I
AE
S In
t
er
na
t
io
na
l J
o
urna
l o
f
Ro
bo
t
ics a
nd
Aut
o
m
a
t
io
n
(
I
J
RA)
Vo
l.
14
,
No
.
1
,
Ma
r
ch
20
25
,
p
p
.
67
~
73
I
SS
N:
2722
-
2
5
8
6
,
DOI
:
1
0
.
1
1
5
9
1
/i
jr
a
.
v
1
4
i
1
.
pp
67
-
73
67
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
r
a
.
ia
esco
r
e.
co
m
Pos
ition
tracking
o
f
DC
m
o
tor
wit
h
P
ID
co
n
troller
ut
ilizing
pa
rticle
swa
rm
o
ptimiza
tion
a
lg
o
ri
thm wi
th
Lév
y
fl
i
g
ht
a
nd
D
o
ppler
e
ff
ec
t
Nur
I
f
f
a
h M
o
ha
m
ed
Azm
i,
Na
f
rizua
n M
a
t
Ya
hy
a
F
a
c
u
l
t
y
o
f
M
a
n
u
f
a
c
t
u
r
i
n
g
a
n
d
M
e
c
h
a
t
r
o
n
i
c
En
g
i
n
e
e
r
i
n
g
T
e
c
h
n
o
l
o
g
y
,
U
n
i
v
e
r
si
t
i
M
a
l
a
y
s
i
a
P
a
h
a
n
g
A
l
-
S
u
l
t
a
n
A
b
d
u
l
l
a
h
,
P
e
k
a
n
,
M
a
l
a
y
s
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ma
y
3
,
2
0
2
4
R
ev
is
ed
Oct
1
1
,
2
0
2
4
Acc
ep
ted
No
v
1
9
,
2
0
2
4
Th
is
p
a
p
e
r
p
re
se
n
ts
t
h
e
imp
lem
e
n
tatio
n
o
f
th
e
p
a
rti
c
le
sw
a
rm
o
p
t
imiz
a
ti
o
n
with
th
e
Lév
y
fli
g
h
t
Do
p
p
ler
e
ffe
c
t
(
PSO
-
LF
DE
)
a
lg
o
rit
h
m
fo
r
o
p
ti
m
izin
g
p
ro
p
o
rti
o
n
a
l
-
i
n
teg
ra
l
-
d
e
riv
a
ti
v
e
(P
ID)
c
o
n
tro
ll
e
r
p
a
ra
m
e
ters
in
a
d
irec
t
c
u
rre
n
t
(DC)
m
o
to
r
s
y
ste
m
.
Trad
i
ti
o
n
a
l
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
s
l
ik
e
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
wh
a
le
o
p
t
imiz
a
ti
o
n
a
l
g
o
ri
th
m
,
g
re
y
w
o
lf
o
p
ti
m
ize
r,
a
n
d
m
o
th
flam
e
o
p
ti
m
iza
ti
o
n
o
ften
fa
c
e
c
h
a
ll
e
n
g
e
s
in
b
a
lan
c
in
g
e
x
p
l
o
r
a
ti
o
n
a
n
d
e
x
p
lo
it
a
ti
o
n
,
lea
d
i
n
g
to
s
u
b
o
p
t
ima
l
p
e
rfo
rm
a
n
c
e
.
Th
e
p
ro
p
o
se
d
P
S
O
-
LF
DE
a
lg
o
rit
h
m
a
d
d
re
ss
e
s
th
e
se
issu
e
s
b
y
in
c
o
r
p
o
ra
t
in
g
Lév
y
fli
g
h
t
fo
r
e
n
h
a
n
c
e
d
e
x
p
lo
ra
ti
o
n
a
n
d
th
e
D
o
p
p
ler
e
ffe
c
t
fo
r
re
fin
e
d
e
x
p
lo
it
a
ti
o
n
.
Th
e
a
l
g
o
rit
h
m
is
v
a
li
d
a
ted
u
sin
g
M
ATLAB/
S
imu
li
n
k
f
o
r
p
o
siti
o
n
c
o
n
tr
o
l
i
n
a
DC
m
o
to
r
sy
ste
m
with
ste
p
in
p
u
ts
o
f
1
0
,
3
0
,
a
n
d
6
0
c
m
.
Ke
y
p
e
rf
o
rm
a
n
c
e
m
e
tri
c
s,
in
c
lu
d
in
g
rise
ti
m
e
,
se
tt
li
n
g
ti
m
e
,
p
e
a
k
ti
m
e
,
a
n
d
ste
a
d
y
-
sta
te
e
rro
r,
we
re
c
o
m
p
a
re
d
a
g
a
i
n
st
o
th
e
r
o
p
ti
m
iz
a
ti
o
n
m
e
th
o
d
s.
P
S
O
-
LF
DE
d
e
m
o
n
stra
ted
su
p
e
rio
r
p
e
rfo
rm
a
n
c
e
,
a
c
h
iev
in
g
a
4
1
.
6
3
%
imp
ro
v
e
m
e
n
t
i
n
rise
t
i
m
e
a
n
d
a
7
0
.
2
0
%
re
d
u
c
ti
o
n
i
n
p
e
a
k
ti
m
e
c
o
m
p
a
re
d
t
o
o
t
h
e
r
m
e
th
o
d
s.
T
h
e
se
re
su
lt
s
h
ig
h
li
g
h
t
P
S
O
-
L
F
DE'
s
e
ffe
c
ti
v
e
n
e
ss
in
o
p
ti
m
izin
g
P
ID
c
o
n
tro
ll
e
r
p
a
ra
m
e
ter
s
a
n
d
imp
r
o
v
i
n
g
th
e
d
y
n
a
m
ic
re
sp
o
n
se
o
f
DC
m
o
to
r
sy
ste
m
s,
o
ffe
rin
g
a
ro
b
u
s
t
so
lu
ti
o
n
fo
r
re
a
l
-
wo
rl
d
c
o
n
tr
o
l
a
p
p
li
c
a
ti
o
n
s.
K
ey
w
o
r
d
s
:
DC
m
o
to
r
Do
p
p
ler
ef
f
ec
t
L
ev
y
f
lig
h
t
Op
tim
izatio
n
Par
ticle
s
war
m
o
p
tim
izatio
n
with
L
év
y
f
lig
h
t D
o
p
p
ler
ef
f
ec
t
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
:
Nu
r
I
f
f
a
h
Mo
h
a
m
ed
Azm
i
Facu
lty
o
f
Ma
n
u
f
ac
tu
r
in
g
an
d
Me
ch
atr
o
n
ic
E
n
g
in
ee
r
in
g
T
ec
h
n
o
lo
g
y
,
Un
iv
e
r
s
iti
Ma
lay
s
ia
Pah
an
g
Al
-
Su
ltan
Ab
d
u
llah
Pek
an
,
Pah
an
g
,
2
6
6
0
0
,
Ma
lay
s
ia
E
m
ail: n
u
r
if
f
a
h
8
7
@
y
ah
o
o
.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Hig
h
-
p
er
f
o
r
m
an
ce
m
o
to
r
d
r
iv
es
ar
e
ex
p
er
ien
cin
g
r
a
p
id
g
r
o
wth
d
u
e
to
th
ei
r
d
iv
er
s
e
a
p
p
li
ca
tio
n
s
in
elec
tr
ic
tr
ain
s
,
r
o
b
o
tics
,
h
o
u
s
eh
o
ld
d
ir
ec
t
cu
r
r
e
n
t
(
DC
)
ap
p
lian
ce
s
,
b
io
m
ed
ical
eq
u
ip
m
en
t,
an
d
v
a
r
io
u
s
in
d
u
s
tr
ial
s
ec
to
r
s
.
DC
m
o
to
r
s
ar
e
f
av
o
r
ed
f
o
r
th
eir
wid
e
s
p
ee
d
r
a
n
g
e,
to
r
q
u
e
ca
p
ac
ities
ex
ce
ed
in
g
4
0
0
%
o
f
th
eir
r
ated
v
alu
e,
s
u
p
er
io
r
s
p
ee
d
r
eg
u
latio
n
,
an
d
co
s
t
-
ef
f
ec
tiv
e
co
n
tr
o
l
s
y
s
tem
s
[
1
]
,
[
2
]
.
On
e
o
f
th
e
wid
ely
u
s
ed
co
n
t
r
o
l
m
et
h
o
d
s
f
o
r
DC
m
o
to
r
s
is
th
e
p
r
o
p
o
r
tio
n
al
-
i
n
teg
r
al
-
d
er
iv
ativ
e
(
PID
)
co
n
tr
o
ller
,
k
n
o
wn
f
o
r
its
s
im
p
le
d
esig
n
an
d
d
ep
en
d
ab
le
p
er
f
o
r
m
an
ce
.
Ho
wev
er
,
PID
co
n
tr
o
ller
s
ar
e
v
u
ln
er
ab
le
to
s
y
s
tem
u
n
p
r
e
d
ictab
ilit
y
,
wh
ich
ca
n
lead
to
s
ig
n
if
ican
t
d
eg
r
ad
atio
n
in
co
n
tr
o
l
p
er
f
o
r
m
a
n
ce
,
n
ec
ess
itatin
g
r
eg
u
lar
f
in
e
-
tu
n
in
g
to
m
ain
tain
o
p
tim
al
f
u
n
ctio
n
ality
[
3
]
–
[
5
]
.
I
n
r
ec
en
t
y
ea
r
s
,
m
etah
eu
r
is
tic
alg
o
r
ith
m
s
lik
e
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
,
g
en
etic
a
lg
o
r
ith
m
s
(
GA)
,
an
d
ad
ap
tiv
e
n
eu
r
o
-
f
u
z
zy
in
f
er
en
ce
s
y
s
tem
s
(
ANFI
S)
h
av
e
g
ain
ed
p
r
o
m
in
e
n
ce
f
o
r
t
h
eir
ef
f
icien
cy
an
d
ef
f
ec
tiv
en
ess
in
s
o
lv
in
g
c
o
m
p
lex
o
p
tim
izatio
n
p
r
o
b
lem
s
[
6
]
,
[
7
]
,
[
8
]
,
[
9
]
.
T
h
e
in
d
u
s
tr
y
h
a
s
s
h
o
wn
s
ig
n
if
ican
t
in
ter
est
in
th
e
im
p
o
r
tan
ce
o
f
m
etah
eu
r
is
tic
PID
tu
n
in
g
alg
o
r
ith
m
s
,
wh
ich
h
a
v
e
d
em
o
n
s
tr
ated
h
ig
h
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
5
8
6
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l
.
14
,
No
.
1
,
Ma
r
ch
20
25
:
67
-
73
68
d
ep
en
d
a
b
ilit
y
o
v
er
t
h
e
last
twen
ty
y
ea
r
s
.
PS
O
is
a
s
im
p
le,
ea
s
ily
im
p
lem
en
tab
le,
an
d
co
m
p
u
tatio
n
ally
ef
f
icien
t
co
n
ce
p
t,
p
r
o
d
u
cin
g
r
eliab
le
r
esu
lts
co
m
p
ar
ed
to
o
th
er
m
eth
o
d
s
[
1
0
]
–
[
1
3
]
.
PS
O
is
a
m
etah
eu
r
is
tic
alg
o
r
ith
m
th
at
m
ain
tai
n
s
a
b
alan
ce
d
eq
u
ilib
r
iu
m
b
etwe
en
e
x
p
lo
r
atio
n
a
n
d
ex
p
lo
itatio
n
p
h
a
s
es,
en
ab
lin
g
it
to
co
n
v
er
g
e
to
war
d
s
p
r
o
m
is
in
g
ar
ea
s
in
th
e
s
ea
r
ch
s
p
ac
e
[
1
4
]
.
PS
O
h
as
m
o
r
e
attr
ac
tiv
e
attr
ib
u
tes
th
an
co
n
v
en
tio
n
al
ev
o
lu
tio
n
ar
y
esti
m
atio
n
m
eth
o
d
s
,
p
r
eser
v
in
g
m
em
o
r
y
,
f
o
s
ter
in
g
co
llab
o
r
ati
o
n
,
an
d
f
ac
ilit
atin
g
k
n
o
wled
g
e
e
x
ch
an
g
e
am
o
n
g
p
ar
ticles
[
1
5
]
.
I
t
ca
n
g
e
n
er
ate
s
u
p
er
io
r
s
o
l
u
tio
n
s
with
in
a
lim
ited
tim
ef
r
am
e
wit
h
a
co
n
cise th
eo
r
etica
l f
o
u
n
d
atio
n
an
d
p
o
s
itiv
e
p
r
o
g
r
am
m
i
n
g
a
p
p
r
o
ac
h
[
1
6
]
.
T
h
e
p
r
o
x
i
m
i
t
y
p
r
i
n
c
i
p
l
e
i
n
PS
O
i
n
v
o
l
v
e
s
p
a
r
t
i
c
le
s
r
es
p
o
n
d
i
n
g
t
o
q
u
a
l
i
t
y
f
a
ct
o
r
s
s
i
m
u
lt
a
n
e
o
u
s
l
y
i
n
b
o
t
h
t
h
e
i
r
i
m
m
e
d
ia
t
e
s
u
r
r
o
u
n
d
i
n
g
s
a
n
d
t
h
e
i
r
o
p
t
i
m
al
p
o
s
i
t
i
o
n
.
T
h
e
s
t
a
b
i
l
it
y
p
r
i
n
c
i
p
l
e
a
l
l
o
w
s
s
wa
r
m
s
t
o
m
o
d
i
f
y
t
h
e
e
n
v
i
r
o
n
m
e
n
t
o
n
l
y
w
h
e
n
i
n
d
i
v
i
d
u
a
l
o
r
c
o
l
l
e
c
t
i
v
e
p
o
s
i
t
i
o
n
s
c
h
a
n
g
e
,
e
n
s
u
r
i
n
g
t
h
e
c
o
n
t
i
n
u
e
d
p
u
r
s
u
i
t
o
f
t
h
e
b
e
s
t
p
o
s
i
t
i
o
n
[
1
7
]
,
[
1
8
]
.
T
h
e
PS
O
a
l
g
o
r
i
t
h
m
s
t
a
n
d
s
o
u
t
d
u
e
t
o
i
ts
f
le
x
i
b
l
e
a
n
d
w
e
ll
-
c
o
o
r
d
i
n
a
t
e
d
m
e
c
h
a
n
is
m
,
e
n
h
a
n
c
i
n
g
g
l
o
b
a
l
a
n
d
l
o
c
a
l e
x
p
l
o
r
a
t
i
o
n
a
b
il
i
ti
e
s
[
1
9
]
–
[
2
1
]
.
O
p
ti
m
i
z
a
ti
o
n
t
h
e
o
r
y
f
o
c
u
s
e
s
o
n
f
i
n
d
i
n
g
t
h
e
b
es
t
w
a
y
s
t
o
s
o
l
v
e
p
r
o
b
l
e
m
s
,
i
n
c
l
u
d
i
n
g
t
e
c
h
n
i
q
u
e
s
,
m
et
h
o
d
s
,
p
r
o
c
e
s
s
e
s
,
a
n
d
a
l
g
o
r
i
t
h
m
s
.
E
n
g
i
n
e
er
s
o
f
t
e
n
d
e
a
l
w
i
t
h
o
p
t
i
m
i
z
a
ti
o
n
p
r
o
b
l
e
m
s
i
n
v
a
r
i
o
u
s
f
i
e
l
d
s
,
s
u
c
h
a
s
m
o
d
e
li
n
g
,
c
h
a
r
a
c
t
e
r
i
z
at
i
o
n
,
a
n
d
m
a
i
n
t
e
n
a
n
ce
[
2
2
]
,
[
2
3
]
.
D
e
s
p
i
t
e
a
d
v
a
n
c
e
m
e
n
t
s
i
n
s
w
a
r
m
i
n
t
el
li
g
e
n
c
e
a
l
g
o
r
i
t
h
m
s
,
ac
h
i
e
v
i
n
g
o
p
t
i
m
a
l
p
e
r
f
o
r
m
a
n
c
e
i
n
a
D
C
m
o
t
o
r
w
i
t
h
a
P
I
D
c
o
n
t
r
o
l
l
e
r
s
y
s
te
m
r
e
q
u
i
r
es
a
b
a
l
a
n
c
e
b
et
w
e
e
n
e
x
p
l
o
r
a
t
i
o
n
an
d
e
x
p
l
o
i
t
a
ti
o
n
p
r
o
c
e
s
s
e
s
.
T
h
is
r
es
e
a
r
c
h
ai
m
s
t
o
e
x
p
l
o
r
e
t
h
e
a
p
p
li
c
a
ti
o
n
o
f
PS
O
i
n
P
I
D
c
o
n
t
r
o
l
l
e
r
t
u
n
i
n
g
f
o
r
D
C
m
o
t
o
r
s
,
d
e
s
p
it
e
i
ts
wi
d
e
s
p
r
e
a
d
u
s
e
.
I
t
a
i
m
s
t
o
p
r
o
v
i
d
e
i
n
s
i
g
h
t
s
i
n
t
o
i
ts
a
d
v
a
n
ta
g
e
s
a
n
d
l
i
m
i
t
a
ti
o
n
s
,
a
d
d
r
e
s
s
i
n
g
t
h
e
l
a
c
k
o
f
c
o
m
p
r
e
h
e
n
s
i
v
e
an
a
l
y
s
is
c
o
n
s
i
d
e
r
i
n
g
d
i
f
f
e
r
e
n
t
m
o
d
e
l
s
,
l
o
a
d
c
o
n
d
it
i
o
n
s
,
a
n
d
p
e
r
f
o
r
m
a
n
c
e
c
r
i
t
e
r
i
a
i
n
p
r
e
v
i
o
u
s
s
t
u
d
i
es
.
T
h
is
s
tu
d
y
p
r
o
p
o
s
es
a
n
ew
m
eth
o
d
ca
lled
p
ar
ticle
s
war
m
o
p
tim
izatio
n
with
L
év
y
f
lig
h
t
an
d
D
o
p
p
ler
ef
f
ec
t
(
PS
O
-
L
FDE)
to
en
h
an
ce
p
o
s
itio
n
co
n
tr
o
l
p
e
r
f
o
r
m
an
ce
in
a
DC
m
o
to
r
s
y
s
tem
wit
h
a
PID
co
n
tr
o
ller
.
T
h
e
p
r
e
s
e
n
t
s
t
u
d
y
f
o
c
u
s
es
o
n
u
t
i
l
i
zi
n
g
t
h
e
P
S
O
-
L
F
D
E
al
g
o
r
it
h
m
t
o
i
m
p
l
e
m
e
n
t
a
D
C
m
o
t
o
r
w
i
t
h
P
I
D
c
o
n
t
r
o
l
le
r
f
o
r
p
o
s
i
t
i
o
n
c
o
n
t
r
o
l
.
T
h
e
o
b
j
e
c
ti
v
e
is
t
o
e
v
a
l
u
a
te
a
n
d
c
o
m
p
a
r
e
t
h
e
p
e
r
f
o
r
m
a
n
c
e
o
f
D
C
m
o
t
o
r
s
t
h
r
o
u
g
h
s
i
m
u
l
a
ti
o
n
a
n
a
l
y
s
is
i
n
M
AT
L
AB
S
i
m
u
l
in
k
.
T
h
e
m
a
t
h
e
m
at
i
c
a
l
m
o
d
e
l
o
f
t
h
e
DC
m
o
t
o
r
is
d
e
r
i
v
e
d
u
s
i
n
g
p
r
i
n
c
i
p
l
e
s
f
r
o
m
p
h
y
s
i
c
s
a
n
d
el
e
c
t
r
o
m
a
g
n
e
ti
s
m
.
T
h
e
P
I
D
c
o
n
t
r
o
l
l
e
r
is
s
p
e
c
i
f
ic
a
l
l
y
e
n
g
i
n
e
e
r
e
d
t
o
a
c
c
u
r
a
t
el
y
t
r
a
c
k
a
n
d
m
a
i
n
t
ai
n
t
h
e
p
o
s
i
t
i
o
n
o
f
t
h
e
D
C
m
o
t
o
r
.
A
n
a
n
a
l
y
s
i
s
is
p
e
r
f
o
r
m
e
d
t
o
a
s
s
e
s
s
t
h
e
e
f
f
e
c
t
i
v
e
n
es
s
o
f
t
h
e
P
I
D
c
o
n
t
r
o
l
l
e
r
i
n
p
r
e
c
i
s
e
l
y
f
o
l
l
o
w
i
n
g
t
h
e
d
e
s
i
r
e
d
p
o
s
i
t
i
o
n
d
u
r
i
n
g
s
t
e
a
d
y
-
s
t
at
e
c
o
n
d
i
t
i
o
n
s
.
T
h
e
s
u
b
s
e
q
u
e
n
t
s
e
c
t
io
n
s
o
f
t
h
e
p
a
p
e
r
a
r
e
o
r
g
a
n
i
z
e
d
a
s
f
o
l
l
o
ws
:
S
e
c
ti
o
n
2
.
1
p
r
o
v
i
d
e
s
a
d
et
a
i
l
e
d
e
x
p
l
a
n
a
t
i
o
n
o
f
t
h
e
m
a
t
h
e
m
a
ti
c
a
l
m
o
d
e
l
o
f
t
h
e
DC
m
o
t
o
r
c
o
u
p
l
e
d
w
i
t
h
t
h
e
P
I
D
c
o
n
t
r
o
ll
er
s
y
s
t
e
m
.
S
e
ct
i
o
n
2
.
2
f
o
c
u
s
es
o
n
t
h
e
d
e
s
i
g
n
o
f
a
PS
O
-
L
F
D
E
al
g
o
r
i
t
h
m
.
S
e
ct
i
o
n
3
e
x
a
m
i
n
e
s
t
h
e
s
i
m
u
la
t
i
o
n
r
es
u
l
ts
o
b
t
a
i
n
e
d
i
n
M
A
T
L
A
B
.
T
h
e
c
o
n
c
l
u
s
i
o
n
s
a
r
e
p
r
e
s
e
n
te
d
i
n
S
e
cti
o
n
4
.
2.
M
E
T
H
O
D
2
.
1
.
M
a
t
hema
t
ica
l
m
o
del o
f
DC
m
o
t
o
r
T
h
e
m
ath
em
atica
l
m
o
d
el
o
f
a
DC
m
o
to
r
is
d
er
iv
ed
b
y
f
o
r
m
u
latin
g
eq
u
atio
n
s
th
at
en
h
an
ce
o
u
r
u
n
d
er
s
tan
d
i
n
g
o
f
its
o
p
e
r
atio
n
.
T
h
e
k
ey
v
ar
iab
les
in
clu
d
e
R
a
,
th
e
a
r
m
atu
r
e
r
esis
tan
ce
;
L
a
,
th
e
ar
m
at
u
r
e
in
d
u
ctan
ce
;
i
a
,
t
h
e
ar
m
atu
r
e
c
u
r
r
en
t;
an
d
v
a
,
t
h
e
in
p
u
t
v
o
ltag
e.
T
h
ese
q
u
an
titi
es
ar
e
m
ea
s
u
r
ed
in
o
h
m
s
(
Ω
)
,
Hen
r
ies
(
H)
,
am
p
er
es
(A)
,
an
d
v
o
lts
(V)
,
r
esp
ec
tiv
ely
.
I
n
th
is
m
o
d
el,
th
e
r
o
to
r
is
tr
ea
ted
as
a
s
in
g
le
co
il
ch
ar
ac
ter
ized
b
y
i
n
d
u
ctan
ce
(L
a
)
an
d
r
esis
tan
ce
(R
a
)
.
A
d
d
itio
n
ally
,
th
e
b
ac
k
elec
tr
o
m
o
tiv
e
f
o
r
ce
(
E
MF)
,
wh
ich
is
th
e
v
o
ltag
e
g
en
er
ated
ac
r
o
s
s
th
e
D
C
m
o
to
r
d
u
r
in
g
o
p
er
atio
n
an
d
is
d
ir
ec
tly
p
r
o
p
o
r
tio
n
al
to
its
s
p
ee
d
,
m
u
s
t
b
e
co
n
s
id
er
ed
.
T
h
e
v
o
lt
ag
e
s
u
p
p
lied
to
th
e
ar
m
at
u
r
e
ca
n
b
e
in
d
ep
e
n
d
en
tly
a
d
ju
s
ted
f
r
o
m
th
e
v
o
ltag
e
s
u
p
p
lied
to
th
e
f
ield
.
T
o
d
er
i
v
e
th
e
co
r
r
esp
o
n
d
in
g
e
q
u
atio
n
f
o
r
th
is
elec
tr
ic
cir
cu
it,
we
f
ir
s
t
ap
p
ly
Kir
ch
h
o
f
f
'
s
v
o
ltag
e
law
(
KVL
)
a
n
d
New
to
n
'
s
s
ec
o
n
d
law
o
f
m
o
tio
n
to
th
e
ar
m
atu
r
e
cir
cu
it
d
iag
r
a
m
,
lead
in
g
to
th
e
d
if
f
er
en
tial e
q
u
atio
n
(
1
)
to
(
3
)
f
o
r
th
e
a
r
m
atu
r
e
cir
c
u
it
.
(
)
=
(
)
+
(
)
+
(
)
(
1
)
(
)
∝
(
)
⇒
(
)
=
=
(
)
(
2
)
(
)
=
2
(
)
2
+
=
(
)
(
3
)
T
h
e
in
d
u
ce
d
v
o
ltag
e
v
b
r
ep
r
esen
ts
th
e
E
MF
an
d
th
e
s
y
m
b
o
l
k
E
r
ep
r
esen
ts
t
h
e
c
o
n
s
tan
t
o
f
e
lectr
o
m
o
tiv
e
f
o
r
ce
.
T
h
e
E
MF
e
q
u
atio
n
m
ay
b
e
d
e
r
iv
ed
b
y
u
s
in
g
Far
ad
ay
'
s
law
o
f
in
d
u
ctio
n
an
d
tak
i
n
g
in
to
a
cc
o
u
n
t
t
h
e
a
n
g
u
lar
v
elo
city
.
T
h
e
v
ar
iab
les
in
th
e
eq
u
atio
n
ar
e
as
f
o
llo
ws:
T(t)
r
ep
r
esen
ts
th
e
m
o
to
r
to
r
q
u
e,
a
n
d
J
r
ep
r
esen
ts
th
e
m
o
m
en
t
o
f
in
er
tia
o
f
th
e
m
o
to
r
s
h
af
t.
T
h
e
to
r
q
u
e
e
q
u
ati
o
n
is
d
er
iv
e
d
f
r
o
m
th
e
m
ec
h
an
ics
o
f
a
m
o
to
r
,
s
p
ec
if
ically
wh
en
an
g
u
lar
v
el
o
city
is
g
iv
en
b
y
ω
(
t)
.
T
h
e
v
is
co
u
s
f
r
ictio
n
al
co
e
f
f
icien
t
an
d
to
r
q
u
e
c
o
n
s
tan
ts
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
P
o
s
itio
n
tr
a
ck
in
g
o
f D
C
mo
to
r
w
ith
P
I
D
co
n
tr
o
ller
u
tili
z
in
g
p
a
r
ticle
s
w
a
r
m
…
(
N
u
r
I
ffa
h
Mo
h
a
med
A
z
mi
)
69
th
e
m
o
to
r
a
r
e
d
en
o
ted
b
y
th
e
co
r
r
esp
o
n
d
en
ce
b
an
d
k
T
,
r
e
s
p
ec
tiv
ely
.
B
y
u
s
in
g
th
e
L
ap
l
ac
e
tr
an
s
f
o
r
m
a
n
d
ass
u
m
in
g
ze
r
o
s
tar
tin
g
c
o
n
d
iti
o
n
s
f
o
r
(1
E
rr
o
r!
Ref
er
ence
s
o
urce
no
t
f
o
un
d.
)
to
(
3
)
,
we
g
et
(
4
)
to
(
6
)
.
(
)
=
(
)
+
(
)
+
(
)
(
4
)
(
)
=
(
)
(
5
)
(
)
=
(
)
+
(
)
=
(
)
(
6
)
R
ep
lacin
g
th
e
eq
u
atio
n
r
ep
r
esen
ted
b
y
(
5
)
in
(
4
)
an
d
s
im
p
lif
y
in
g
(
4
)
an
d
(
6
)
y
ield
s
(
7
)
an
d
(
8
)
.
(
)
=
(
)
−
(
)
+
=
(
)
−
(
)
(
+
)
(
7
)
(
)
=
1
+
(
)
=
+
(
)
(
8
)
2
.
2
.
Dev
el
o
pm
ent
o
f
P
SO
-
L
F
DE
a
lg
o
rit
hm
T
h
e
PS
O
-
L
FDE
alg
o
r
ith
m
is
an
ad
v
an
ce
d
v
ar
iatio
n
o
f
t
h
e
PSO
m
eth
o
d
,
in
c
o
r
p
o
r
atin
g
elem
en
ts
f
r
o
m
L
év
y
f
lig
h
t
(
L
F)
a
n
d
D
o
p
p
ler
ef
f
ec
t
(
DE
)
th
eo
r
ies
to
im
p
r
o
v
e
p
er
f
o
r
m
a
n
ce
.
T
h
e
L
F
co
n
ce
p
t
en
h
an
ce
s
th
e
r
an
d
o
m
walk
b
eh
av
i
o
r
d
u
r
i
n
g
p
o
s
itio
n
u
p
d
ates,
in
cr
ea
s
in
g
th
e
ex
p
lo
r
atio
n
ca
p
ab
i
liti
es
o
f
p
ar
ticles.
Me
an
wh
ile,
th
e
DE
th
eo
r
y
r
e
p
lace
s
th
e
in
er
tia
weig
h
t,
wh
ic
h
tr
ad
itio
n
ally
m
a
n
ag
es
th
e
in
f
lu
en
ce
o
f
p
r
e
v
io
u
s
v
elo
cities
o
n
cu
r
r
e
n
t
o
n
es,
t
o
o
p
tim
ize
th
e
f
itn
ess
f
u
n
ctio
n
s
o
f
th
e
p
er
s
o
n
al
b
est
(
p
b
e
s
t
)
an
d
g
lo
b
al
b
est
(
g
b
est
)
p
o
s
itio
n
s
.
T
h
is
h
y
b
r
id
ap
p
r
o
ac
h
aim
s
to
ac
h
iev
e
s
u
p
er
io
r
o
p
tim
izatio
n
r
esu
lts
[
2
4
]
.
T
h
e
p
er
f
o
r
m
an
ce
ev
alu
atio
n
f
u
n
ctio
n
b
y
Yah
y
a
an
d
Yu
s
o
f
f
[
2
5
]
,
p
r
o
v
id
ed
in
(
9
)
,
is
u
tili
ze
d
as
an
o
b
jectiv
e
f
u
n
ctio
n
in
co
n
ju
n
ctio
n
with
v
ar
io
u
s
o
p
ti
m
izatio
n
alg
o
r
ith
m
s
to
o
p
tim
ally
ad
ju
s
t
th
e
PID
co
n
tr
o
lle
r
p
ar
am
eter
s
.
T
h
is
f
u
n
ctio
n
,
alo
n
g
s
id
e
t
h
e
PS
O,
wh
ale
o
p
tim
izatio
n
alg
o
r
ith
m
(
W
OA
)
,
g
r
ey
wo
lf
o
p
tim
izer
(
GW
O
)
,
an
d
m
o
t
h
f
lam
e
o
p
tim
izatio
n
(
MFO
)
alg
o
r
ith
m
s
,
aid
s
in
ac
h
iev
in
g
o
p
tim
al
tu
n
in
g
b
y
m
i
n
im
izin
g
s
ettlin
g
tim
e,
r
is
in
g
tim
e,
o
v
er
s
h
o
o
t,
a
n
d
s
tead
y
-
s
tate
er
r
o
r
,
e
n
s
u
r
in
g
s
u
p
er
i
o
r
p
er
f
o
r
m
an
ce
o
f
th
e
DC
m
o
to
r
with
th
e
PID
co
n
tr
o
ller
s
y
s
tem
.
(
)
=
(
1
−
−
)
(
+
)
+
−
(
−
)
(
9
)
Alg
o
r
ith
m
1
.
Par
ticle
s
war
m
o
p
tim
izatio
n
with
L
év
y
f
lig
h
t a
n
d
th
e
Do
p
p
ler
e
f
f
ec
t
B
e
g
i
n
f
o
r
e
a
c
h
p
a
r
t
i
c
l
e
i
n
t
h
e
sw
a
r
m
I
n
i
t
i
a
l
i
z
e
i
t
s
p
o
s
i
t
i
o
n
a
n
d
v
e
l
o
c
i
t
y
r
a
n
d
o
ml
y
e
n
d
f
o
r
w
h
i
l
e
i
t
e
r
<
ma
x
_
i
t
e
r
do
f
o
r
e
a
c
h
p
a
r
t
i
c
l
e
,
j
do
U
p
d
a
t
e
v
e
l
o
c
i
t
y
w
i
t
h
t
h
e
D
o
p
p
l
e
r
Ef
f
e
c
t
e
q
u
a
t
i
o
n
r
e
p
l
a
c
e
s
t
h
e
i
n
e
r
t
i
a
w
e
i
g
h
t
e
q
u
a
t
i
o
n
.
C
h
e
c
k
t
h
e
v
e
l
o
c
i
t
y
b
o
u
n
d
a
r
i
e
s
U
p
d
a
t
e
p
o
s
i
t
i
o
n
w
i
t
h
L
é
v
y
f
l
i
g
h
t
e
q
u
a
t
i
o
n
C
a
l
c
u
l
a
t
e
f
i
t
n
e
s
s
v
a
l
u
e
i
f
Th
e
f
i
t
n
e
ss
v
a
l
u
e
i
s
b
e
t
t
e
r
t
h
a
n
t
h
e
b
e
s
t
f
i
t
n
e
ss
v
a
l
u
e
.
p
b
e
s
t
i
n
t
h
e
p
a
s
t
s
e
t
t
h
e
c
u
r
r
e
n
t
v
a
l
u
e
a
s
t
h
e
n
e
w
p
b
e
st
.
e
n
d
i
f
e
n
d
f
o
r
F
r
o
m a
l
l
t
h
e
p
a
r
t
i
c
l
e
s
o
r
n
e
i
g
h
b
o
r
h
o
o
d
,
c
h
o
o
se
t
h
e
p
a
r
t
i
c
l
e
w
i
t
h
t
h
e
b
e
st
f
i
t
n
e
ss
v
a
l
u
e
a
s
t
h
e
g
b
e
st
e
n
d
w
h
i
l
e
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
s
y
s
tem
s
tr
u
ctu
r
e
is
d
ev
elo
p
ed
b
y
i
n
teg
r
atin
g
p
r
ev
i
o
u
s
r
e
s
ea
r
ch
to
cr
ea
te
a
DC
m
o
to
r
with
a
PID
co
n
tr
o
ller
s
y
s
tem
,
u
tili
zin
g
t
h
e
PS
O
-
L
FDE
alg
o
r
ith
m
.
T
h
is
p
r
o
p
o
s
ed
al
g
o
r
ith
m
o
p
tim
izes
th
e
co
n
tr
o
l
p
a
r
a
m
e
te
r
s
o
f
th
e
DC
m
o
to
r
w
ith
a
P
I
D
c
o
n
tr
o
l
le
r
,
a
n
d
its
p
e
r
f
o
r
m
a
n
ce
is
v
al
id
ate
d
u
s
i
n
g
MA
T
L
AB
/Si
m
u
li
n
k
.
T
h
e
p
o
s
itio
n
co
n
tr
o
l
p
e
r
f
o
r
m
an
ce
o
f
th
e
s
y
s
tem
is
th
o
r
o
u
g
h
ly
ev
alu
ated
,
d
em
o
n
s
tr
atin
g
th
e
PS
O
-
L
FDE
alg
o
r
ith
m
'
s
ef
f
ec
tiv
en
ess
an
d
p
r
ec
is
io
n
.
A
th
r
ee
-
s
tep
in
p
u
t
c
o
m
m
an
d
co
n
s
is
tin
g
o
f
1
0
,
3
0
,
an
d
6
0
ce
n
tim
eter
s
will
b
e
u
tili
ze
d
to
an
aly
ze
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
'
s
p
er
f
o
r
m
an
ce
o
n
th
e
DC
m
o
to
r
co
n
tr
o
lled
b
y
th
e
PID
co
n
tr
o
ller
s
y
s
tem
.
T
h
e
s
p
ec
if
icatio
n
s
an
d
v
alu
es
o
f
th
e
DC
m
o
to
r
,
as
p
r
esen
ted
in
T
a
b
le
1
.
Fig
u
r
e
1
d
ep
icts
(
)
(
)
k
k
k
k
g
j
g
j
g
j
g
j
g
j
g
j
s
g
b
e
s
t
r
c
s
p
b
e
s
t
r
c
d
e
v
v
,
.
2
2
,
.
1
1
,
,
1
−
−
−
+
=
+
1
1
,
,
,
+
+
+
=
k
k
k
g
j
g
j
g
j
v
x
x
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
5
8
6
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l
.
14
,
No
.
1
,
Ma
r
ch
20
25
:
67
-
73
70
th
e
DC
m
o
to
r
with
a
PID
co
n
tr
o
ller
s
y
s
tem
f
o
r
p
o
s
itio
n
c
o
n
tr
o
l
u
tili
zin
g
t
h
e
PS
O
-
L
FDE
alg
o
r
ith
m
i
n
th
e
Simu
lin
k
b
lo
ck
d
iag
r
am
.
T
ab
le
1
.
DC
m
o
to
r
p
ar
am
eter
s
v
alu
es
P
a
r
a
me
t
e
r
s
D
e
scri
p
t
i
o
n
U
n
i
t
s
V
a
l
u
e
s
R
a
M
o
t
o
r
r
e
si
s
t
a
n
c
e
(
)
1
.
5
1
L
a
M
o
t
o
r
e
l
e
c
t
r
i
c
i
n
d
u
c
t
a
n
c
e
(
)
0
.
5
5
J
B
o
d
y
i
n
e
r
t
i
a
(
2
)
1
.
1
−
6
b
V
i
sco
u
s
f
r
i
c
t
i
o
n
a
l
c
o
e
f
f
i
c
i
e
n
t
5
.
06
−
6
k
T
To
r
q
u
e
c
o
n
st
a
n
t
s
o
f
t
h
e
mo
t
o
r
−
1
0
.
0
2
7
k
E
C
o
n
st
a
n
t
o
f
e
l
e
c
t
r
o
m
o
t
i
v
e
f
o
r
c
e
−
1
0
.
0
2
7
Fig
u
r
e
1
.
Simu
lin
k
m
o
d
el
o
f
DC
m
o
to
r
with
PID
co
n
tr
o
ller
s
y
s
tem
f
o
r
p
o
s
itio
n
c
o
n
tr
o
l
T
h
e
p
er
f
o
r
m
a
n
ce
e
v
alu
atio
n
r
esu
lts
co
llected
f
o
r
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
s
a
r
e
co
m
p
ar
e
d
with
th
o
s
e
o
f
o
th
e
r
f
u
n
d
am
en
tal
o
p
ti
m
izatio
n
alg
o
r
ith
m
s
.
T
h
e
ev
alu
atio
n
f
o
cu
s
ed
o
n
f
o
u
r
k
ey
tim
e
-
d
o
m
ain
s
p
ec
if
icatio
n
s
:
s
ettlin
g
tim
e,
r
is
e
tim
e,
o
v
er
s
h
o
o
t,
an
d
s
tead
y
-
s
tate
er
r
o
r
.
T
h
e
p
er
f
o
r
m
an
ce
ev
alu
atio
n
is
g
r
ap
h
ically
d
ep
icted
in
Fig
u
r
e
2
f
o
r
all
s
et
p
o
in
ts
with
th
e
n
u
m
er
ical
r
esu
lts
p
r
esen
ted
in
T
a
b
le
2
.
T
ab
le
2
.
Op
tim
u
m
v
alu
es o
b
ta
in
ed
b
y
PS
O
-
L
FDE
with
f
o
u
r
d
if
f
er
en
t m
et
h
o
d
s
at
s
tep
in
p
u
t
s
10
cm
,
3
0
cm
,
an
d
6
0
cm
10
c
m
30c
m
60c
m
B
e
s
t
M
e
a
n
W
or
s
t
σ
B
e
s
t
M
e
a
n
W
or
s
t
σ
B
e
s
t
M
e
a
n
W
or
s
t
σ
PSO
-
L
F
DE
0.
2224
0.
2381
0.
2604
0.
0101
0.
2119
0.
2309
0.
2616
0.
0132
0.
2002
0.
2097
0.
2505
0.
014062
PSO
0.
3148
0.
3172
0.
3194
0.
0021
0.
2879
0.
2898
0.
2919
0.
0019
0.
2553
0.
2567
0.
2581
0.
001453
W
OA
1.
2622
3.
3372
7.
5143
1.
7487
1.
1794
3.
0917
5.
9886
1.
5697
0.
4325
2.
7734
8.
7769
1.
771845
G
W
O
0.
2882
0.
3032
0.
3184
0.
0134
0.
2881
0.
3031
0.
3192
0.
0140
0.
2553
0.
2606
0.
3630
0.
019774
M
F
O
0.
3156
0.
3167
0.
3168
0.
0004
0.
2879
0.
2879
0.
2880
1.
09
e
-
05
0.
2553
0.
2563
0.
2653
0.
003039
T
h
e
an
aly
s
is
o
f
th
e
PS
O
-
L
FDE
alg
o
r
ith
m
s
h
o
wed
s
ig
n
if
ican
t im
p
r
o
v
em
e
n
ts
in
k
ey
m
etr
ics:
−
R
is
e
tim
e:
f
o
r
a
1
0
cm
s
tep
in
p
u
t,
PS
O
-
L
FDE
ac
h
iev
ed
a
r
is
e
tim
e
o
f
0
.
1
7
3
3
s
ec
o
n
d
s
,
o
u
tp
er
f
o
r
m
in
g
th
e
MFO
m
eth
o
d
b
y
4
1
.
6
3
%.
I
n
co
m
p
ar
is
o
n
,
PS
O,
W
OA,
an
d
GW
O
m
eth
o
d
s
h
ad
r
is
en
tim
es
o
f
0
.
2
9
4
1
,
0
.
1
8
5
7
,
an
d
0
.
2
9
5
1
s
ec
o
n
d
s
,
r
esp
ec
tiv
ely
.
−
Settli
n
g
tim
e
:
PS
O
-
L
FDE
ac
h
iev
ed
a
s
ettlin
g
tim
e
o
f
0
.
2
6
4
4
s
ec
o
n
d
s
,
f
ar
o
u
tp
er
f
o
r
m
i
n
g
PS
O,
wh
ich
r
eq
u
ir
ed
2
.
0
0
0
s
ec
o
n
d
s
.
W
OA
an
d
GW
O
ac
h
iev
ed
s
ettli
n
g
tim
es
o
f
0
.
3
1
8
9
an
d
2
.
0
0
0
0
s
ec
o
n
d
s
,
r
esp
ec
tiv
ely
.
−
Peak
tim
e
:
T
h
e
PS
O
-
L
FDE
alg
o
r
ith
m
r
ec
o
r
d
ed
a
p
ea
k
tim
e
o
f
0
.
3
3
0
4
s
ec
o
n
d
s
,
7
0
.
2
0
%
f
a
s
ter
th
an
PS
O
(
1
.
1
0
8
9
s
ec
o
n
d
s
)
.
W
OA,
GW
O,
an
d
MFO
r
ec
o
r
d
ed
p
ea
k
ti
m
es
o
f
0
.
8
8
6
0
,
1
.
1
1
2
7
,
an
d
1
.
1
2
8
7
s
ec
o
n
d
s
,
r
esp
ec
tiv
ely
.
T
h
ese
f
in
d
in
g
s
d
e
m
o
n
s
tr
ate
t
h
at
th
e
PS
O
-
L
FDE
alg
o
r
ith
m
s
ig
n
if
ican
tly
en
h
a
n
ce
s
th
e
d
y
n
am
ic
r
esp
o
n
s
e
o
f
th
e
DC
m
o
to
r
with
th
e
PID
c
o
n
tr
o
ller
s
y
s
tem
,
p
a
r
ticu
lar
ly
in
o
p
tim
izin
g
r
is
e
tim
e,
s
ettli
n
g
tim
e,
an
d
p
ea
k
tim
e.
T
h
e
s
tu
d
y
u
n
d
er
s
co
r
e
s
th
e
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
o
f
PS
O
-
L
FDE
in
r
ea
l
-
wo
r
ld
co
n
tr
o
l
s
y
s
tem
ap
p
licatio
n
s
,
s
u
r
p
ass
in
g
tr
ad
it
io
n
al
o
p
tim
izatio
n
tec
h
n
iq
u
es
.
T
h
is
wo
r
k
h
ig
h
lig
h
ts
th
e
n
o
v
elty
an
d
p
r
ac
tical
v
alu
e
o
f
PS
O
-
L
FDE
as a
r
o
b
u
s
t so
lu
tio
n
f
o
r
o
p
tim
izin
g
PID
co
n
tr
o
ller
s
in
DC
m
o
to
r
s
y
s
tem
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
P
o
s
itio
n
tr
a
ck
in
g
o
f D
C
mo
to
r
w
ith
P
I
D
co
n
tr
o
ller
u
tili
z
in
g
p
a
r
ticle
s
w
a
r
m
…
(
N
u
r
I
ffa
h
Mo
h
a
med
A
z
mi
)
71
Fig
u
r
e
2
.
Step
r
esp
o
n
s
e
f
o
r
p
o
s
itio
n
co
n
tr
o
l p
e
r
f
o
r
m
an
ce
o
f
a
DC
m
o
to
r
with
PID
co
n
tr
o
ller
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
5
8
6
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l
.
14
,
No
.
1
,
Ma
r
ch
20
25
:
67
-
73
72
4.
C
O
NCLU
SI
O
N
T
h
is
s
tu
d
y
s
u
cc
ess
f
u
lly
im
p
le
m
en
ted
th
e
PS
O
-
L
FDE
alg
o
r
i
th
m
to
o
p
tim
ize
th
e
c
o
n
tr
o
l
p
ar
am
eter
s
o
f
a
DC
m
o
to
r
with
a
PID
co
n
tr
o
ller
s
y
s
tem
.
T
h
r
o
u
g
h
ex
te
n
s
iv
e
s
im
u
latio
n
s
u
s
in
g
MA
T
L
AB
/Si
m
u
lin
k
,
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
p
r
o
p
o
s
ed
PS
O
-
L
FDE
alg
o
r
ith
m
i
s
th
o
r
o
u
g
h
ly
e
v
alu
ated
an
d
co
m
p
ar
ed
ag
ai
n
s
t
o
th
er
estab
lis
h
ed
o
p
tim
izatio
n
m
eth
o
d
s
,
in
clu
d
i
n
g
PS
O,
W
OA,
GW
O,
an
d
MFO
.
T
h
e
r
esu
lts
d
em
o
n
s
tr
ated
th
a
t
PSO
-
L
FDE
s
ig
n
if
ican
tly
o
u
tp
er
f
o
r
m
s
th
e
co
m
p
etin
g
alg
o
r
i
th
m
s
in
ter
m
s
o
f
k
ey
tim
e
-
d
o
m
ain
p
er
f
o
r
m
an
ce
m
etr
ics
s
u
ch
as
r
is
e
t
im
e,
s
et
tlin
g
tim
e,
an
d
p
ea
k
tim
e.
Sp
ec
if
ically
,
PS
O
-
L
FDE
ex
h
ib
it
ed
f
aster
r
esp
o
n
s
e
tim
es
an
d
s
u
p
er
io
r
s
tab
ilit
y
,
i
n
d
icatin
g
its
ef
f
ec
tiv
en
ess
in
o
p
tim
izin
g
th
e
d
y
n
am
ic
b
eh
av
io
r
o
f
th
e
DC
m
o
to
r
with
PID
co
n
tr
o
ller
.
T
h
e
f
in
d
in
g
s
v
alid
ate
th
e
PS
O
-
L
FDE
alg
o
r
ith
m
as
a
r
o
b
u
s
t
an
d
ef
f
icien
t
o
p
tim
izatio
n
tech
n
iq
u
e,
ca
p
ab
le
o
f
ac
h
ie
v
in
g
im
p
r
o
v
e
d
co
n
tr
o
l
p
e
r
f
o
r
m
an
ce
i
n
r
ea
l
-
wo
r
ld
ap
p
licatio
n
s
.
T
h
e
s
tu
d
y
h
ig
h
lig
h
ts
th
e
alg
o
r
ith
m
'
s
ab
il
ity
to
b
alan
ce
ex
p
l
o
r
atio
n
a
n
d
ex
p
lo
itatio
n
in
s
ea
r
ch
s
p
ac
e,
av
o
id
in
g
p
r
em
atu
r
e
co
n
v
er
g
en
ce
an
d
en
s
u
r
in
g
g
lo
b
al
o
p
tim
izatio
n
.
C
o
n
s
eq
u
e
n
tly
,
th
e
PS
O
-
L
FDE
alg
o
r
ith
m
r
ep
r
esen
ts
a
v
alu
ab
le
ad
v
an
ce
m
e
n
t
in
o
p
tim
izin
g
P
I
D
co
n
tr
o
ller
s
f
o
r
DC
m
o
to
r
s
y
s
tem
s
an
d
h
o
ld
s
g
r
ea
t
p
o
t
en
tial
f
o
r
b
r
o
a
d
er
ap
p
licatio
n
s
in
co
n
t
r
o
l sy
s
tem
s
en
g
in
ee
r
in
g
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
ex
p
r
ess
th
eir
g
r
a
titu
d
e
to
t
h
e
Min
is
tr
y
o
f
Hig
h
er
E
d
u
ca
tio
n
f
o
r
th
e
f
in
an
ci
al
s
u
p
p
o
r
t
r
ec
eiv
ed
th
r
o
u
g
h
th
e
UM
PS
A
I
n
ter
n
al
Gr
an
t
(
U
n
iv
er
s
ity
R
ef
er
en
ce
R
DU2
4
0
3
0
9
)
a
n
d
to
Un
iv
er
s
iti
Ma
lay
s
ia
Pah
an
g
Al
-
Su
ltan
Ab
d
u
llah
f
o
r
p
r
o
v
id
in
g
la
b
f
ac
ilit
ies.
RE
F
E
R
E
NC
E
S
[
1
]
D
.
B
a
r
k
a
s,
G
.
C
.
I
o
a
n
n
i
d
i
s
,
C
.
P
s
o
mo
p
o
u
l
o
s,
S
.
D
.
K
a
m
i
n
a
r
i
s
,
a
n
d
G
.
V
o
k
a
s,
“
B
r
u
s
h
e
d
D
C
m
o
t
o
r
d
r
i
v
e
s
f
o
r
i
n
d
u
st
r
i
a
l
a
n
d
a
u
t
o
m
o
b
i
l
e
a
p
p
l
i
c
a
t
i
o
n
s
w
i
t
h
e
mp
h
a
s
i
s
o
n
c
o
n
t
r
o
l
t
e
c
h
n
i
q
u
e
s:
A
c
o
mp
r
e
h
e
n
s
i
v
e
r
e
v
i
e
w
,
”
El
e
c
t
ro
n
i
c
s
,
v
o
l
.
9
,
p
.
8
8
7
,
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
e
l
e
c
t
r
o
n
i
c
s
9
0
6
0
8
8
7
.
[
2
]
S
.
P
.
S
i
mo
n
,
L.
D
e
w
a
n
,
a
n
d
M
.
P
.
R
.
P
r
a
sad
,
“
D
e
si
g
n
a
n
d
a
n
a
l
y
s
i
s
o
f
I
TA
E
t
u
n
e
d
r
o
b
u
s
t
P
I
D
c
o
n
t
r
o
l
l
e
r
f
o
r
b
r
u
sh
e
d
D
C
m
o
t
o
r
,
”
i
n
2
0
2
2
I
EE
E
S
i
l
c
h
a
r
S
u
b
se
c
t
i
o
n
C
o
n
f
e
r
e
n
c
e
,
S
I
L
C
O
N
2
0
2
2
,
2
0
2
2
,
p
p
.
1
–
6
.
d
o
i
:
1
0
.
1
1
0
9
/
S
I
LC
O
N
5
5
2
4
2
.
2
0
2
2
.
1
0
0
2
8
9
3
8
.
[
3
]
S
.
P
a
n
d
e
y
,
“
O
p
t
i
mi
z
a
t
i
o
n
o
f
P
I
D
c
o
n
t
r
o
l
l
e
r
p
a
r
a
m
e
t
e
r
s
f
o
r
s
p
e
e
d
c
o
n
t
r
o
l
o
f
D
C
m
o
t
o
r
u
si
n
g
f
i
r
e
f
l
y
a
n
d
f
m
i
n
s
e
a
r
c
h
a
l
g
o
r
i
t
h
ms
,
”
S
S
RN
El
e
c
t
ro
n
i
c
J
o
u
r
n
a
l
,
p
p
.
1
–
9
,
2
0
2
3
,
d
o
i
:
1
0
.
2
1
3
9
/
s
sr
n
.
4
3
7
8
7
8
4
.
[
4
]
Z.
Q
i
,
Q
.
S
h
i
,
a
n
d
H
.
Z
h
a
n
g
,
“
T
u
n
i
n
g
o
f
d
i
g
i
t
a
l
P
I
D
c
o
n
t
r
o
l
l
e
r
s u
s
i
n
g
p
a
r
t
i
c
l
e
sw
a
r
m o
p
t
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m f
o
r
a
C
A
N
-
B
a
se
d
D
C
mo
t
o
r
s
u
b
j
e
c
t
t
o
st
o
c
h
a
s
t
i
c
d
e
l
a
y
s
,
”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
I
n
d
u
s
t
ri
a
l
E
l
e
c
t
ro
n
i
c
s
,
v
o
l
.
6
7
,
n
o
.
7
,
p
p
.
5
6
3
7
–
5
6
4
6
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
TI
E.
2
0
1
9
.
2
9
3
4
0
3
0
.
[
5
]
A
.
A
b
d
u
l
a
me
e
r
,
M
.
S
u
l
a
i
m
a
n
,
M
.
S
.
M
.
A
r
a
s,
a
n
d
D
.
S
a
l
e
e
m
,
“
T
u
n
i
n
g
m
e
t
h
o
d
s
o
f
P
I
D
c
o
n
t
r
o
l
l
e
r
f
o
r
D
C
m
o
t
o
r
sp
e
e
d
c
o
n
t
r
o
l
,
”
I
n
d
o
n
e
si
a
n
J
o
u
r
n
a
l
o
f
E
l
e
c
t
r
i
c
a
l
En
g
i
n
e
e
r
i
n
g
a
n
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
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
j
e
e
c
s.
v
3
.
i
2
.
p
p
3
4
3
-
3
4
9
.
[
6
]
L.
F
.
F
r
a
g
a
-
G
o
n
z
a
l
e
z
,
R
.
Q
.
F
u
e
n
t
e
s
-
A
g
u
i
l
a
r
,
A
.
G
a
r
c
i
a
-
G
o
n
z
a
l
e
z
,
a
n
d
G
.
S
a
n
c
h
e
z
-
A
n
t
e
,
“
A
d
a
p
t
i
v
e
si
mu
l
a
t
e
d
a
n
n
e
a
l
i
n
g
f
o
r
t
u
n
i
n
g
P
I
D
c
o
n
t
r
o
l
l
e
r
s,”
AI
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
3
0
,
p
p
.
3
4
7
–
3
6
2
,
2
0
1
7
,
d
o
i
:
1
0
.
3
2
3
3
/
A
I
C
-
1
7
0
7
4
1
.
[
7
]
S
.
B
.
J
o
se
p
h
,
E
.
G
.
D
a
d
a
,
A
.
A
b
i
d
e
mi
,
D
.
O
.
O
y
e
w
o
l
a
,
a
n
d
B
.
M
.
K
h
a
mm
a
s,
“
M
e
t
a
h
e
u
r
i
st
i
c
a
l
g
o
r
i
t
h
ms
f
o
r
P
I
D
c
o
n
t
r
o
l
l
e
r
p
a
r
a
m
e
t
e
r
s
t
u
n
i
n
g
:
R
e
v
i
e
w
,
a
p
p
r
o
a
c
h
e
s
a
n
d
o
p
e
n
p
r
o
b
l
e
ms,
”
H
e
l
i
y
o
n
,
v
o
l
.
8
,
n
o
.
5
,
p
.
e
0
9
3
9
9
,
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
h
e
l
i
y
o
n
.
2
0
2
2
.
e
0
9
3
9
9
.
[
8
]
B
.
A
l
l
a
o
u
a
,
B
.
G
a
s
b
a
o
u
i
,
a
n
d
B
.
M
e
b
a
r
k
i
,
“
S
e
t
t
i
n
g
u
p
P
I
D
D
C
mo
t
o
r
sp
e
e
d
c
o
n
t
r
o
l
a
l
t
e
r
a
t
i
o
n
p
a
r
a
m
e
t
e
r
s
u
s
i
n
g
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
s
t
r
a
t
e
g
y
,
”
L
e
o
n
a
r
d
o
J
o
u
r
n
a
l
o
f
Pr
a
c
t
i
c
e
s
a
n
d
T
e
c
h
n
o
l
o
g
i
e
s
,
n
o
.
1
4
,
p
p
.
1
9
–
3
2
,
2
0
0
9
,
d
o
i
:
1
0
.
2
1
7
4
/
9
7
8
1
6
0
8
0
5
1
2
6
7
1
1
2
0
1
0
1
0
0
0
3
.
[
9
]
W
.
M
.
El
sr
o
g
y
,
M
.
A
.
F
k
i
r
i
n
,
a
n
d
M
.
A
.
M
.
H
a
ss
a
n
,
“
S
p
e
e
d
c
o
n
t
r
o
l
o
f
D
C
m
o
t
o
r
u
s
i
n
g
P
I
D
c
o
n
t
r
o
l
l
e
r
b
a
se
d
o
n
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
t
e
c
h
n
i
q
u
e
s
,
”
i
n
2
0
1
3
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
n
t
r
o
l
,
D
e
c
i
s
i
o
n
a
n
d
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
i
e
s
(
C
o
D
I
T
)
,
H
a
m
m
a
m
e
t
,
T
u
n
i
s
i
a
,
2
0
1
3
,
p
p
.
1
9
6
–
2
0
1
.
d
o
i
:
1
0
.
1
1
0
9
/
C
o
D
I
T.
2
0
1
3
.
6
6
8
9
5
4
3
.
[
1
0
]
E.
S
.
R
a
h
a
y
u
,
A
.
M
a
’
a
r
i
f
,
a
n
d
A
.
C
a
k
a
n
,
“
P
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
(
P
S
O
)
t
u
n
i
n
g
o
f
P
I
D
c
o
n
t
r
o
l
o
n
D
C
m
o
t
o
r
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
Ro
b
o
t
i
c
s
a
n
d
C
o
n
t
r
o
l
S
y
st
e
m
s
,
v
o
l
.
2
,
n
o
.
2
,
p
p
.
4
3
5
–
4
4
7
,
2
0
2
2
,
d
o
i
:
1
0
.
3
1
7
6
3
/
i
j
r
c
s
.
v
2
i
2
.
4
7
6
.
[
1
1
]
H
.
F
e
n
g
,
W
.
M
a
,
C
.
Y
i
n
,
a
n
d
D
.
C
a
o
,
“
Tr
a
j
e
c
t
o
r
y
c
o
n
t
r
o
l
o
f
e
l
e
c
t
r
o
-
h
y
d
r
a
u
l
i
c
p
o
si
t
i
o
n
s
e
r
v
o
sy
s
t
e
m
u
si
n
g
i
m
p
r
o
v
e
d
P
S
O
-
P
I
D
c
o
n
t
r
o
l
l
e
r
,
”
A
u
t
o
m
a
t
i
o
n
i
n
C
o
n
s
t
r
u
c
t
i
o
n
,
v
o
l
.
1
2
7
,
p
.
1
0
3
7
2
2
,
2
0
2
1
,
d
o
i
:
h
t
t
p
s:
/
/
d
o
i
.
o
r
g
/
1
0
.
1
0
1
6
/
j
.
a
u
t
c
o
n
.
2
0
2
1
.
1
0
3
7
2
2
.
[
1
2
]
A
.
K
.
K
a
sh
y
a
p
a
n
d
D
.
R
.
P
a
r
h
i
,
“
P
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
a
i
d
e
d
P
I
D
g
a
i
t
c
o
n
t
r
o
l
l
e
r
d
e
si
g
n
f
o
r
a
h
u
ma
n
o
i
d
r
o
b
o
t
,
”
I
S
A
T
ra
n
s
a
c
t
i
o
n
s
,
v
o
l
.
1
1
4
,
p
p
.
3
0
6
–
3
3
0
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
sa
t
r
a
.
2
0
2
0
.
1
2
.
0
3
3
.
[
1
3
]
Z.
X
i
a
n
g
,
D
.
J
i
,
H
.
Z
h
a
n
g
,
H
.
W
u
,
a
n
d
Y
.
L
i
,
“
A
s
i
mp
l
e
P
I
D
-
b
a
se
d
st
r
a
t
e
g
y
f
o
r
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
,
”
I
n
f
o
rm
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
5
0
2
,
p
p
.
5
5
8
–
5
7
4
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
n
s.
2
0
1
9
.
0
6
.
0
4
2
.
[
1
4
]
F
.
R
e
z
a
e
i
a
n
d
H
.
R
.
S
a
f
a
v
i
,
“
G
u
A
S
P
S
O
:
a
n
e
w
a
p
p
r
o
a
c
h
t
o
h
o
l
d
a
b
e
t
t
e
r
e
x
p
l
o
r
a
t
i
o
n
–
e
x
p
l
o
i
t
a
t
i
o
n
b
a
l
a
n
c
e
i
n
P
S
O
a
l
g
o
r
i
t
h
m,”
S
o
f
t
C
o
m
p
u
t
i
n
g
,
v
o
l
.
2
4
,
n
o
.
7
,
p
p
.
4
8
5
5
–
4
8
7
5
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
0
7
/
s
0
0
5
0
0
-
019
-
0
4
2
4
0
-
8.
[
1
5
]
J.
N
a
y
a
k
,
H
.
S
w
a
p
n
a
r
e
k
h
a
,
B
.
N
a
i
k
,
G
.
D
h
i
ma
n
,
a
n
d
S
.
V
i
mal
,
“
2
5
y
e
a
r
s
o
f
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
:
F
l
o
u
r
i
sh
i
n
g
v
o
y
a
g
e
o
f
t
w
o
d
e
c
a
d
e
s,
”
Arc
h
i
v
e
s
o
f
C
o
m
p
u
t
a
t
i
o
n
a
l
Me
t
h
o
d
s
i
n
E
n
g
i
n
e
e
r
i
n
g
,
v
o
l
.
3
0
,
n
o
.
3
,
p
p
.
1
6
6
3
–
1
7
2
5
,
A
p
r
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
8
3
1
-
0
2
2
-
0
9
8
4
9
-
x.
[
1
6
]
A
.
J.
M
a
l
i
k
,
W
.
S
h
a
h
z
a
d
,
a
n
d
F
.
A
.
K
h
a
n
,
“
N
e
t
w
o
r
k
i
n
t
r
u
si
o
n
d
e
t
e
c
t
i
o
n
u
si
n
g
h
y
b
r
i
d
b
i
n
a
r
y
P
S
O
a
n
d
r
a
n
d
o
m
f
o
r
e
st
s
a
l
g
o
r
i
t
h
m
,
”
S
e
c
u
r
i
t
y
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
N
e
t
w
o
r
k
s
,
v
o
l
.
5
,
n
o
.
4
,
p
p
.
4
2
2
–
4
3
7
,
2
0
1
2
,
d
o
i
:
1
0
.
1
0
0
2
/
s
e
c
.
[
1
7
]
A
.
J.
M
o
h
a
mm
e
d
,
“
A
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
(
P
S
O
)
b
a
se
d
o
p
t
i
m
u
m
o
f
t
u
n
i
n
g
P
I
D
c
o
n
t
r
o
l
l
e
r
f
o
r
a
s
e
p
a
r
a
t
e
l
y
e
x
c
i
t
e
d
D
C
mo
t
o
r
(
S
ED
M
)
,
”
En
g
i
n
e
e
r
i
n
g
a
n
d
T
e
c
h
n
o
l
o
g
y
J
o
u
rn
a
l
,
v
o
l
.
2
9
,
n
o
.
1
6
,
p
p
.
3
3
3
1
–
3
3
4
4
,
2
0
1
1
,
d
o
i
:
1
0
.
3
0
6
8
4
/
e
t
j
.
2
9
.
1
6
.
7
.
[
1
8
]
L.
X
u
-
z
h
o
u
,
Y
.
F
e
i
,
a
n
d
W
.
Y
o
u
-
b
o
,
“
P
S
O
a
l
g
o
r
i
t
h
m
b
a
s
e
d
o
n
l
i
n
e
s
e
l
f
-
t
u
n
i
n
g
o
f
P
I
D
c
o
n
t
r
o
l
l
e
r
,
”
i
n
2
0
0
7
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
a
t
i
o
n
a
l
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
S
e
c
u
ri
t
y
,
C
I
S
,
2
0
0
7
,
p
p
.
1
2
8
–
1
3
2
.
d
o
i
:
1
0
.
1
1
0
9
/
C
I
S
.
2
0
0
7
.
1
8
8
.
[
1
9
]
N
.
M
a
t
Y
a
h
y
a
a
n
d
M
.
N
.
O
sm
a
n
Z
a
h
i
d
,
“
A
p
p
l
i
c
a
t
i
o
n
o
f
a
d
a
p
t
i
v
e
b
a
t
s
so
n
a
r
a
l
g
o
r
i
t
h
m
f
o
r
so
l
v
i
n
g
a
si
n
g
l
e
o
b
j
e
c
t
i
v
e
o
f
p
r
a
c
t
i
c
a
l
b
u
s
i
n
e
ss
o
p
t
i
mi
s
a
t
i
o
n
,
”
E
-
J
o
u
r
n
a
l
o
f
Art
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
&
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
4
,
p
p
.
1
–
1
3
,
2
0
1
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
P
o
s
itio
n
tr
a
ck
in
g
o
f D
C
mo
to
r
w
ith
P
I
D
co
n
tr
o
ller
u
tili
z
in
g
p
a
r
ticle
s
w
a
r
m
…
(
N
u
r
I
ffa
h
Mo
h
a
med
A
z
mi
)
73
[
2
0
]
T.
M
.
S
h
a
m
i
,
A
.
A
.
El
-
S
a
l
e
h
,
M
.
A
l
sw
a
i
t
t
i
,
Q
.
A
l
-
T
a
s
h
i
,
M
.
A
.
S
u
mm
a
k
i
e
h
,
a
n
d
S
.
M
i
r
j
a
l
i
l
i
,
“
P
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
mi
z
a
t
i
o
n
:
A
c
o
m
p
r
e
h
e
n
si
v
e
su
r
v
e
y
,
”
I
EE
E
A
c
c
e
ss
,
v
o
l
.
1
0
,
p
p
.
1
0
0
3
1
–
1
0
0
6
1
,
2
0
2
2
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
2
.
3
1
4
2
8
5
9
.
[
2
1
]
D
.
S
e
d
i
g
h
i
z
a
d
e
h
,
E
.
M
a
s
e
h
i
a
n
,
M
.
S
e
d
i
g
h
i
z
a
d
e
h
,
a
n
d
H
.
A
k
b
a
r
i
p
o
u
r
,
“
G
EPS
O
:
A
n
e
w
g
e
n
e
r
a
l
i
z
e
d
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
a
l
g
o
r
i
t
h
m,
”
M
a
t
h
e
m
a
t
i
c
s
a
n
d
C
o
m
p
u
t
e
rs i
n
S
i
m
u
l
a
t
i
o
n
,
v
o
l
.
1
7
9
,
p
p
.
1
9
4
–
2
1
2
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
ma
t
c
o
m.
2
0
2
0
.
0
8
.
0
1
3
.
[
2
2
]
S
.
M
.
G
i
r
i
r
a
j
K
u
mar
,
D
.
Ja
y
a
r
a
j
,
a
n
d
A
.
R
.
K
i
s
h
a
n
,
“
P
S
O
b
a
s
e
d
t
u
n
i
n
g
o
f
a
P
I
D
c
o
n
t
r
o
l
l
e
r
f
o
r
a
h
i
g
h
p
e
r
f
o
r
ma
n
c
e
d
r
i
l
l
i
n
g
mac
h
i
n
e
,
”
I
n
t
e
rn
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
C
o
m
p
u
t
e
r A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
1
,
n
o
.
1
9
,
p
p
.
1
2
–
1
8
,
2
0
1
0
,
d
o
i
:
1
0
.
5
1
2
0
/
4
1
0
-
6
0
7
.
[
2
3
]
D
.
C
h
e
n
,
G
.
Z
h
a
n
g
,
a
n
d
C
.
Y
a
o
,
“
P
S
O
a
l
g
o
r
i
t
h
m
b
a
se
d
P
I
D
p
a
r
a
m
e
t
e
r
s o
p
t
i
m
i
z
a
t
i
o
n
o
f
h
y
d
r
a
u
l
i
c
screw
d
o
w
n
s
y
st
e
m o
f
c
o
l
d
s
t
r
i
p
mi
l
l
,
”
i
n
Pro
c
e
e
d
i
n
g
s
o
f
2
0
1
1
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
Fl
u
i
d
Po
w
e
r
a
n
d
Me
c
h
a
t
ro
n
i
c
s,
Be
i
j
i
n
g
,
C
h
i
n
a
,
2
0
1
1
,
p
p
.
1
1
3
–
1
1
6
.
d
o
i
:
1
0
.
1
1
0
9
/
F
P
M
.
2
0
1
1
.
6
0
4
5
7
4
0
.
[
2
4
]
M
.
M
.
M
a
f
a
r
j
a
,
R
.
J
a
r
r
a
r
,
S
.
A
h
ma
d
,
a
n
d
A
.
A
.
A
b
u
s
n
a
i
n
a
,
“
F
e
a
t
u
r
e
s
e
l
e
c
t
i
o
n
u
si
n
g
b
i
n
a
r
y
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
w
i
t
h
t
i
m
e
v
a
r
y
i
n
g
i
n
e
r
t
i
a
w
e
i
g
h
t
st
r
a
t
e
g
i
e
s,
”
2
0
1
8
.
d
o
i
:
1
0
.
1
1
4
5
/
3
2
3
1
0
5
3
.
3
2
3
1
0
7
1
.
[
2
5
]
N
.
M
a
t
Y
a
h
y
a
,
“
I
mp
r
o
v
e
me
n
t
o
f
t
h
e
f
e
e
d
b
a
c
k
c
o
n
t
r
o
l
sy
s
t
e
m
p
e
r
f
o
r
ma
n
c
e
b
y
o
p
t
i
mi
z
i
n
g
t
h
e
P
I
D
c
o
n
t
r
o
l
l
e
r
p
a
r
a
met
e
r
s
u
s
i
n
g
t
h
e
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m,”
(
i
n
M
a
l
a
y
s
i
a
n
:
P
e
n
i
n
g
k
a
t
a
n
p
r
e
s
t
a
si
si
s
t
e
m
p
e
m
a
c
u
su
a
p
b
a
l
i
k
d
e
n
g
a
n
men
g
o
p
t
i
m
u
m
k
a
n
p
a
r
a
m
e
t
e
r
p
e
n
g
a
w
a
l
P
I
D
men
g
g
u
n
a
k
a
n
a
l
g
o
r
i
t
m
a
p
e
n
g
o
p
t
i
mu
ma
n
k
a
w
a
n
a
n
p
a
r
t
i
k
e
l
)
M
.
S
.
T
h
e
s
i
s,
F
K
P
U
M
P
S
A
,
P
a
h
a
n
g
,
M
a
l
a
y
si
a
,
2
0
0
9
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Nur
Iffa
h
Mo
h
a
m
e
d
Az
m
i
is
c
u
rre
n
t
ly
a
p
o
st
g
ra
d
u
a
te
st
u
d
e
n
t
(Do
c
t
o
r
o
f
P
h
il
o
so
p
h
y
)
a
t
U
n
iv
e
rsit
i
M
a
la
y
sia
P
a
h
a
n
g
Al
-
S
u
lt
a
n
Ab
d
u
ll
a
h
.
S
h
e
is
w
o
rk
i
n
g
o
n
s
o
m
e
re
se
a
rc
h
in
c
o
m
p
u
tatio
n
a
l
i
n
tell
ig
e
n
c
e
a
n
d
o
p
ti
m
iza
ti
o
n
a
l
g
o
rit
h
m
s.
He
r
m
a
in
re
s
e
a
rc
h
d
irec
ti
o
n
s
i
n
c
lu
d
e
a
rti
ficia
l
in
t
e
ll
ig
e
n
c
e
(c
o
n
tro
l
s
y
ste
m
o
p
ti
m
iza
ti
o
n
,
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
b
io
-
in
sp
ired
c
o
m
p
u
tatio
n
i
n
telli
g
e
n
c
e
,
a
n
d
in
telli
g
e
n
t
m
a
n
u
fa
c
tu
r
in
g
a
u
to
m
a
ti
o
n
).
S
h
e
c
a
n
b
e
c
o
n
tac
te
d
a
t
n
u
riff
a
h
8
7
@
y
a
h
o
o
.
c
o
m
.
Na
fr
izua
n
M
a
t
Ya
h
y
a
g
ra
d
u
a
ted
wit
h
h
is
first
d
e
g
re
e
fro
m
th
e
Un
iv
e
rsiti
S
a
in
s
M
a
lay
sia
,
in
M
a
n
u
fa
c
tu
ri
n
g
En
g
i
n
e
e
rin
g
wit
h
M
a
n
a
g
e
m
e
n
t.
He
th
e
n
o
b
tain
e
d
h
is
M
a
ste
r
o
f
E
n
g
i
n
e
e
rin
g
(M
a
n
u
fa
c
tu
rin
g
)
fr
o
m
Un
i
v
e
rsiti
M
a
lay
sia
P
a
h
a
n
g
a
n
d
h
is
P
h
.
D.
i
n
a
u
to
m
a
ti
c
c
o
n
tro
l
a
n
d
sy
ste
m
s
e
n
g
in
e
e
rin
g
fro
m
th
e
Un
i
v
e
rsity
o
f
S
h
e
ffield
,
UK
.
His
in
tere
sts
in
c
lu
d
e
b
io
-
in
sp
ired
c
o
m
p
u
tati
o
n
i
n
telli
g
e
n
c
e
,
c
o
n
tr
o
l
sy
ste
m
o
p
ti
m
iza
ti
o
n
,
in
telli
g
e
n
t
m
a
n
u
fa
c
tu
rin
g
a
u
to
m
a
t
io
n
,
a
n
d
e
rg
o
n
o
m
ics
fo
r
i
n
d
u
strial
a
p
p
li
c
a
ti
o
n
s.
He
is
a
lso
a
p
ro
fe
ss
io
n
a
l
tec
h
n
o
lo
g
ist
o
f
th
e
M
a
lay
sia
Bo
a
rd
o
f
Tec
h
n
o
l
o
g
i
sts
(M
BOT).
He
c
a
n
b
e
c
o
n
tac
ted
a
t
n
a
frizu
a
n
m
y
@u
m
p
sa
.
e
d
u
.
m
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.