1
9
-
0
0
4
8
5
-
8
.
[1
1
]
Ab
d
u
lam
e
e
r,
M
.
S
u
laim
a
n
,
M
.
S
.
M
.
Ara
s,
a
n
d
D.
S
a
lee
m
,
“
Tu
n
in
g
m
e
th
o
d
s
o
f
P
ID
c
o
n
tro
ll
e
r
f
o
r
DC
m
o
to
r
sp
e
e
d
c
o
n
tro
l,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
E
lec
trica
l
En
g
in
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
(IJ
EE
CS
)
,
v
o
l.
3
,
n
o
.
2
,
p
p
.
3
4
3
-
3
4
9
,
2
0
1
6
,
d
o
i:
1
0
.
1
1
5
9
1
/i
jee
c
s.v
3
.
i2
.
p
p
3
4
3
-
3
4
9
.
[1
2
]
S
.
K.
S
u
m
a
n
a
n
d
V.
K
.
G
iri
,
“
S
p
e
e
d
c
o
n
tr
o
l
o
f
DC
m
o
to
r
u
sin
g
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s
b
a
se
d
P
ID
Co
n
tro
l
ler,”
i
n
2
0
1
6
IEE
E
In
ter
n
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
E
n
g
in
e
e
rin
g
a
n
d
T
e
c
h
n
o
l
o
g
y
(IC
ET
ECH)
,
2
0
1
6
,
p
p
.
5
8
1
-
5
8
7
,
d
o
i:
1
0
.
1
1
0
9
/ICE
T
ECH.
2
0
1
6
.
7
5
6
9
3
1
8
.
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
.
2
,
Au
g
u
s
t 2
0
2
1
:
65
7
-
66
4
664
[1
3
]
D.
P
a
th
a
k
,
G
.
S
a
g
a
r,
a
n
d
P
.
G
a
u
r,
“
An
Ap
p
li
c
a
ti
o
n
o
f
In
telli
g
e
n
t
No
n
-
li
n
e
a
r
Disc
re
te
-
P
ID
Co
n
tro
ll
e
r
fo
r
M
P
P
T
o
f
P
V
S
y
ste
m
,
”
Pro
c
e
d
ia
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
1
6
7
,
n
o
.
2
0
1
9
,
p
p
.
1
5
7
4
-
1
5
8
3
,
2
0
2
0
,
d
o
i:
1
0
.
1
0
1
6
/j
.
p
ro
c
s.
2
0
2
0
.
0
3
.
3
6
8
.
[1
4
]
G
.
A.
S
a
lma
n
,
H.
I.
Hu
ss
e
in
,
a
n
d
M
.
S
.
Ha
sa
n
,
“
E
n
h
a
n
c
e
m
e
n
t
T
h
e
Dy
n
a
m
ic
S
tab
il
it
y
o
f
Th
e
Ira
q
’
s
P
o
we
r
S
tatio
n
Us
in
g
P
ID
C
o
n
tro
ll
e
r
O
p
ti
m
ize
d
b
y
F
A
a
n
d
P
S
O
Ba
se
d
o
n
Diffe
re
n
t
Ob
jec
ti
v
e
F
u
n
c
ti
o
n
s,”
El
e
k
tro
t
e
h
n
isk
i
Ves
tn
ik
,
v
o
l.
8
5
,
n
o
.
1
/
2
,
p
p
.
4
2
-
4
8
,
2
0
1
8
.
[1
5
]
S
.
Ti
wa
ri,
A.
B
h
a
tt
,
A.
C.
U
n
n
i
,
J.
G
.
S
in
g
h
,
a
n
d
W
.
On
g
sa
k
u
l
,
“
Co
n
tro
l
o
f
DC
m
o
t
o
r
u
sin
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
b
a
se
d
p
id
c
o
n
tr
o
ll
e
r
,
”
in
2
0
1
8
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
a
n
d
Util
i
ty
Exh
ib
it
i
o
n
o
n
Gr
e
e
n
En
e
rg
y
f
o
r
S
u
st
a
in
a
b
le
De
v
e
lo
p
me
n
t
(ICUE)
,
2
0
1
8
,
p
p
.
1
-
6
,
d
o
i:
1
0
.
2
3
9
1
9
/ICUE
-
G
ES
D.2
0
1
8
.
8
6
3
5
6
6
2
.
[1
6
]
W.
-
J.
Tan
g
,
Z.
-
T.
Li
u
,
a
n
d
Q.
W
a
n
g
,
“
Dc
m
o
to
r
sp
e
e
d
c
o
n
tro
l
b
a
se
d
o
n
sy
ste
m
id
e
n
ti
fica
ti
o
n
a
n
d
p
id
a
u
to
tu
n
in
g
,
”
in
2
0
1
7
3
6
t
h
C
h
in
e
se
Co
n
tro
l
C
o
n
fer
e
n
c
e
(CCC)
,
2
0
1
7
,
p
p
.
6
4
2
0
-
6
4
2
3
,
d
o
i:
1
0
.
2
3
9
1
9
/Ch
iCC.
2
0
1
7
.
8
0
2
8
3
7
6
.
[1
7
]
C.
Ro
b
les
-
Alg
a
rí
n
,
O.
Ro
d
rí
g
u
e
z
,
a
n
d
A.
Os
p
in
o
,
“
Ev
a
l
u
a
ti
o
n
o
f
n
o
n
-
p
a
ra
m
e
tri
c
id
e
n
ti
fica
ti
o
n
tec
h
n
iq
u
e
s in
se
c
o
n
d
o
rd
e
r
m
o
d
e
ls
p
lu
s
d
e
a
d
ti
m
e
,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
ter
En
g
in
e
e
rin
g
(I
J
ECE
)
,
v
o
l.
1
0
,
n
o
.
6
,
p
p
.
6
3
4
0
-
6
3
4
8
,
2
0
2
0
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
e
c
e
.
v
1
0
i6
.
p
p
6
3
4
0
-
6
3
4
8
.
[1
8
]
S
.
I.
Kh
a
th
e
r
a
n
d
M
.
A.
I
b
ra
h
im,
“
M
o
d
e
li
n
g
a
n
d
sim
u
latio
n
o
f
S
E
P
IC
c
o
n
tr
o
ll
e
d
c
o
n
v
e
rter
u
si
n
g
P
ID
c
o
n
tro
ll
e
r,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
(IJ
PE
DS
)
,
v
o
l.
1
1
,
n
o
.
2
,
p
p
.
8
3
3
-
8
4
3
,
2
0
2
0
,
doi
:
1
0
.
1
1
5
9
1
/
ij
p
e
d
s
.
v
1
1
.
i
2
.
p
p
8
3
3
-
8
4
3
.
[1
9
]
P
.
M
.
M
e
sh
ra
m
a
n
d
R
.
G
.
Ka
n
o
ji
y
a
,
“
Tu
n
i
n
g
o
f
P
ID
c
o
n
tro
ll
e
r
u
si
n
g
Zi
e
g
ler
-
Nic
h
o
ls
m
e
th
o
d
f
o
r
sp
e
e
d
c
o
n
tro
l
o
f
DC
m
o
to
r,
”
in
IE
EE
-
in
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
o
n
a
d
v
a
n
c
e
s
in
e
n
g
in
e
e
rin
g
,
sc
ien
c
e
a
n
d
m
a
n
a
g
e
m
e
n
t
(ICAE
S
M
-
2
0
1
2
)
,
p
p
.
1
1
7
-
1
2
2
,
2
0
1
2
.
[2
0
]
S
.
A.
Bh
a
tt
i,
S
.
A.
M
a
li
k
,
a
n
d
A.
Da
ra
z
,
“
Co
m
p
a
riso
n
o
f
P
-
I
a
n
d
I
-
P
c
o
n
tro
ll
e
r
b
y
u
sin
g
Z
ieg
ler
-
Nic
h
o
ls
tu
n
in
g
m
e
th
o
d
f
o
r
sp
e
e
d
c
o
n
tro
l
o
f
D
C
m
o
to
r,
”
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
telli
g
e
n
t
S
y
ste
ms
En
g
i
n
e
e
rin
g
(ICI
S
E)
2
0
1
6
,
2
0
1
6
,
p
p
.
3
30
-
3
3
4
,
d
o
i:
1
0
.
1
1
0
9
/INTE
LS
E.
2
0
1
6
.
7
4
7
5
1
4
4
.
[2
1
]
M.
Ku
sh
wa
h
a
n
d
A.
P
a
tra,
“
P
ID Co
n
tr
o
ll
e
r
Tu
n
in
g
u
si
n
g
Zi
e
g
ler
-
Nic
h
o
ls M
e
th
o
d
f
o
r
S
p
e
e
d
C
o
n
tr
o
l
o
f
DC M
o
t
o
r,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
S
c
ien
ti
fi
c
En
g
in
e
e
rin
g
a
n
d
T
e
c
h
n
o
lo
g
y
Res
e
a
rc
h
,
v
o
l.
3
,
n
o
.
1
3
,
p
p
.
2
9
2
4
-
2
9
2
9
,
2
0
1
4
.
[2
2
]
W.
N.
A.
-
D.
Ab
e
d
,
A.
H.
S
a
leh
,
a
n
d
A.
S
.
Ha
m
e
e
d
,
“
S
p
e
e
d
C
o
n
tr
o
l
o
f
P
M
DCM
Ba
se
d
G
A
a
n
d
DS
Tec
h
n
i
q
u
e
s,
”
In
ter
n
a
t
io
n
a
l
J
o
u
r
n
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
(IJ
PE
DS
)
,
v
o
l
.
9
,
n
o
.
4
,
p
.
1
4
6
7
,
2
0
1
8
,
d
o
i:
1
0
.
1
1
5
9
1
/i
jp
e
d
s.
v
9
n
4
.
p
p
1
4
6
7
-
1
4
7
5
.
[2
3
]
M
.
M
.
G
a
n
i,
M
.
S
.
Isla
m
,
a
n
d
M
.
A.
Ullah
,
“
Op
ti
m
a
l
P
ID
tu
n
in
g
f
o
r
c
o
n
tr
o
ll
i
n
g
t
h
e
tem
p
e
ra
tu
re
o
f
e
lec
tri
c
fu
rn
a
c
e
b
y
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
”
S
N
A
p
p
li
e
d
S
c
ien
c
e
s
,
v
o
l.
1
,
n
o
.
8
,
p
p
.
1
-
8
,
2
0
1
9
,
d
o
i:
1
0
.
1
0
0
7
/s
4
2
4
5
2
-
0
1
9
-
0
9
2
9
-
y.
[2
4
]
G
.
M
a
n
tri
a
n
d
N.
R.
Ku
l
k
a
rn
i,
“
De
si
g
n
a
n
d
o
p
ti
m
iza
ti
o
n
o
f
P
ID
c
o
n
tro
ll
e
r
u
sin
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Res
e
a
rc
h
in
En
g
i
n
e
e
rin
g
a
n
d
T
e
c
h
n
o
lo
g
y
,
v
o
l.
2
,
n
o
.
6
,
p
p
.
9
2
6
-
9
3
0
,
2
0
1
3
,
d
o
i:
1
0
.
1
5
6
2
3
/IJRE
T.
2
0
1
3
.
0
2
0
6
0
0
2
.
[2
5
]
M
.
S
.
Am
iri
,
M
.
F
.
I
b
ra
h
im,
a
n
d
R.
Ra
m
li
,
“
Op
ti
m
a
l
p
a
ra
m
e
ter es
t
ima
ti
o
n
fo
r
a
DC m
o
t
o
r
u
si
n
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
P
o
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
m
s
(IJ
PE
DS
)
,
v
o
l
.
1
1
,
n
o
.
2
,
p
.
1
0
4
7
,
2
0
2
0
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
p
e
d
s
.
v
1
1
.
i
2
.
p
p
1
0
4
7
-
1
0
5
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Ya
sir
G
h
a
z
i
Ra
shi
d
wa
s
b
o
r
n
in
Am
m
a
a
n
/Jo
rd
a
n
,
1
9
9
1
.
He
wo
rk
s
a
t
Diy
a
la
u
n
i
v
e
rsity
,
c
o
ll
e
g
e
o
f
e
n
g
in
e
e
ri
n
g
,
El
e
c
tro
n
ic
En
g
i
n
e
e
rin
g
De
p
a
rtme
n
t
.
He
re
c
e
iv
e
d
a
BS
.
c
d
e
g
re
e
i
n
e
lec
tri
c
a
l
p
o
we
r
a
n
d
m
a
c
h
in
e
s
fro
m
Diy
a
la
Un
iv
e
rsit
y
in
2
0
1
3
,
M
S
c
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
/
p
o
we
r
a
n
d
m
a
c
h
in
e
s
fro
m
Ba
g
h
d
a
d
Un
iv
e
rsit
y
in
2
0
1
9
.
His
c
u
rre
n
t
re
se
a
rc
h
a
c
ti
v
it
ies
a
re
in
t
h
e
field
s
o
f
re
n
e
wa
b
le
e
n
e
rg
y
,
win
d
p
o
we
r,
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s,
o
p
ti
m
a
l
p
o
we
r
flo
w
,
d
ri
v
e
m
a
c
h
in
e
a
n
d
p
o
we
r
sy
ste
m
o
p
e
ra
ti
o
n
a
n
d
c
o
n
tr
o
l.
Ema
il
:
y
a
ss
e
rg
h
a
z
e
e
_
e
n
g
e
@u
o
d
i
y
a
la.ed
u
.
i
q
Ahm
e
d
Mo
h
a
m
m
e
d
Abd
u
l
H
u
ss
a
in
o
b
tain
e
d
a
b
a
c
h
e
l
o
r'
s
d
e
g
r
e
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fro
m
Ba
g
h
d
a
d
Un
iv
e
rsit
y
in
2
0
1
0
,
M
S
c
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
/p
o
we
r
a
n
d
m
a
c
h
in
e
s
in
2
0
1
9
.
Re
n
e
wa
b
le
re
so
u
rc
e
s,
p
o
we
r
e
lec
tro
n
ics
,
e
lec
tri
c
p
o
we
r,
a
r
ti
ficia
l
in
te
ll
ig
e
n
c
e
,
c
o
n
tro
l
o
f
m
a
c
h
in
e
ry
e
n
g
i
n
e
e
rin
g
m
a
c
h
in
e
ry
,
a
n
d
o
t
h
e
r
field
s
o
f
st
u
d
y
a
re
a
ll
o
f
i
n
tere
st t
o
re
se
a
rc
h
e
rs.
Ema
il
:
a
.
a
lad
e
ly
@c
o
e
n
g
.
u
o
b
a
g
h
d
a
d
.
e
d
u
.
iq
Evaluation Warning : The document was created with Spire.PDF for Python.