I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
p
ute
r
E
ng
in
ee
ring
(
I
J
E
CE
)
Vo
l.
9
,
No
.
2
,
A
p
r
il
201
9
,
p
p
.
8
1
5
~8
2
5
I
SS
N:
2
0
8
8
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v9
i
2
.
pp
815
-
8
2
5
815
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
co
r
e
.
co
m/
jo
u
r
n
a
ls
/in
d
ex
.
p
h
p
/
I
JE
C
E
A
new
sca
led f
u
zzy
m
e
thod usi
ng
P
SO
seg
m
en
tatio
n
(SeP
S
O
)
a
pplied for
tw
o
a
rea po
w
er sy
stem
B
a
la
s
i
m
M
.
H
us
s
ein
De
p
a
rtme
n
t
o
f
P
o
w
e
r
a
n
d
El
e
c
tri
c
a
l
M
a
c
h
in
e
s,
Co
l
leg
e
o
f
En
g
in
e
e
rin
g
,
Un
iv
e
rsity
O
f
Di
y
a
l
a
Di
y
a
la
,
Ira
q
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
A
p
r
2
7
,
2
0
1
8
R
ev
i
s
ed
Sep
1
3
,
2
0
1
8
A
cc
ep
ted
Oct
4
,
2
0
1
8
T
h
e
b
a
lan
c
e
o
f
th
e
p
o
w
e
r
su
p
p
ly
a
n
d
d
e
m
a
n
d
(
f
re
q
u
e
n
c
y
c
o
n
tro
l)
is
o
n
e
o
f
th
e
m
o
st
a
n
c
ien
t
a
p
p
ro
a
c
h
e
s
f
o
r
th
e
p
o
w
e
r
s
y
ste
m
s,
w
h
ich
is
c
o
n
si
d
e
re
d
a
s
a
h
ig
h
ly
c
o
m
p
lex
s
y
st
e
m
.
T
h
e
p
o
w
e
r
s
y
ste
m
s
f
r
e
q
u
e
n
c
y
re
sp
o
n
se
is
a
p
e
rf
e
c
t
in
d
ica
to
r
o
f
th
e
re
sili
e
n
c
e
to
th
e
m
u
lt
i
-
d
istu
rb
a
n
c
e
s.
In
t
h
is
w
o
rk
,
th
e
f
u
z
z
y
lo
g
ich
a
s
b
e
e
n
sc
a
led
u
sin
g
P
S
O
s
e
g
m
e
n
tatio
n
(
S
e
P
S
O
)
a
n
d
su
g
g
e
ste
d
to
g
e
t
h
ig
h
p
e
rf
o
rm
a
n
c
e
o
f
f
r
e
q
u
e
n
c
y
sta
b
il
it
y
.
P
S
O
h
a
s
p
a
rti
c
ip
a
ted
i
n
to
m
u
lt
i
-
se
g
m
e
n
ts
f
o
r
c
a
lcu
latin
g
th
e
s
c
a
ld
-
f
u
z
z
y
m
e
m
b
e
rsh
ip
w
it
h
b
a
sic
ru
le
s.
Tw
o
id
e
n
ti
c
a
l
in
terc
o
n
n
e
c
ted
p
o
w
e
r
a
re
a
s
w
e
re
se
lec
ted
to
e
x
a
m
th
e
n
e
w
sc
a
led
f
u
z
z
y
m
e
th
o
d
.
T
h
e
ti
m
e
re
sp
o
n
se
o
f
th
e
re
su
lt
s
h
a
s
u
n
d
e
rtak
e
n
th
e
e
ffe
c
ti
v
e
n
e
ss
o
f
th
e
c
o
n
tro
ll
e
r
re
a
c
ti
o
n
u
sin
g
th
e
M
ATLA
B
S
im
u
li
n
k
.
T
h
e
w
o
rk
f
e
e
d
b
a
c
k
p
ro
v
e
d
th
a
t
th
e
p
ro
p
o
se
d
S
e
P
S
O
o
p
ti
m
iza
ti
o
n
f
o
r
th
e
c
o
n
tro
l
h
a
s
sig
n
if
ica
n
tl
y
f
a
st
e
r
with
l
o
w
u
n
d
e
rsh
o
t
c
o
n
c
e
rn
i
n
g
th
e
c
las
sic
a
l
c
o
n
tro
ll
e
rs i
n
d
if
f
e
re
n
tt
i
m
e
sc
h
e
d
u
les
a
n
d
d
ist
u
rb
a
n
c
e
v
a
lu
e
s
.
K
ey
w
o
r
d
s
:
Co
n
tr
o
l
F
re
q
u
e
n
c
y
S
c
a
ld
-
f
u
z
z
y
S
e
g
m
e
n
tatio
n
Tw
o
a
re
a
Co
p
y
rig
h
t
©
2
0
1
9
In
stit
u
te o
f
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
rin
g
a
n
d
S
c
ien
c
e
.
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ba
las
i
m
M
.
Hu
ss
e
in
,
E
lectr
ical
E
n
g
i
n
ee
r
i
n
g
Dep
ar
t
m
en
t,
C
o
lleg
e
o
f
E
n
g
in
ee
r
i
n
g
,
Un
i
v
er
s
it
y
o
f
Di
y
ala,
Di
y
ala,
I
r
aq
.
E
m
ail: b
alasi
m
@
i
n
b
o
x
.
r
u
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
o
b
j
ec
tiv
e
of
g
en
er
ati
n
g
a
g
o
o
d
q
u
alit
y
o
f
a
n
elec
tr
ical
p
o
w
er
s
y
s
te
m
is
to
s
u
p
p
l
y
en
er
g
y
to
co
n
s
u
m
er
s
a
t
n
o
m
in
a
l
s
y
s
te
m
f
r
eq
u
en
c
y
a
n
d
v
o
lta
g
e
[
1
]
.
T
h
e
b
alan
cin
g
o
f
p
o
w
er
g
e
n
er
ati
o
n
w
ith
th
e
lo
ad
d
em
a
n
d
is
a
r
ea
l
ch
allen
g
e
in
th
e
h
i
g
h
l
y
co
m
p
le
x
co
n
tr
o
lled
s
y
s
te
m
[
2
]
.
No
r
m
all
y
,
t
h
e
s
tead
y
-
s
ta
te
f
r
eq
u
en
c
y
i
s
c
h
an
g
i
n
g
b
y
t
h
e
r
an
d
o
m
v
ar
iatio
n
o
f
t
h
e
c
u
s
to
m
er
'
s
e
n
er
g
y
d
e
m
a
n
d
,
a
n
d
L
FC
is
t
h
e
co
n
tr
o
ller
w
h
ich
r
esp
o
n
s
ib
le
f
o
r
r
eset th
e
n
o
r
m
al
co
n
d
itio
n
[
2
]
.
T
h
e
L
FC
p
er
f
o
r
m
a
n
ce
i
s
d
ir
ec
tl
y
a
f
f
ec
t
in
g
b
y
t
h
e
f
ee
d
b
a
ck
co
n
tr
o
ller
d
esig
n
to
m
ai
n
t
ain
th
e
p
o
w
er
tr
an
s
f
er
r
ed
b
et
w
ee
n
th
e
t
w
o
ar
ea
s
at
i
ts
'
e
x
p
ec
ted
v
al
u
es
[
3
]
.
T
h
e
ar
ea
co
n
tr
o
l
er
r
o
r
(
AC
E
)
is
m
o
s
t
i
m
p
o
r
tan
t c
h
allen
g
e
i
n
th
e
L
F
C
lo
o
p
w
h
ic
h
i
s
r
ep
r
esen
ti
n
g
a
s
th
e
co
n
tr
o
l o
u
tp
u
t[
3
]
.
T
h
e
class
ical
co
n
tr
o
ller
s
h
av
e
b
ee
n
u
s
ed
i
n
d
if
f
er
en
t
p
o
w
er
s
y
s
te
m
o
p
er
atio
n
an
d
co
n
tr
o
l
t
o
p
ics
d
u
e
to
its
s
i
m
p
lic
it
y
.
B
u
t,
t
h
e
m
a
in
d
r
a
w
b
ac
k
o
f
cla
s
s
ica
l
co
n
tr
o
ller
is
t
u
n
in
g
it
s
p
ar
a
m
eter
s
an
d
it
is
d
es
ig
n
f
o
r
n
ar
r
o
w
co
n
d
itio
n
s
[
2
]
,
[
3
]
.
T
o
co
u
n
ter
ac
t
th
e
b
ad
cir
cu
m
s
t
an
ce
s
o
f
c
la
s
s
ical
f
r
eq
u
en
c
y
co
n
tr
o
ller
s
;
m
a
n
y
i
n
telli
g
e
n
t
co
n
tr
o
l
m
et
h
o
d
s
h
a
v
e
b
ee
n
p
u
t
f
o
r
w
ar
d
an
d
s
tu
d
ied
to
w
ar
d
s
d
ev
elo
p
in
g
t
h
e
s
tab
ilit
y
[
3
]
,
[
4
]
.
No
r
m
a
ll
y
th
e
f
u
zz
y
co
n
tr
o
ll
er
s
h
a
v
e
n
o
t
b
ee
n
ab
le
to
d
i
m
in
is
h
t
h
e
d
ar
k
n
ess
b
e
y
o
n
d
o
f
cla
s
s
ical
co
n
tr
o
ller
s
,
th
er
e
w
it
h
th
e
ca
s
es
w
h
ich
ar
e
ex
a
m
i
n
ed
w
it
h
th
e
i
n
telli
g
e
n
t
m
et
h
o
d
o
lo
g
y
a
r
e
u
n
d
o
u
b
ted
l
y
n
eg
l
ig
ib
le
w
it
h
r
esp
ec
t
to
t
h
e
u
n
co
m
p
e
n
s
ated
p
r
o
b
lem
s
[
1
]
.
On
e
s
o
f
th
e
m
o
s
t
r
ea
lis
t
ic
co
n
d
itio
n
s
to
g
et
a
p
r
o
m
i
s
ed
r
esu
lt
s
in
a
n
y
f
u
z
z
y
co
n
tr
o
ller
ar
e
th
e
o
b
tain
i
n
g
a
n
d
o
p
ti
m
izi
n
g
th
e
f
u
zz
y
r
u
le
s
an
d
it
s
'
m
e
m
b
er
s
h
ip
s
[
5
].
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
p
r
il 2
0
1
9
:
8
1
5
-
8
2
5
816
P
SO
co
n
tr
o
l
f
u
zz
y
g
a
in
at
e
ac
h
ar
ea
af
ter
s
u
d
d
en
u
p
d
at
e
o
f
th
e
ac
tiv
e
p
o
w
er
u
s
in
g
a
n
e
w
alg
o
r
ith
m
s
u
g
g
ested
b
y
A
.
J
a
b
er
et
a
l.
,
[
6
]
.
Oth
er
w
o
r
k
s
,
i
n
v
o
l
v
ed
th
e
u
s
e
o
f
Ge
n
etic
Alg
o
r
ith
m
or
A
n
t
C
o
lo
n
y
Op
ti
m
iza
tio
n
to
s
ca
ld
th
e
f
u
zz
y
f
o
r
d
r
iv
i
n
g
t
h
e
f
r
eq
u
en
c
y
co
n
tr
o
l in
p
o
w
er
s
y
s
te
m
s
[
7
]
-
[
9
]
.
Ho
w
e
v
er
,
ev
e
n
t
h
o
u
g
h
P
SO
o
r
Ga
s
tr
ateg
ie
s
to
s
ca
le
th
e
f
u
z
z
y
is
p
er
f
o
r
m
i
n
g
w
ell
i
n
s
o
m
e
ca
s
es,
th
e
y
m
a
y
f
a
il to
en
s
u
r
e
th
at
t
h
e
f
r
eq
u
en
c
y
r
esp
o
n
s
e
[
1
0
]
-
[
12]
.
I
n
th
is
p
ap
er
,
Se
-
P
SO
w
a
s
u
s
ed
to
g
et
t
h
e
o
p
ti
m
al
g
ai
n
to
s
ca
le
t
h
e
f
u
zz
y
P
I
D
co
n
tr
o
ller
.
T
h
is
co
n
tr
o
ller
h
as
ap
p
lied
to
t
w
o
s
y
m
m
etr
ica
l
ar
ea
s
w
h
ic
h
w
er
e
s
i
m
u
lated
u
s
i
n
g
M
A
T
L
A
B
.
T
h
e
r
an
g
e
in
itial
v
al
u
e
s
o
o
f
t
h
e
F
u
zz
y
co
n
tr
o
ller
g
ai
n
s
h
a
v
e
b
ee
n
d
iv
id
ed
in
to
a
d
i
f
f
er
e
n
t
n
u
m
b
er
o
f
s
eg
m
e
n
ts
.
T
h
e
s
i
m
u
la
tio
n
r
esu
lts
h
a
v
e
d
em
o
n
s
tr
ated
th
e
f
ea
s
ib
ili
t
y
o
f
th
e
en
s
e
m
b
le
i
n
th
e
s
u
g
g
e
s
ted
m
eth
o
d
v
ia
I
T
A
E
p
r
o
p
er
ties
esti
m
at
io
n
ap
p
r
o
ac
h
w
it
h
r
esp
ec
t to
P
I
D
an
d
P
SO
-
s
ca
led
f
u
zz
y
.
2.
M
O
DE
L
O
F
I
NT
E
RCO
N
N
E
CT
E
D
P
O
W
E
R
SY
ST
E
M
AREAS
T
h
e
t
w
o
m
ai
n
r
ea
s
o
n
s
f
o
r
A
u
to
m
atic
Ge
n
er
atio
n
C
o
n
tr
o
l
(
A
V
C
)
to
n
eg
lec
t
Au
to
m
at
ic
Vo
ltag
e
R
eg
u
lato
r
th
e
A
V
R
lo
o
p
I
n
in
t
er
co
n
n
ec
ted
p
o
w
er
s
y
s
te
m
ar
e
:
-
a)
T
h
e
v
o
ltag
e
r
e
m
ai
n
s
f
air
l
y
co
n
s
ta
n
t
d
u
r
i
n
g
s
m
al
l
ch
a
n
g
es
in
t
h
e
s
y
s
te
m
’
s
lo
ad
,
w
h
ile
th
e
d
ev
iatio
n
i
n
f
r
eq
u
e
n
c
y
.
b)
T
h
e
A
VC
i
s
f
a
s
ter
th
a
n
t
h
e
p
r
im
e
m
o
v
er
r
ea
ctio
n
.
So
th
e
m
o
d
el
i
s
co
n
s
is
t
o
f
f
o
u
r
p
ar
ts
o
f
s
i
m
u
latio
n
(
Go
v
er
n
o
r
T
u
r
b
in
e
Mo
d
el
,
T
ie
L
in
e
Mo
d
el,
an
d
C
o
n
tr
o
l
A
r
ea
Mo
d
elin
g
)
T
h
e
p
ar
am
eter
s
o
f
th
e
s
ep
ar
ated
ar
ea
o
f
a
p
o
w
er
s
y
s
t
e
m
ca
n
r
ep
r
esen
t
in
t
h
e
b
lo
ck
d
iag
r
a
m
as
f
o
llo
w
s
[
1
3
]
-
[
19]
.
Sin
g
le
ar
ea
p
o
w
er
s
y
s
te
m
is
s
h
o
w
n
i
n
Fi
g
u
r
e
1
.
N
j
i
j
ij
T
1
s
/
2
N
j
i
j
j
ij
f
T
1
Li
P
gi
P
mi
P
Fig
u
r
e
1
.
Sin
g
le
ar
ea
p
o
w
er
s
y
s
te
m
3.
P
SO
M
AT
H
E
M
AT
I
CA
L
M
O
DE
L
In
1
9
9
5
,
P
SO
alg
o
r
ith
m
was
in
tr
o
d
u
ce
d
b
y
E
b
er
h
ar
t
an
d
Ken
n
ed
y
a
s
a
n
o
v
el
h
eu
r
is
tic
m
et
h
o
d
[
2
0
]
.
T
h
e
P
SO in
d
ex
o
f
t
h
e
b
est p
ar
ticle
in
th
e
p
o
p
u
latio
n
is
r
ep
r
e
s
en
ti
n
g
b
y
t
h
e
s
y
m
b
o
l g
.
A
t e
a
ch
ti
m
e
s
tep
t i
n
th
e
s
i
m
u
latio
n
t
h
e
v
el
o
cit
y
o
f
t
h
e
i
th
p
ar
ticle
r
ep
r
es
en
ted
as
v
i
=
(
v
i1
, v
i2
,
.
.
.
,
v
id
)
,
is
ad
j
u
s
ted
alo
n
g
ea
ch
ax
i
s
j
th
e
eq
u
atio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
A
n
ew s
ca
led
fu
z
z
y
meth
o
d
u
s
in
g
P
S
O
s
eg
men
ta
tio
n
(
S
eP
S
O
)
a
p
p
lied
fo
r
tw
o
…
(
B
a
la
s
im
M.
Hu
s
s
ein
)
817
(
)
(
)
(
(
)
(
)
)
(
(
)
(
)
)
(
1
)
W
h
er
e
c
1
,
c
2
ar
e
ac
ce
ler
atio
n
c
o
ef
f
icie
n
t
s
,
p
i
a
n
d
G
i
th
e
lo
ca
l
an
d
g
lo
b
al
o
p
ti
m
u
m
p
o
in
t
af
te
r
ea
ch
i
ter
atio
n
r
esp
ec
tiv
el
y
,
a
n
d
ω
is
w
ei
g
h
t
o
f
in
er
tia.
p
i
an
d
G
i
ar
e
co
g
n
iti
v
e
an
d
s
o
cial
ac
ce
ler
atio
n
co
ef
f
icien
t.
A
l
s
o
,
th
e
p
ar
ticle’
s
v
e
lo
cit
y
r
an
g
e
i
s
co
n
s
ta
n
t a
n
d
u
p
d
ati
n
g
f
o
r
ea
ch
iter
atio
n
as :
[
]
(
2
)
T
h
e
n
e
w
p
o
s
itio
n
o
f
a
p
ar
ticle
is
ca
lcu
la
ted
ac
co
r
d
in
g
to
th
e
eq
u
atio
n
s
h
o
w
n
:
(
)
(
)
(
)
(
3
)
Mo
r
eo
v
er
,
p
er
s
o
n
al
n
e
w
p
o
s
iti
o
n
o
f
th
e
p
ar
ticle
is
u
p
d
ated
u
s
in
g
(
)
{
(
(
)
)
(
(
)
)
(
)
(
(
)
)
(
(
)
)
(
4
)
W
h
ile
th
e
g
lo
b
al
b
est in
d
ex
i
s
d
ef
in
ed
as:
(
)
)
(
5
)
4.
SeP
SO
M
E
T
H
O
D
T
h
e
r
eq
u
ir
em
e
n
t
to
d
ev
elo
p
a
n
e
w
tec
h
n
iq
u
e
to
in
cr
ea
s
e
t
h
e
ac
cu
r
ac
y
o
f
P
SO
w
a
s
b
ec
am
e
o
n
e
o
f
th
e
m
ai
n
to
p
ics
i
n
o
p
ti
m
izat
io
n
s
cie
n
ce
.
T
h
e
ca
s
e
o
f
e
x
i
s
tin
g
m
o
r
e
th
a
n
a
n
o
p
ti
m
a
l
p
o
in
t
w
h
ich
is
ex
p
lain
ed
i
n
2
.
4
,
is
a
b
ig
p
r
o
b
l
e
m
in
P
SO.
T
h
e
d
iv
id
ed
o
f
th
e
s
ea
r
ch
in
g
p
ar
ticles
in
to
s
ea
r
c
h
in
g
g
r
o
u
p
s
is
t
h
e
ai
m
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
.
E
ac
h
s
eg
m
e
n
t
is
a
P
SO
alg
o
r
ith
m
to
ev
al
u
ate
th
e
g
lo
b
al
p
o
in
t
as
s
h
o
w
n
in
F
i
g
u
r
e
2
.
T
h
e
o
p
tim
al
in
itial
r
an
g
e
is
al
w
a
y
s
g
i
v
e
n
a
f
a
s
ter
co
n
v
er
g
e
n
ce
to
ac
h
ie
v
e
t
h
e
o
p
ti
m
al
g
lo
b
al
p
o
in
t [
2
0
]
.
Fig
u
r
e
2
.
Op
ti
m
al
lo
ca
l a
n
d
g
l
o
b
al
p
o
in
ts
I
n
Fi
g
u
r
e
2
,
p
o
in
ts
1
,
2
an
d
3
ca
n
b
e
ass
u
m
ed
as
a
s
e
g
m
en
t
o
p
ti
m
al
lo
ca
l
p
o
in
t
s
,
b
u
t
t
h
e
g
lo
b
al
o
p
tim
a
l
p
o
in
t
is
3.
A
m
o
d
if
ica
tio
n
o
f
P
SO
eq
u
at
io
n
s
w
it
h
a
d
d
itio
n
al
eq
u
atio
n
h
a
v
e
b
ee
n
d
o
n
e
to
g
et
t
h
e
o
p
tim
a
l se
g
m
e
n
t a
n
d
p
o
in
t a
s
s
h
o
w
n
[
2
1
]
;
(
6
)
(
)
(
)
(
(
)
(
)
)
(
(
)
(
)
)
(
7
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
p
r
il 2
0
1
9
:
8
1
5
-
8
2
5
818
(
)
(
)
(
)
(
8
)
Hen
ce
;
(
9
)
W
h
er
e
,
j
is
th
e
to
talp
ar
a
m
eter
s
eg
m
e
n
t
n
u
m
b
er
.
A
ls
o
th
e
f
lo
wch
ar
t o
f
th
e
SeP
SO
is
s
h
o
w
n
i
n
Fi
g
u
r
e
3
.
Fig
u
r
e
3
.
SeP
SO o
p
tim
iza
tio
n
5.
SCAL
E
D
F
U
Z
Z
Y
CO
N
T
R
O
L
L
E
R
T
h
e
ex
p
er
t
in
clas
s
ical
Fu
zz
y
m
et
h
o
d
s
is
th
e
ad
j
u
s
ted
w
a
y
t
o
ca
lcu
late
th
e
b
o
u
n
d
ar
y
o
f
th
e
f
u
zz
y
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
,
w
h
ic
h
is
n
o
t
s
u
r
e
to
g
u
ar
an
tee
th
e
s
y
s
te
m
s
’
p
er
f
o
r
m
an
ce
[
2
]
.
On
th
e
o
th
er
h
an
d
,
u
s
i
n
g
o
f
i
n
tel
lig
e
n
t
s
ea
r
ch
o
p
t
i
m
izatio
n
m
et
h
o
d
s
to
s
elec
t
t
h
e
b
o
u
n
d
ar
ies
o
f
th
e
m
e
m
b
er
s
h
ip
s
ar
e
li
m
ited
u
p
o
n
th
e
d
esi
g
n
ed
o
p
er
atio
n
co
n
d
itio
n
s
.
T
h
e
Scaled
Fu
zz
y
co
n
tr
o
ller
ca
n
in
cr
ea
s
e
th
e
co
n
tr
o
l
o
p
er
atio
n
co
n
d
itio
n
s
.
T
h
is
co
n
tr
o
ller
is
d
ep
en
d
in
g
o
n
ad
ap
ti
n
g
th
e
er
r
o
r
an
d
th
e
ch
a
n
g
e
o
f
er
r
o
r
(
th
e
in
p
u
t
o
f
th
e
f
u
zz
y
co
n
t
r
o
ller
)
ac
co
r
d
in
g
to
th
e
f
u
zz
y
m
e
m
b
er
s
h
ip
in
s
tead
o
f
ch
a
n
g
i
n
g
th
e
m
e
m
b
er
s
h
ip
s
ac
co
r
d
in
g
to
th
e
o
p
er
atio
n
co
n
d
itio
n
.
Fo
r
ex
a
m
p
le,
w
e
s
u
p
p
o
s
ed
t
h
at
th
e
b
o
u
n
d
ar
ies
o
f
th
e
i
n
p
u
t
to
th
e
f
u
zz
y
co
n
tr
o
ller
ar
e
f
r
o
m
1
0
0
to
-
1
0
0
,
an
d
th
e
s
elec
ted
m
e
m
b
er
s
h
ip
s
ar
e
f
r
o
m
1
to
-
1
.
I
n
t
h
is
ca
s
e
to
ad
ap
t
th
e
in
p
u
t
w
i
th
th
e
f
u
zz
y
s
y
s
te
m
w
e
ca
n
m
u
ltip
l
y
t
h
e
i
n
p
u
t
b
y
a
g
ai
n
o
f
1
/1
0
0
w
it
h
o
u
t
n
ee
d
to
ch
an
g
e
in
f
u
zz
y
m
e
m
b
er
s
h
ip
f
i
g
u
r
e
s
.
T
h
is
g
ain
i
s
ca
lled
th
e
s
ca
led
f
u
zz
y
p
ar
a
m
e
ter
.
Fig
u
r
e
4
is
s
h
o
w
t
h
e
o
v
er
all
s
ca
led
p
ar
a
m
et
e
r
co
n
tr
o
l.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
A
n
ew s
ca
led
fu
z
z
y
meth
o
d
u
s
in
g
P
S
O
s
eg
men
ta
tio
n
(
S
eP
S
O
)
a
p
p
lied
fo
r
tw
o
…
(
B
a
la
s
im
M.
Hu
s
s
ein
)
819
Fig
u
r
e
4
.
Scaled
f
u
zz
y
co
n
tr
o
l
ler
W
as
p
r
o
p
o
s
ed
to
co
n
tr
o
l
th
e
f
r
eq
u
en
c
y
b
y
B
r
o
u
j
en
i
[
1
4
]
.
H
o
w
e
v
er
,
th
e
u
s
i
n
g
o
f
G
A
m
a
y
ef
f
ec
t
by
t
h
e
i
n
itial
v
al
u
es
w
h
ic
h
ca
u
s
ed
to
d
iv
er
g
en
ce
a
n
d
co
n
v
er
g
en
ce
o
f
t
h
e
o
p
ti
m
u
m
p
o
in
t.
6.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
T
o
o
v
er
co
m
e
th
e
s
lo
w
r
esp
o
n
s
e
o
f
u
s
in
g
th
e
G
A
a
n
d
P
SO
in
s
ca
led
f
u
zz
y
P
I
co
n
tr
o
ller
,
A
co
m
b
in
a
tio
n
b
et
w
ee
n
SeP
SO
an
d
f
u
zz
y
P
I
co
n
tr
o
ller
th
e
b
o
u
n
d
ar
ies
to
S
y
n
th
e
s
is
t
h
e
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
(
s
ca
led
f
u
zz
y
g
ai
n
s
)
.
T
h
ese
g
ai
n
s
r
ep
r
esen
ted
b
y
t
h
r
ee
p
ar
a
m
eter
s
Go
u
t,
Gi
n
1
,
an
d
Gi
n
2
,
w
h
ich
ar
e
s
h
o
w
n
i
n
Fi
g
u
r
e
5
[
2
]
,
[
1
4
]
.
T
h
e
r
u
le
o
f
th
e
f
u
zz
y
h
a
s
b
ee
n
s
u
g
g
e
s
ted
as
i
n
T
ab
le1
ac
co
r
d
in
g
to
t
h
e
in
p
u
t
s
an
d
t
h
e
o
u
tp
u
t
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
w
h
ic
h
ar
e
s
h
o
w
n
in
Fi
g
u
r
e
6.
T
h
e
f
lo
w
ch
ar
t
o
f
SeP
SO
alg
o
r
ith
m
to
s
ca
led
th
e
f
u
zz
y
P
I
p
a
r
am
eter
s
a
s
o
p
ti
m
al
r
esp
o
n
s
e
is
s
h
o
w
n
in
F
ig
u
r
e
7
.
T
ab
le
1
.
Scaled
Fu
zz
y
R
u
les
⁄
PP
SP
ZE
SN
NN
PP
PP
SP
SP
ZE
ZE
SP
SP
SP
ZE
ZE
NS
ZE
SP
ZE
ZE
NS
NS
SN
ZE
ZE
NS
NS
NN
NN
ZE
NS
NS
NN
NN
W
h
er
e:
P
P
: m
ed
iu
m
p
o
s
iti
v
e,
SP
: s
m
all
p
o
s
iti
v
e,
SN
: s
m
all
n
eg
ati
v
e,
Z
E
: z
er
o
an
d
NN:
m
e
d
iu
m
n
eg
a
tiv
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
p
r
il 2
0
1
9
:
8
1
5
-
8
2
5
820
T
h
e
r
u
les
in
th
e
f
u
zz
y
co
n
tr
o
ller
w
h
ic
h
ar
e
u
s
ed
in
t
h
is
w
o
r
k
s
ca
n
b
e
lis
ted
in
T
ab
le
1
.
A
ls
o
a
b
asic
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
ets
o
f
i
d
en
tical
tr
ian
g
le
s
w
a
s
u
s
ed
f
o
r
th
e
in
p
u
t
an
d
th
e
o
u
tp
u
t
o
f
f
u
zz
y
as
s
h
o
w
n
i
n
Fig
u
r
e
6
.
I
n
th
is
co
n
tr
o
ller
,
MO
Md
ef
u
zz
if
ica
tio
n
m
et
h
o
d
h
as
b
ee
n
p
er
f
o
r
m
ed
in
t
h
is
w
o
r
k
.
Fig
u
r
e
5
.
Scaled
Fu
zz
y
P
I
co
n
tr
o
ller
Fig
u
r
e
6
.
I
n
p
u
t &
o
u
tp
u
t M
e
m
b
er
s
h
ip
On
t
h
e
o
t
h
er
h
an
d
,
t
h
e
c
h
a
n
g
e
an
d
d
ev
elo
p
i
n
g
o
f
b
as
ic
P
S
O
h
a
v
e
r
ed
u
ce
d
t
h
e
w
ea
k
p
o
in
ts
o
f
o
p
tim
a
l
s
o
lu
tio
n
o
f
m
a
n
y
p
r
o
b
lem
s
[
2
1
]
,
[
2
2
]
.
Am
o
n
g
t
h
e
p
ar
tial
s
w
ar
m
i
m
p
r
o
v
e
m
en
t
,
th
e
al
g
o
r
ith
m
s
s
ea
r
ch
i
n
g
h
as
b
ee
n
d
iv
id
ed
in
t
o
g
r
o
u
p
s
ea
ch
o
n
e
w
as
n
a
m
e
d
s
eg
m
en
t,
a
n
d
t
h
e
m
et
h
o
d
w
as
n
a
m
ed
P
SO
s
eg
m
e
n
tatio
n
[
2
0
]
.
I
n
th
i
s
p
ap
er
,
Se
-
P
SO
w
as
u
s
ed
to
ca
lcu
late
th
e
o
p
ti
m
al
g
a
in
to
s
ca
le
t
h
e
f
u
zz
y
P
I
D
co
n
tr
o
ller
.
T
h
e
f
u
zz
y
co
n
tr
o
l
h
as
ap
p
lied
to
t
w
o
s
y
m
m
etr
ical
ar
ea
s
w
h
i
ch
w
er
e
s
i
m
u
lated
u
s
in
g
M
AT
L
A
B
.
E
ac
h
o
f
Kp
,
Kd
,
an
d
K
iin
itia
l
v
al
u
es
r
an
g
e
s
h
av
e
d
iv
id
ed
i
n
to
a
d
i
f
f
er
en
t
n
u
m
b
er
o
f
s
e
g
m
e
n
t
s
.
T
h
e
s
i
m
u
lat
io
n
r
esu
lt
s
h
a
v
e
d
e
m
o
n
s
tr
ated
th
e
f
ea
s
ib
ilit
y
o
f
th
e
e
n
s
e
m
b
le
in
th
e
s
u
g
g
e
s
ted
m
et
h
o
d
v
ia
I
T
A
E
p
r
o
p
er
ties
esti
m
atio
n
ap
p
r
o
ac
h
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
A
n
ew s
ca
led
fu
z
z
y
meth
o
d
u
s
in
g
P
S
O
s
eg
men
ta
tio
n
(
S
eP
S
O
)
a
p
p
lied
fo
r
tw
o
…
(
B
a
la
s
im
M.
Hu
s
s
ein
)
821
Fig
u
r
e
7
.
Scaled
f
u
zz
y
p
ar
a
m
e
ter
u
s
i
n
g
SeP
SO
7.
SI
M
UL
AT
I
O
N
R
E
S
UL
T
S
T
h
e
s
i
m
u
latio
n
p
ar
a
m
eter
s
w
h
ich
is
u
s
ed
in
t
h
i
s
p
ap
er
ar
e
g
i
v
en
in
T
ab
le
2
.
T
h
e
f
ir
s
t
Si
m
u
latio
n
d
is
tu
r
b
an
ce
i
n
th
e
p
o
w
er
s
y
s
t
e
m
w
as
s
et
to
3
0
s
an
d
th
e
d
e
f
er
en
ce
m
o
m
e
n
ts
o
f
lo
ad
ch
an
g
e.
B
o
th
o
f
th
e
t
w
o
ar
ea
s
w
er
e
s
e
ts
to
1
0
%
o
f
s
u
d
d
en
l
y
d
ev
ia
tio
n
i
n
t
h
e
p
o
w
er
b
u
t
w
it
h
0
an
d
2
s
ec
o
n
d
r
esp
ec
tiv
el
y
a
n
d
Fig
u
r
e
8
s
h
o
w
s
t
h
e
ti
m
e
r
esp
o
n
s
e
o
f
t
h
e
f
r
eq
u
en
c
y
.
Seco
n
d
l
y
;
f
o
u
r
v
al
u
es
o
f
d
is
t
u
r
b
an
ce
in
t
h
e
s
ec
o
n
d
ar
ea
w
ith
s
a
m
e
ti
m
e
s
c
h
ed
u
le
a
n
d
d
is
t
u
r
b
an
ce
o
f
ar
ea
o
n
e
w
er
e
s
elec
ted
t
o
v
alid
ate
th
e
s
y
s
te
m
,
o
n
e
o
f
th
eir
s
h
o
w
n
i
n
Fi
g
u
r
e
9
.
A
n
o
t
h
er
th
r
ee
d
is
tu
r
b
an
ce
ca
s
e
s
ca
n
b
e
n
o
ted
in
T
a
b
le
3
,
w
h
ic
h
ar
e
s
h
o
w
i
n
g
th
e
ti
m
e
r
esp
o
n
s
e
s
o
f
t
h
e
s
y
s
te
m
.
T
h
e
h
ig
h
er
ad
v
a
n
ta
g
e
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
is
0
.
0
1
2
1
p
u
w
it
h
2
0
% d
is
tu
r
b
an
ce
.
T
ab
le
2
.
Sy
s
te
m
P
ar
a
m
eter
s
R
Ts
Tt
Kp
Tp
2
.
4
0
.
0
8
0
.
0
3
1
2
0
20
T
ab
le
3
.
T
h
e
Pro
p
e
r
ties
o
f
C
h
an
g
i
n
g
P
o
w
er
in
A
r
ea
T
w
o
A
r
e
a
2
C
h
a
n
g
i
n
g
P
I
D
PSO
-
F
u
z
z
y
S
e
P
S
O
-
F
u
z
z
y
U
-
Sh
S
e
t
t
l
i
n
g
t
i
me
U
-
Sh
S
e
t
t
l
i
n
g
t
i
me
U
-
Sh
S
e
t
t
l
i
n
g
t
i
me
1
0
%
7
5
7
0
.
0
>
3
0
7
5
7
0
.
0
2
3
.
2
3
1
7
5
7
0
0
0
2
1
.
4
1
4
2
0
%
7
5
7
0
0
0
>
3
0
7
5
7
.
0
0
2
4
.
4
3
1
7
5
7
0
0
0
2
2
.
9
4
4
2
5
%
7
5
7
0
7
.
>
3
0
7
5
7
0
0
0
2
5
.
1
1
2
7
5
7
.
0
0
2
3
.
2
1
6
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
p
r
il 2
0
1
9
:
8
1
5
-
8
2
5
822
W
h
er
e:
-
U
-
S
h
is
u
n
d
er
s
h
o
t
A
l
s
o
m
u
lti
-
d
is
t
u
r
b
an
ce
s
o
f
b
o
th
ar
ea
s
w
it
h
s
a
m
e
ti
m
e
s
c
h
ed
u
le
w
as
ap
p
lied
to
ex
a
m
th
e
n
e
w
s
ca
led
m
et
h
o
d
,
o
n
e
o
f
th
eir
s
h
o
w
n
in
Fig
u
r
e
1
0
.
A
n
o
t
h
er
ca
s
es
s
ee
n
in
T
ab
leb
4
.
T
h
e
d
ar
k
w
o
r
d
s
o
f
th
e
cla
s
s
ical
co
n
tr
o
ller
ca
n
b
e
clea
r
ly
n
o
tes
in
th
e
T
ab
le
4
.
Fig
u
r
e
8
.
Fre
q
u
en
c
y
c
h
a
n
g
i
n
g
o
f
ca
s
e
1
Fig
u
r
e
9
.
Fre
q
u
en
c
y
c
h
a
n
g
i
n
g
1
0
% a
r
ea
1
,
1
5
% a
r
ea
2
Fig
u
r
e1
0
.
Fre
q
u
en
c
y
c
h
a
n
g
i
n
g
2
0
% a
r
ea
1
,
2
0
% a
r
ea
2
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
A
n
ew s
ca
led
fu
z
z
y
meth
o
d
u
s
in
g
P
S
O
s
eg
men
ta
tio
n
(
S
eP
S
O
)
a
p
p
lied
fo
r
tw
o
…
(
B
a
la
s
im
M.
Hu
s
s
ein
)
823
T
ab
le
4
.
T
h
e
Pro
p
e
r
ties
o
f
C
h
an
g
i
n
g
P
o
w
er
in
B
o
th
A
r
ea
s
B
o
t
h
A
r
e
a
C
h
a
n
g
i
n
g
P
I
D
PSO
-
F
u
z
z
y
S
e
P
S
O
-
F
u
z
z
y
U
-
Sh
U
-
Sh
U
-
Sh
1
0
%
7
5
7
0
.
0
7
5
7
0
.
0
7
5
7
0
0
0
3
0
%
7
5
0
.
0
7
7
5
0
0
0
0
7
5
0
0
0
.
4
0
%
7
5
0
7
0
0
7
5
0
0
0
.
7
5
0
0
0
0
L
ast
l
y
t
h
e
c
h
an
g
e
w
as
in
ti
m
e
s
c
h
ed
u
le
o
f
t
h
e
d
is
t
u
r
b
an
ce
s
;
t
h
e
d
i
s
tu
r
b
an
ce
o
f
t
h
e
f
ir
s
t
ar
ea
is
al
w
a
y
s
ze
r
o
s
ec
,
b
u
t
t
h
e
s
ec
o
n
d
d
is
tu
r
b
an
ce
ch
a
n
g
ed
f
r
o
m
4
to
8
s
ec
o
n
d
,
f
o
r
4
s
ec
t
i
m
e
d
i
s
tu
r
b
an
ce
s
h
o
w
n
i
n
F
ig
u
r
e
1
1
.
A
n
o
t
h
er
th
r
ee
ca
s
e
s
ar
e
s
u
p
p
o
s
ed
in
ti
m
e
s
ch
ed
u
le
a
n
d
th
e
r
esu
lts
c
an
b
e
s
h
o
w
n
i
n
T
ab
le
5
.
Fig
u
r
e
1
1
.
Fre
q
u
en
c
y
c
h
an
g
i
n
g
w
it
h
4
s
ec
s
ch
ed
u
le
ti
m
e
o
f
ar
ea
2
T
ab
le
5
.
T
h
e
Pro
p
e
r
ties
o
f
C
h
an
g
i
n
g
T
i
m
e
Sch
ed
u
le
D
i
st
u
r
b
a
n
c
e
T
i
me
o
f
A
r
e
a
2
P
I
D
PSO
-
F
u
z
z
y
S
e
P
S
O
-
F
u
z
z
y
U
-
Sh
U
-
Sh
U
-
Sh
2
7
5
7
0
.
0
7
5
7
0
.
0
7
5
7
0
0
0
6
7
5
7
0
.
7
7
5
7
.
0
.
7
5
7
.
.
0
8
7
5
7
0
.
7
7
5
7
.
0
.
7
5
7
.
.
0
I
t
ca
n
b
e
n
o
te
s
f
r
o
m
f
i
g
u
r
es
a
n
d
tab
les
th
a
t
t
h
e
s
ec
o
n
d
ar
y
co
n
tr
o
l
ac
tio
n
is
ef
f
ec
ti
n
g
o
n
th
e
r
esp
o
n
s
e
s
.
So
th
e
d
ec
r
ea
s
in
g
in
s
et
tli
n
g
ti
m
e
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
o
n
l
y
a
f
e
w
s
ec
o
n
d
s
s
p
ec
iall
y
co
m
p
ar
ed
w
it
h
P
SO
-
F
u
zz
y
co
n
tr
o
ller
.
8.
CO
NCLU
SI
O
N
On
e
o
f
t
h
e
m
ai
n
ch
al
len
g
es
in
au
to
m
atic
o
p
er
atio
n
m
u
l
ti
-
ar
ea
p
o
w
er
s
y
s
te
m
s
i
s
th
e
L
o
ad
Fre
q
u
en
c
y
C
o
n
tr
o
l
(
L
F
C
)
.
L
F
C
is
r
esp
o
n
s
ib
le
o
n
s
c
h
ed
u
led
p
o
w
er
ca
lib
r
atio
n
b
et
w
ee
n
t
h
e
m
u
lti
-
ar
ea
s
at
an
y
d
i
s
t
u
r
b
an
ce
s
.
S
u
c
h
as;
th
e
co
n
n
ec
ti
n
g
o
r
d
is
co
n
n
ec
ti
n
g
g
en
er
at
in
g
u
n
it
o
r
s
u
d
d
en
l
y
l
ar
g
e
in
cr
ea
s
in
g
d
em
in
d
.
I
n
th
i
s
w
o
r
k
,
t
h
e
p
r
o
p
o
s
ed
s
ca
led
f
u
zz
y
co
n
tr
o
ller
ex
a
m
in
e
s
o
n
t
w
o
ar
ea
s
p
o
w
er
s
y
s
te
m
u
s
in
g
P
SO,
SeP
SO
also
P
I
D.
T
h
ese
r
u
les
ar
e
o
b
tain
ed
b
ased
o
n
Ma
tlab
s
i
m
u
latio
n
o
f
f
r
eq
u
en
c
y
r
e
s
p
o
n
s
e,
er
r
o
r
s
ig
n
al
an
d
it
s
ti
m
e
ch
a
n
g
in
g
.
T
h
e
s
i
m
u
latio
n
r
e
s
u
lt
s
p
r
o
v
e
th
at
t
h
e
s
u
g
g
e
s
ted
co
n
tr
o
ller
h
as
o
b
tain
ed
a
h
ig
h
s
p
ee
d
o
f
r
esp
o
n
s
e
an
d
less
u
n
d
er
s
h
o
o
ts
w
it
h
r
e
s
p
ec
t
to
th
e
co
n
tr
o
lu
s
i
n
g
P
I
D,
an
d
P
SO
-
f
u
zz
y
co
n
tr
o
ller
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
p
r
il 2
0
1
9
:
8
1
5
-
8
2
5
824
RE
F
E
R
E
NC
E
S
[1
]
S
.
A
.
A
z
e
e
r,
e
t
a
l.
,
“
In
telli
g
e
n
t
C
o
n
tr
o
ll
e
rs
f
o
r
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tr
o
l
o
f
Tw
o
-
A
re
a
P
o
w
e
r
S
y
st
e
m
,
”
S
c
ien
c
e
Dire
c
t
,
v
o
l.
5
0
,
n
o
.
2
,
2
0
1
7
,
p
p
.
3
0
1
-
3
0
6
.
[2
]
A
q
e
e
l
S
.
Ja
b
e
r,
e
t
a
l.
,
“
A
d
v
a
n
c
e
T
wo
-
A
re
a
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tr
o
l
u
si
n
g
P
a
rti
c
le
S
w
a
r
m
O
p
ti
m
iz
a
ti
o
n
S
c
a
le
d
F
u
z
z
y
L
o
g
ic,”
Ad
v
.
M
a
ter
.
Res
.
,
v
o
l.
6
2
2
-
6
2
3
,
2
0
1
3,
p
p
.
8
0
-
8
5
,
2
0
1
3
.
[3
]
M
.
Na
jee
b
,
e
t
a
l.
,
“
A
n
Op
ti
m
a
l
L
F
C
in
Tw
o
-
A
re
a
P
o
w
e
r
S
y
s
tem
s
Us
in
g
a
M
e
ta
-
he
u
risti
c
O
p
ti
m
iza
ti
o
n
A
l
g
o
rit
h
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
Co
mp
u
ter
En
g
i
n
e
e
rin
g
,
v
o
l.
7
,
n
o
.
6
,
p
p
.
3
2
1
7
-
3
2
2
5
,
2
0
1
7
.
[4
]
T
.
P
.
Da
o
,
e
t
a
l.
,
“
No
v
e
l
H
y
b
ri
d
L
o
a
d
-
F
re
q
u
e
n
c
y
Co
n
tro
ll
e
r
Ap
p
ly
in
g
A
rti
f
i
c
ial
In
telli
g
e
n
c
e
T
e
c
h
n
iq
u
e
s
In
teg
ra
ted
w
it
h
S
u
p
e
rc
o
n
d
u
c
ti
n
g
M
a
g
n
e
ti
c
En
e
rg
y
S
to
ra
g
e
De
v
ice
s f
o
r
a
n
In
terc
o
n
n
e
c
ted
El
e
c
tri
c
P
o
w
e
r
G
r
id
,
”
Kin
g
F
a
h
d
U
n
iv
e
rsity
o
f
P
e
tro
leu
m
&
M
in
e
ra
ls
Jo
u
rn
a
l
2
0
1
5
.
[5
]
T
.
Wen
,
“
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tro
l:
P
r
o
b
lem
s
a
n
d
S
o
l
u
ti
o
n
s,”
Co
n
tro
l
Co
n
f.
(
CCC),
3
0
t
h
Ch
i
n
e
se
,
2
0
1
1
,
p
p
.
6
2
8
1
-
6
2
8
6
.
[6
]
A
q
e
e
l
S
.
Ja
b
e
r,
e
t
a
l.
,
“
A
n
e
w
I
m
p
ro
v
e
m
rn
t
o
f
Co
n
v
e
n
ti
o
n
a
l
P
I/
P
D
c
o
n
trl
lers
f
o
t
lo
a
d
f
re
q
u
e
n
c
y
c
o
n
tro
l
w
it
h
sc
a
led
f
u
z
z
y
c
o
n
tro
ll
e
r,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
A
p
p
li
e
d
S
c
ien
c
e
s
,
v
o
l.
2
,
n
o
.
4
,
2
0
1
5
,
p
p
.
6
9
-
7
4
.
[7
]
Ha
ss
a
n
F
a
rh
a
n
Ra
sh
a
g
,
e
t
a
l.
,
“
M
o
d
if
ied
Dire
c
t
T
o
rq
u
e
Co
n
tr
o
l
u
sin
g
A
lg
o
rit
h
m
Co
n
tro
l
o
f
S
tato
r
F
lu
x
Esti
m
a
ti
o
n
a
n
d
S
p
a
c
e
V
e
c
to
r
M
o
d
u
lati
o
n
Ba
se
d
o
n
F
u
z
z
y
L
o
g
ic
C
o
n
tr
o
l
f
o
r
A
c
h
iev
in
g
Hi
g
h
P
e
r
f
o
rm
a
n
c
e
f
ro
m
In
d
u
c
ti
o
n
M
o
to
rs,”
J
o
u
rn
a
l
o
f
P
o
we
r E
lec
tro
n
ics
,
v
o
l.
1
3
,
n
o
.
3
,
p.
3
6
9
,
2
0
1
3
.
[8
]
I.
K.
E.
Ca
m
,
“
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tr
o
l
In
T
w
o
A
r
e
a
P
o
w
e
r
S
y
ste
m
s
U
sin
g
F
u
z
z
y
L
o
g
ic
Co
n
tro
ll
e
r,
”
En
e
rg
y
Co
n
v
e
rs
.
M
a
n
a
g
.
v
o
l.
4
6
,
n
o
.
2
,
2
0
0
5
,
p
p
.
2
3
3
-
2
4
3
,
2
0
0
5
.
[9
]
K
M
a
n
ick
a
v
a
s
a
g
a
n
,
“
F
u
z
z
y
b
a
se
d
P
o
w
e
r
F
lo
w
c
o
n
tro
l
o
f
Tw
o
A
r
e
a
P
o
w
e
r
S
y
ste
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
2
,
n
o
.
1
,
p
p
.
1
3
0
-
1
3
6
,
2
0
1
2
.
[1
0
]
A
.
G
u
e
d
iri
a
n
d
D.
Be
n
A
tt
o
u
s,
“
M
o
d
e
li
n
g
a
n
d
Co
m
p
a
riso
n
o
f
Ip
a
n
d
F
u
z
z
y
-
P
i
Re
g
u
lato
rs
o
f
S
p
e
e
d
Co
n
tr
o
l
o
f
Df
i
m
f
o
r
S
u
p
p
ly
o
f
P
o
w
e
r
to
th
e
El
e
c
tri
c
a
l
Ne
t
w
o
rk
,
”
J
F
u
n
d
a
m
Ap
p
l
S
c
i.
,
v
o
l
.
1
0
,
n
o
.
1
,
2
0
1
8
,
pp.
1
8
1
-
1
9
0
.
[1
1
]
E.
A
.
H.
A
b
d
a
ll
a
,
e
t
a
l.
,
“
M
o
d
e
l
Be
h
a
v
io
ro
f
Co
o
li
n
g
P
lan
t
Us
in
g
S
u
b
trac
ti
v
e
Clu
ste
rin
g
A
n
f
is
A
t
Un
iv
e
rsit
y
Bu
il
d
i
n
g
s,”
J
Fu
n
d
a
m A
p
p
l
S
c
i.
,
v
o
l
.
1
0
,
n
o
.
3
S
,
p
p
.
6
6
5
-
6
7
9
,
2
0
1
8
.
[1
2
]
R.
F
a
rh
a
n
g
i,
e
t
a
l.
,
“
L
o
a
d
–
f
re
q
u
e
n
c
y
Co
n
tro
l
o
f
I
n
terc
o
n
n
e
c
ted
P
o
w
e
r
S
y
ste
m
u
sin
g
E
m
o
ti
o
n
a
l
L
e
a
rn
in
g
-
b
a
s
e
d
In
telli
g
e
n
t
Co
n
tr
o
ll
e
r
,”
P
o
we
r E
n
e
rg
y
S
y
st
.,
v
o
l.
3
6
,
n
o
.
1
,
p
p
.
7
6
-
8
3
,
2
0
1
2
.
[1
3
]
S
.
G
h
o
sh
a
l,
“
Op
ti
m
iza
ti
o
n
s
o
f
P
ID
G
a
in
s
b
y
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iza
ti
o
n
s
i
n
F
u
z
z
y
Ba
se
d
A
u
to
m
a
ti
c
G
e
n
e
r
a
ti
o
n
C
o
n
tr
o
l,
”
El
e
c
tr.
P
o
w
e
r S
y
st.
Res
.
,
v
o
l.
2
,
n
o
.
3
,
p
p
.
2
0
3
-
2
1
2
,
2
0
0
4
.
[1
4
]
S
a
y
e
d
M
o
jt
a
b
a
S
h
irv
a
n
i
Bo
r
o
u
j
e
n
i,
e
t
a
l
.
,
“
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tro
l
i
n
M
u
lt
i
A
re
a
El
e
c
tri
c
P
o
w
e
r
S
y
ste
m
Us
in
g
G
e
n
e
ti
c
S
c
a
led
F
u
z
z
y
L
o
g
ic,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
P
h
y
sic
a
l
S
c
ien
c
e
s
,
v
o
l.
6
,
n
o
.
3
,
p
p
.
3
7
7
-
3
8
5
,
2
0
1
1
.
[1
5
]
V
ik
ra
m
Ku
m
a
r
Ka
m
b
o
j,
e
t
a
l.
,
“
A
u
to
m
a
ti
c
G
e
n
e
ra
ti
o
n
C
o
n
tro
l
f
o
r
In
terc
o
n
n
e
c
ted
Hy
d
ro
-
th
e
rm
a
l
S
y
st
e
m
w
it
h
th
e
h
e
lp
o
f
Co
n
v
e
n
ti
o
n
a
l
Co
n
tr
o
ll
e
rs,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l
.
2
,
n
o
.
4
,
p
p
.
5
4
7
-
5
5
2
,
2
0
1
2
.
[1
6
]
R.
F
a
rh
a
n
g
i,
e
t
a
l.
,
“
L
o
a
d
–
f
re
q
u
e
n
c
y
C
o
n
tro
l
o
f
In
terc
o
n
n
e
c
ted
P
o
w
e
r
S
y
ste
m
u
sin
g
E
m
o
t
io
n
a
l
L
e
a
rn
in
g
-
b
a
s
e
d
In
telli
g
e
n
t
Co
n
tr
o
ll
e
r
,”
P
o
we
r E
n
e
rg
y
S
y
st
.,
v
o
l.
3
6
,
n
o
.
1
,
p
p
.
7
6
-
8
3
,
2
0
1
2
.
[1
7
]
A
.
M
.
A
b
d
e
l
G
h
a
n
y
,
“
De
si
g
n
o
f
S
tatic
Ou
tp
u
t
F
e
e
d
b
a
c
k
P
ID
Co
n
tro
ll
e
r
v
ia
IL
M
I
M
e
th
o
d
f
o
r
A
P
o
w
e
r
S
y
ste
m
S
tab
il
ize
r,
”
1
2
th
M
id
d
le E
a
st
Po
we
r S
y
ste
ms
Co
n
fer
e
n
c
e
,
2
0
0
8
,
p
p
.
5
9
3
-
5
9
9
.
[1
8
]
Ho
se
in
p
o
o
r,
e
t
a
l.
,
“
W
in
d
T
u
r
b
in
e
s
C
o
n
tr
o
ll
b
y
P
so
A
lg
o
rit
h
m
,
”
J
Fu
n
d
a
m
Ap
p
l
S
c
i
.
,
v
o
l.
8
,
n
o
.
2
S
,
p
p
.
3
6
3
8
-
3
6
4
6
,
2
0
1
6
.
[1
9
]
A
.
J
.
H.
S
h
a
y
e
g
h
i,
H.A
.
S
h
a
y
a
n
f
a
r,
“
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tro
l
S
t
ra
teg
ies
:
A
S
tate
-
of
-
th
e
-
A
rt
S
u
rv
e
y
f
o
r
th
e
Re
se
a
rc
h
e
r,
”
En
e
rg
y
Co
n
v
e
rs
.
M
a
n
a
g
.
S
c
i.
,
v
o
l.
5
0
,
n
o
.
2
,
p
p
.
3
4
4
-
3
5
3
,
2
0
0
9
.
[2
0
]
A
q
e
e
l
S
.
Ja
b
e
r,
e
t
a
l.
,
“
A
n
e
w
P
a
ra
m
e
t
e
rs
Id
e
n
ti
f
ica
ti
o
n
o
f
si
n
g
le
a
re
a
P
o
w
e
r
S
y
ste
m
b
a
se
d
L
F
C
u
sin
g
S
e
g
m
e
n
tatio
n
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iza
ti
o
n
(S
e
P
S
O)
A
lg
o
rit
h
m
,
”
Po
we
r
a
n
d
E
n
e
rg
y
En
g
i
n
e
e
rin
g
Co
n
fer
e
n
c
e
(
AP
PE
EC)
IEE
Asia
-
Pa
c
if
ic
,
2
0
1
3
,
p
p
.
1
-
6.
[2
1
]
M
o
u
e
ll
e
f
S
ih
e
m
,
e
t
a
l.
,
“
Op
ti
m
a
l
De
sig
n
o
f
S
w
it
c
h
e
d
Re
lu
c
tan
c
e
M
o
to
r
u
s
in
g
P
S
O
Ba
se
d
F
EM
-
EM
C
M
o
d
e
li
n
g
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
ter
En
g
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
5
,
n
o
.
5
,
2
0
1
5
,
p
p
.
4
2
7
-
4
3
2
,
2
0
1
5
.
[2
2
]
S
.
P
.
M
a
n
g
a
iy
a
r
k
a
ra
si
,
e
t
a
l.
,
“
Op
ti
m
a
l
L
o
c
a
ti
o
n
a
n
d
S
izi
n
g
o
f
M
u
lt
ip
le
S
tatic
V
A
r
Co
m
p
e
n
sa
to
rs
f
o
r
V
o
lt
a
g
e
Risk
As
se
s
s
m
e
n
t
Us
in
g
H
y
b
rid
P
S
O
-
G
S
A
A
l
g
o
rit
h
m
,
”
Kin
g
Fa
h
d
Un
ive
rs
it
y
o
f
Petro
leu
m
&
M
in
e
ra
l
s
J
o
u
rn
a
l
,
2
0
1
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.