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I
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s
te
m
p
er
f
o
r
m
a
n
ce
,
m
u
s
t
co
o
r
d
in
atio
n
a
m
o
n
g
P
SS
an
d
UP
FC
-
P
OD
tech
n
iq
u
es
u
til
ized
f
o
r
d
a
m
p
i
n
g
L
FO.
Un
co
o
r
d
in
ated
a
m
o
n
g
P
OD
an
d
P
SS
ca
u
s
ed
d
estab
ilizin
g
in
ter
ac
tio
n
s
an
d
th
er
ef
o
r
e,
u
n
s
tab
le
b
e
p
o
w
er
s
y
s
te
m
.
T
o
av
o
id
th
e
is
s
u
e
o
f
in
ter
ac
tio
n
s
,
a
co
o
r
d
in
ated
d
esig
n
is
u
s
ed
to
g
et
th
e
m
o
s
t
b
e
n
ef
its
o
f
m
u
lti
p
le
s
tab
ilizer
s
.
T
h
is
d
ec
r
ea
s
es
an
y
p
r
o
b
ab
le
n
eg
a
tiv
e
i
n
ter
ac
tio
n
s
a
m
o
ng
th
e
v
ar
io
u
s
-
s
tab
ilizer
s
a
n
d
i
n
cr
ea
s
es
s
y
s
te
m
s
tab
ilit
y
.
N
u
m
er
o
u
s
o
f
r
esear
c
h
es
h
a
v
e
b
ee
n
p
r
esen
ted
f
o
r
th
e
co
o
r
d
in
atio
n
a
m
o
n
g
P
SS
a
s
w
ell
as
F
AC
T
S
-
d
a
m
p
i
n
g
co
n
tr
o
ller
b
y
u
tili
zi
n
g
a
d
if
f
er
en
t
m
et
h
o
d
.
P
ar
am
eter
tu
n
in
g
i
s
t
h
e
k
e
y
p
r
o
b
le
m
i
n
th
e
co
o
r
d
in
at
ed
am
o
n
g
P
SS
an
d
UP
FC
-
P
OD
s
i
m
u
lta
n
eo
u
s
l
y
c
o
n
tr
o
ller
d
esig
n
f
o
r
u
s
e
f
u
l
d
a
m
p
in
g
.
T
h
e
u
tili
za
t
io
n
o
f
i
m
p
r
o
v
e
m
e
n
t
m
eth
o
d
s
f
o
r
f
ac
ilit
ated
co
n
f
i
g
u
r
atio
n
m
u
s
t
b
e
s
p
ee
d
y
,
p
r
o
d
u
ctiv
e.
A
cc
o
r
d
in
g
l
y
,
n
u
m
er
o
u
s
s
tr
ateg
ies
d
is
ti
n
ct
i
v
e
h
a
v
e
b
ee
n
u
t
ilized
to
g
iv
e
t
h
e
c
o
v
e
t
e
d
c
o
m
p
o
s
e
d
p
l
an
a
n
d
s
t
r
e
n
g
t
h
t
o
v
a
r
i
o
u
s
s
t
a
b
i
l
i
z
e
r
s
,
f
o
r
e
x
a
m
p
l
e
,
t
h
e
u
t
i
l
i
z
a
t
i
o
n
o
f
n
o
n
-
d
o
m
i
n
a
t
e
d
s
o
r
t
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
(
N
S
PS
O
)
[
8
]
,
f
u
z
z
y
l
o
g
i
c
[
9
]
a
n
d
c
h
a
o
t
i
c
o
p
t
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
(
C
O
A
)
[
10
].
I
n
th
i
s
p
ap
er
,
a
n
e
w
al
g
o
r
ith
m
u
s
e
o
f
a
g
lo
b
al
o
p
ti
m
al
s
ea
r
c
h
th
at
is
b
ased
o
n
e
c
h
o
lo
ca
tio
n
,
k
n
o
w
n
as
th
e
d
o
lp
h
i
n
ec
h
o
lo
ca
tio
n
o
p
tim
izatio
n
(
DE
O)
tec
h
n
iq
u
e.
T
h
e
DE
O
is
u
ti
lized
as a
n
o
p
ti
m
i
za
tio
n
to
o
l to
ad
j
u
s
t
th
e
d
a
m
p
in
g
p
ar
am
e
ter
s
f
o
r
in
d
ep
en
d
en
tl
y
an
d
d
u
al
d
a
m
p
in
g
co
n
tr
o
ller
s
d
esig
n
o
n
th
e
b
as
i
s
o
f
th
e
eig
en
v
al
u
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
.
E
m
u
latio
n
o
f
SMI
B
r
es
u
lts
p
r
ep
ar
ed
w
it
h
UP
FC
d
e
n
o
ted
th
at
th
e
d
u
al
s
i
m
u
lta
n
eo
u
s
co
o
r
d
in
atio
n
a
m
o
n
g
P
SS
&
UP
FC
b
ased
-
P
OD
h
ad
b
etter
an
d
f
aster
d
am
p
i
n
g
ca
p
ac
it
y
f
o
r
L
ess
i
n
g
L
FO
w
it
h
less
er
o
v
er
s
h
o
o
t
co
m
p
ar
ed
w
it
h
t
h
e
i
n
d
ep
en
d
en
t
d
esig
n
,
w
h
ic
h
i
m
p
r
o
v
ed
th
e
s
tab
ilit
y
o
f
SMI
B
s
y
s
te
m
p
o
in
ted
l
y
.
I
n
ad
d
itio
n
,
DE
O
h
as
g
i
v
e
n
th
e
b
etter
r
es
u
lt
s
i
n
i
n
d
iv
id
u
al
an
d
co
o
r
d
in
ated
d
es
ig
n
co
m
p
ar
ed
w
i
th
P
SO a
lg
o
r
ith
m
r
esu
lts
.
2.
M
O
DE
L
O
F
SM
I
B
WI
T
H
UP
F
C
Fig
u
r
e
1
s
h
o
w
s
a
SMI
B
f
itted
w
it
h
UP
FC
d
ev
ice
[
1
1
]
.
T
r
an
s
m
i
s
s
io
n
lin
e
an
d
UP
FC
ar
e
tr
an
s
f
er
r
in
g
elec
tr
ic
p
o
w
er
f
r
o
m
t
h
e
s
y
n
c
h
r
o
n
o
u
s
g
e
n
er
ato
r
to
th
e
in
f
i
n
it
e
b
u
s
.
T
h
e
UP
FC
f
o
r
m
ed
o
f
t
w
o
v
o
lta
g
e
s
o
u
r
ce
co
n
v
er
ter
s
(
VS
C
s
)
,
th
at
is
V
SC
1
an
d
VSC
2
w
h
ich
ar
e
co
u
p
lin
g
th
r
o
u
g
h
DC
li
n
k
ca
p
ac
ito
r
,
ex
citatio
n
tr
an
s
f
o
r
m
er
(
E
T
)
,
b
o
o
s
tin
g
t
r
an
s
f
o
r
m
er
(
B
T
)
an
d
co
n
tr
o
l
s
ig
n
a
ls
w
h
ich
ar
e
co
n
s
is
t
s
o
f
f
o
u
r
in
p
u
ts
to
th
e
UP
F
C
[
12
]
.
T
h
ese
f
o
u
r
in
p
u
t
co
n
tr
o
l
s
i
g
n
a
ls
ar
e
th
e
m
o
d
u
latio
n
a
m
p
lit
u
d
e
r
atio
(
mB
,
mE
)
an
d
c
o
n
tr
o
l
an
g
le
p
h
ase
r
atio
(
B
,
E
)
f
o
r
ev
er
y
v
o
ltag
e
s
o
u
r
ce
co
n
v
er
ter
.
DC
v
o
ltag
e
f
o
r
t
w
o
VS
C
s
i
s
p
r
o
v
i
d
in
g
v
ia
a
co
m
m
o
n
ca
p
ac
ito
r
b
an
k
to
m
ai
n
tai
n
ac
t
iv
e
p
o
w
er
b
alan
ce
b
et
w
ee
n
t
wo
v
o
ltag
e
co
n
v
er
ter
s
.
I
n
t
h
is
wo
r
k
,
mE
ch
an
n
el
i
s
m
o
d
u
lated
s
o
as
to
co
o
r
d
i
n
ate
d
d
esig
n
.
V
SC
1
is
i
n
s
er
t
i
n
p
ar
allel
w
it
h
th
e
lin
e
v
ia
a
n
(
E
T
)
an
d
h
a
v
e
t
w
o
in
p
u
t
co
n
tr
o
l
(
m
E
an
d
E)
w
h
ic
h
ar
e
u
s
ed
to
r
e
g
u
la
te
s
h
u
n
t
v
o
lta
g
e
an
d
D
C
-
lin
k
ca
p
ac
ito
r
v
o
ltag
e
r
esp
ec
tiv
el
y
.
VSC
2
is
attac
h
ed
to
th
e
co
n
v
ey
an
ce
li
n
e
in
s
er
ies
v
ia
an
(
B
T
)
an
d
h
av
e
t
w
o
in
p
u
t c
o
n
tr
o
l (
mB
an
d
B
)
w
h
ic
h
ar
e
u
tili
ze
d
f
o
r
co
n
tr
o
llin
g
ac
ti
v
e
in
ad
d
itio
n
to
r
ea
ctiv
e
p
o
w
e
r
o
n
th
e
tr
an
s
m
is
s
io
n
lin
e
r
esp
e
ctiv
el
y
.
T
h
ese
f
o
u
r
in
p
u
t
co
n
tr
o
l
s
ig
n
als
ar
e
u
tili
ze
d
f
o
r
p
r
o
v
id
in
g
s
y
n
c
h
r
o
n
iz
ed
p
o
w
er
co
m
p
en
s
atio
n
i
n
s
e
r
ies
l
in
e
d
ev
o
id
o
f
ex
ter
n
al
s
o
u
r
ce
o
f
v
o
lta
g
e
[1
3
]
.
T
h
e
s
y
s
te
m
p
ar
a
m
eter
s
ar
e
li
s
ted
in
A
p
p
en
d
ix
.
Fi
g
u
r
e
1
.
SMI
B
s
u
p
p
lied
w
it
h
UP
FC
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
Op
tima
l c
o
o
r
d
in
a
ted
d
esig
n
o
f
P
S
S
a
n
d
UP
F
C
−
P
OD
u
s
in
g
…
(
Oma
r
Mu
h
a
mme
d
N
ed
a
)
6113
2
.
1
.
No
n
-
lin
ea
r
dy
na
m
ic
f
o
r
m
o
f
UP
F
C
UP
FC
's
d
y
n
a
m
ic
p
er
f
o
r
m
an
ce
is
u
s
ed
a
s
a
o
n
e
w
a
y
to
ad
v
a
n
ce
t
h
e
p
o
w
er
s
y
s
te
m
's
s
i
g
n
al
s
tab
ilit
y
.
Via
n
eg
lec
ts
th
e
r
esi
s
tan
ce
as
w
ell
as
tr
an
s
ien
t
o
f
th
e
UP
FC
tr
an
s
f
o
r
m
er
s
(
i.e
.
ET
,
BT
)
an
d
ap
p
l
y
i
n
g
P
ar
k
’
s
tr
an
s
f
o
r
m
atio
n
th
e
UP
F
C
ca
n
b
e
m
o
d
eled
as f
o
llo
w
s
[
1
4
]:
[
td
tq
]
=
[
0
-
x
0
]
[
Ed
Eq
]
+
[
DC
cos
2
DC
s
in
2
]
(1
)
[
td
tq
]
=
[
0
-
x
0
]
[
Bd
Bq
]
+
[
DC
cos
2
DC
s
in
2
]
(2
)
DC
E
d
B
d
EB
E
E
B
B
E
q
B
q
D
C
D
C
33
44
d
dt
ii
mm
=
c
o
s
δ
s
i
n
δ
+
c
o
s
δ
s
i
n
δ
ii
CC
v
(3
)
w
h
e
r
e
,
V
E
,
X
E
a
n
d
i
E
a
r
e
v
o
l
ta
g
e
,
r
e
ac
t
an
c
e
an
d
cu
r
r
en
t
o
f
ex
c
it
a
t
i
o
n
r
es
p
e
c
ti
v
e
ly
.
V
B
,
X
B
a
n
d
i
B
a
r
e
v
o
lt
ag
e,
r
e
a
c
t
an
c
e
an
d
cu
r
r
en
t
o
f
b
o
o
s
t
in
g
r
e
s
p
e
ct
iv
e
ly
.
V
DC
an
d
C
DC
a
r
e
th
e
v
o
lt
a
g
e
an
d
c
a
p
a
c
it
an
c
e
o
f
DC
-
lin
k
.
2
.
2
.
SM
I
B
no
n
-
lin
ea
r
f
o
rm
I
n
(
4
)
,
(
5
)
,
(
6
)
,
an
d
(
7
)
r
ep
r
esen
t
s
th
e
n
o
n
-
li
n
ea
r
d
y
n
a
m
i
c
f
o
r
SMI
B
s
y
s
te
m
w
h
ic
h
p
r
esen
ted
in
Fig
u
r
e
1
[1
5
]:
̇
=
ω
(
−
1
)
(4
)
̇
=
1
(
−
−
(
-
1
)
)
(5
)
̇
′
=
1
′
do
(
fd
−
′
−
id
(
xd
−
′
)
)
(6
)
̇
fd
=
1
(
(
re
f
−
)
−
fd
)
(7
)
Fro
m
th
e
ab
o
v
e
eq
u
atio
n
s
,
:
is
th
e
an
g
le
o
f
r
o
to
r
,
an
d
:
ar
e
th
e
r
o
to
r
an
d
s
y
n
c
h
r
o
n
o
u
s
s
p
ee
d
,
:
is
th
e
i
n
p
u
t
m
ec
h
an
ical
p
o
w
er
,
:
is
o
u
tp
u
t
e
lectr
ical
p
o
w
er
,
D
a
n
d
M
:
ar
e
d
a
m
p
in
g
co
ef
f
icie
n
t
a
n
d
m
ac
h
i
n
e
in
er
tia,
E
,
̇
′
an
d
′
:
ar
e
th
e
g
en
er
ato
r
f
ield
,
i
n
ter
n
a
l
v
o
lta
g
e
o
f
g
e
n
er
ato
r
an
d
tr
a
n
s
ie
n
t
g
e
n
er
ato
r
,
r
esp
ec
tiv
el
y
,
T
׳
do
:
is
t
h
e
ti
m
e
co
n
s
tan
t
o
f
f
ield
cir
cu
it,
t
h
e
r
ef
er
en
ce
v
o
lta
g
e
is
Vr
e
f
.
Ka
,
Ta
:
ar
e
th
e
g
ain
a
n
d
ti
m
e
co
n
s
ta
n
t
o
f
e
x
citatio
n
s
y
s
te
m
,
r
esp
ec
ti
v
el
y
.
T
h
e
g
en
er
ato
r
o
u
tp
u
t
p
o
w
er
i
s
wr
itten
i
n
ter
m
s
o
f
th
e
q
-
a
x
is
a
s
w
ell
as d
-
a
x
i
s
co
m
p
o
n
en
ts
o
f
t
h
e
ar
m
a
tu
r
e
cu
r
r
en
t
,
an
d
ter
m
i
n
al
v
o
ltag
e
as:
e
t
d
d
t
q
q
P
=
v
i
+
v
i
(
8
)
2
.
3
.
L
inea
rize
d f
o
r
m
o
f
SM
I
B
w
i
t
h UP
F
C
T
h
e
m
o
d
el
o
f
lin
ea
r
d
y
n
a
m
i
c
b
y
lin
ea
r
izatio
n
o
f
n
o
n
−
lin
e
ar
m
o
d
el
f
o
r
th
e
o
p
er
atin
g
co
n
d
itio
n
.
Fig
u
r
e
1
illu
s
tr
ates t
h
e
lin
ea
r
iz
ed
m
o
d
el
o
f
t
h
e
p
o
w
er
s
y
s
te
m
as g
i
v
en
b
y
[
1
6
]:
̇
=
(
9
)
̇
=
1
(
−
−
)
(
1
0
)
̇
′
=
1
′
(
−
′
−
(
−
′
)
)
(
1
1
)
̇
=
1
(
−
−
)
(
1
2
)
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.
10
,
No
.
6
,
Dec
em
b
er
2
0
2
0
:
6
1
1
1
-
6
1
2
1
6114
w
h
er
e:
Δ
P
=K
1
Δδ
+K
2
Δ
E'
+Kp
d
Δ
vDC
+Kp
e
Δ
m
+K
p
δ
e
+Kp
b
Δ
m
+Kp
δ
b
(
1
3
)
Δ
E'
=K
4
Δδ
+K
3
Δ
E'
+Kq
d
Δ
vDC
+Kq
e
Δ
m
+Kq
δ
e
+Kq
b
Δ
m
+Kq
δ
b
(
1
4
)
Δ
v
=K
5
Δδ
+K
6
Δ
E'
+Kvd
Δ
vDC
+Kve
Δ
m
+Kv
δ
e
+Kvb
Δ
m
+Kv
δ
b
(
1
5
)
̇
dc
=K
7
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E
+K
8
Δ
E'
-
K
9
Δ
vDC
+Kce
Δ
m
+Kc
δ
e
+Kcb
Δ
m
+K
c
δ
b
(
16)
w
h
er
e
t
h
e
co
n
s
tan
t
s
K
1
to
K
9
,
pd
,
pe,
p
δ
e
,
pb
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pδ
b,
K
K
K
K
K
qd
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qe,
q
δ
e
,
qb
,
qδ
b,
K
K
K
K
K
v
d,
v
e
,
v
δe
,
v
b,
v
δb,
K
K
K
K
K
ce,
c
δ
e,
cb
K
K
K
an
d
c
δb
K
ar
e
f
u
n
ct
io
n
s
o
f
t
h
e
s
y
s
te
m
co
ef
f
ic
ien
t
s
an
d
th
e
in
itial
o
p
er
atin
g
co
ef
f
icien
ts
.
I
n
s
tate
−
s
p
ac
e
ex
e
m
p
li
f
icat
io
n
,
th
ese
eq
u
a
tio
n
s
m
a
y
b
e
ar
r
ay
e
d
in
co
n
cise
f
o
r
m
u
la
as:
̇
=
+
(
1
7
)
=
[
Δδ
Δω
Δ
E
′
Δ
E
fd
Δ
V
dc
]
,
Δ
U=
[
Δ
Ups
s
Δ
U
mE
Δ
U
δ
E
Δ
U
mB
Δ
U
δ
b
]
T
h
e
co
n
s
tr
u
ctio
n
o
f
th
e
m
atr
ic
es A
a
n
d
B
ar
e:
=
[
0
0
0
0
0
0
0
0
0
−
K1
−
−
K2
0
−
Kp
d
0
−
Kp
e
−
Kp
−
Kp
b
−
Kp
−
K4
T
'do
0
−
K3
T
'do
1
T
'do
−
Kq
d
T
'do
0
−
Kq
e
T
'do
−
Kq
T
'do
−
Kq
b
T
'do
−
Kq
T
'do
−
KA
K5
TA
0
−
KA
K6
TA
−
1
TA
−
KA
Kvd
TA
0
−
KA
Kve
TA
−
KA
Kvd
TA
−
KA
Kvb
TA
−
KA
Kv
TA
K7
0
K8
0
K9
0
Kc
e
Kc
Kc
b
Kc
-
Kdp
K7
0
-
Kdp
K8
0
−
(
Kdi
+
K9
Kdp
)
0
-
Kdp
Kc
e
-
Kdp
Kc
-
Kdp
Kc
b
-
Kdp
Kc
0
0
0
0
0
0
−
1
Ts1
0
0
0
0
0
0
0
0
Ks2
Ts2
0
−
1
Ts2
0
0
0
0
0
0
0
0
0
0
−
1
Ts3
0
0
0
0
0
0
0
0
0
0
−
1
Ts4
]
T
1
1
2
2
3
3
4
4
A
A
K
0
0
0
0
0
0
0
0
0
T
Ks
0
0
0
0
0
0
0
0
0
Ts
Ks
B=
0
0
0
0
0
0
0
0
0
Ts
Ks
0
0
0
0
0
0
0
0
0
Ts
Ks
0
0
0
0
0
0
0
0
0
Ts
2
.
4
.
E
ig
env
a
lues
(
λ)
o
f
t
he
s
y
s
t
em
w
it
ho
ut
co
ntr
o
ller
B
y
s
o
l
v
i
n
g
C
h
.
E
q
u
atio
n
|
−
|
=
0
u
ti
lizin
g
M
A
T
L
A
B
,
s
y
s
te
m
ei
g
en
v
al
u
e
s
ar
e
o
b
tain
ed
an
d
d
is
p
la
y
ed
in
T
ab
le
1
.
I
t
ca
n
b
e
d
ir
ec
tl
y
u
n
d
er
s
to
o
d
f
r
o
m
T
ab
l
e
1
th
at
th
e
p
er
f
o
r
m
an
ce
o
f
th
i
s
s
y
s
te
m
is
u
n
s
tab
l
e
d
u
e
to
th
e
ex
is
te
n
ce
o
f
t
w
o
p
o
s
itiv
e
d
a
m
p
ed
m
o
d
es
(
λ
3
)
an
d
(
λ
4
)
an
d
r
e
q
u
ir
es
a
s
u
p
p
lem
en
tar
y
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n
tr
o
ller
f
o
r
s
tab
ilit
y
.
T
ab
le
1
.
E
ig
en
v
al
u
es
(
λ
)
w
it
h
o
u
t c
o
n
tr
o
ller
Ei
g
e
n
v
a
l
u
e
s (
λ)
V
a
l
u
e
1
λ
-
1
8
.
2
6
8
1
+
0
.
0
0
0
0
i
2
λ
-
1
9
.
9
2
5
2
+
0
.
0
0
0
0
i
λ
3
&
λ
4
0
.
2
6
5
4
±
2
.
6
2
8
8
i
5
λ
-
2
.
4
4
2
5
+
0
.
0
0
0
0
i
λ
6
&
λ
7
-
0
.
0
8
0
6
±
0
.
1
8
2
9
i
λ
8,
λ
9
&
λ
10
-
2
0
.
0
0
0
0
+
0
.
0
0
0
0
i
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
Op
tima
l c
o
o
r
d
in
a
ted
d
esig
n
o
f
P
S
S
a
n
d
UP
F
C
−
P
OD
u
s
in
g
…
(
Oma
r
Mu
h
a
mme
d
N
ed
a
)
6115
3.
T
H
E
P
O
WE
R
F
L
O
W
CO
N
T
RO
L
L
I
N
G
DAM
P
I
NG
T
o
d
am
p
L
F
O
an
d
en
s
u
r
e
s
y
s
t
e
m
s
tab
ilit
y
,
au
x
iliar
y
co
n
tr
o
l
is
ad
o
p
ted
to
th
e
g
en
er
ato
r
s
ti
m
u
latio
n
i
n
th
e
m
o
d
el
o
f
f
lo
w
co
n
tr
o
ller
o
f
th
e
u
n
i
f
ied
p
o
w
er
–
d
a
m
p
i
n
g
co
n
tr
o
ller
o
f
p
o
w
er
o
s
cillati
o
n
.
T
h
e
f
o
u
r
co
n
tr
o
l
s
ig
n
al
co
e
f
f
icien
ts
f
o
r
t
h
e
u
n
i
f
ied
p
o
w
er
f
lo
w
co
n
tr
o
ller
)
mE
,
δ
E
,
mB
,
an
d
δ
B
)
b
e
ar
r
an
g
e
s
o
a
s
to
g
e
n
er
ate
s
u
itab
le
d
a
m
p
in
g
to
r
q
u
e
as d
is
p
lay
ed
i
n
Fi
g
u
r
e
2
.
I
n
th
i
s
w
o
r
k
,
u
s
ed
o
n
e
co
n
tr
o
l si
g
n
al
p
ar
am
eter
is
e
x
citat
io
n
a
m
p
lit
u
d
e
m
o
d
u
lat
io
n
r
atio
(
i.e
.
mE
)
s
o
as
to
g
en
er
ate
th
e
p
r
o
p
er
d
am
p
i
n
g
a
n
d
f
o
r
d
u
al
-
co
o
r
d
in
atio
n
d
esig
n
[
1
7
]
.
P
OD
co
n
tr
o
ller
is
lik
e
P
S
S
as
d
i
s
p
la
y
ed
i
n
Fig
u
r
e
3
.
W
h
er
e
m
ad
o
f
m
ai
n
b
lo
c
k
s
o
f
t
h
r
ee
i
n
p
u
t
s
,
g
ain
,
a
w
a
s
h
o
u
t a
n
d
p
h
a
s
e
co
m
p
e
n
s
ato
r
s
.
Fig
u
r
e
2
.
UP
FC
-
P
OD
co
n
tr
o
ll
er
Fig
u
r
e
3
.
B
lo
ck
d
iag
r
a
m
o
f
P
S
S o
r
P
OD
co
n
tr
o
ller
T
h
e
g
ain
b
lo
ck
u
s
e
f
o
r
d
eter
m
i
n
in
g
t
h
e
a
m
o
u
n
t
o
f
d
a
m
p
i
n
g
t
h
e
r
es
u
lti
n
g
f
r
o
m
th
e
P
S
S
.
T
h
e
h
i
g
h
p
as
s
f
ilter
is
s
h
o
w
n
as t
h
e
w
as
h
o
u
t
b
lo
ck
u
s
i
n
g
to
r
e
m
o
v
e
t
h
e
DC
o
f
f
s
et
o
f
th
e
P
SS
o
r
P
OD
o
u
tp
u
t a
n
d
f
u
r
th
er
m
o
r
e
av
o
id
s
th
e
ch
a
n
g
e
o
f
s
tead
y
-
s
tate
s
ig
n
al
an
d
th
e
p
h
a
s
e
co
m
p
e
n
s
ato
r
b
lo
c
k
is
u
s
ed
to
s
u
p
p
l
y
ap
p
r
o
p
r
iate
p
h
ase
-
lead
ch
ar
ac
ter
is
tic
f
o
r
co
m
p
e
n
s
at
in
g
th
e
p
h
a
s
e
lag
a
m
o
n
g
th
e
g
en
er
ato
r
elec
tr
ical
to
r
q
u
e
in
ad
d
itio
n
to
th
e
ex
citer
in
p
u
t.
T
h
e
W
ash
o
u
t T
im
e
(
Tw
)
m
u
s
t
h
av
e
a
v
alu
e
in
th
e
ch
o
ice
o
f
(
1
−
2
0
s
.
)
.
T
w
eq
u
al
to
(
1
0
s
ec
)
,
w
h
ic
h
ar
e
tak
e
n
i
n
th
e
p
r
ese
n
t
s
tu
d
y
.
T
h
e
P
OD
p
ar
a
m
eter
s
ar
e
K
PS
S
,
T
1
,
T
2
,
T
3
an
d
T
4
,
to
b
e
ca
lcu
lated
.
Sp
ee
d
d
ev
iatio
n
(
Δ
)
is
th
e
P
OD
in
p
u
t
s
ig
n
al
a
n
d
is
th
e
o
u
tp
u
t
o
f
th
e
co
n
tr
o
ller
,
w
h
er
e
K
PS
S
=
PS
S
an
d
/o
r
mE
co
n
tr
o
ller
s
,
i=1
,
2
,
3
,
4
[
1
8
].
4.
O
B
J
E
CT
I
V
E
F
UNC
T
I
O
N
T
h
e
m
ai
n
tar
g
et
o
f
th
e
tec
h
n
i
q
u
e
b
ased
o
n
o
p
tim
izatio
n
to
en
h
a
n
ce
th
e
p
o
w
er
s
y
s
te
m
s
tab
ilit
y
to
d
is
o
r
d
er
s
at
m
is
ce
l
lan
eo
u
s
co
n
d
itio
n
s
o
f
lo
ad
in
g
.
I
t
b
e
r
ea
ch
ed
b
y
tu
n
in
g
d
a
m
p
i
n
g
o
f
t
h
e
co
n
tr
o
ller
p
ar
am
eter
s
.
T
h
e
P
OD
is
a
lead
−
lag
t
y
p
e
co
n
tr
o
ller
w
h
ic
h
ca
n
b
e
p
r
esen
ted
as
:
U(
s
)
=
G(
s
)
Y(
s
)
(
1
8
)
w
h
er
e:
G(
s
)
,
Y(
s
)
&
U(
s
)
ar
e
th
e
tr
an
s
f
er
f
u
n
ctio
n
,
i
n
p
u
t
s
i
g
n
al
a
n
d
o
u
tp
u
t
s
i
g
n
al
o
f
P
OD
co
n
tr
o
ller
,
r
esp
ec
tiv
el
y
.
I
n
s
tate
-
s
p
ac
e
m
o
d
e,
in
(
1
8
)
ca
n
b
e
p
r
esen
ted
as:
X˙
C
=
A
C
∆X
C
+B
C
∆U
(
19
)
w
h
er
e
:
Δ
XC
is
s
ta
te
v
ec
to
r
o
f
th
e
co
n
tr
o
ller
.
B
y
m
er
g
i
n
g
E
q
.
(
1
7
&
1
9
)
,
th
e
clo
s
ed
lo
o
p
s
y
s
te
m
ca
n
b
e
ac
h
iev
ed
.
Δ
X˙
Cl
= A
Cl
(
20
)
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.
10
,
No
.
6
,
Dec
em
b
er
2
0
2
0
:
6
1
1
1
-
6
1
2
1
6116
=
[
]
(
21
)
=
−
R
e
a
l
(
)
|
|
(
22
)
T
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
i
s
:
=
M
in
.
(
)
(
23
)
Her
e,
is
t
h
e
v
ec
to
r
s
tate,
is
th
e
co
e
f
f
icien
t
o
f
d
a
m
p
in
g
o
f
th
e
i
th
ei
g
e
n
v
al
u
e
a
n
d
is
th
e
i
th
eig
e
n
v
al
u
e
o
f
th
e
m
a
t
r
ix
o
f
clo
s
ed
lo
o
p
s
y
s
te
m
.
I
t
is
n
o
ticed
th
at
o
b
j
ec
tiv
e
f
u
n
ctio
n
J
ca
lcu
late
s
th
e
m
i
n
i
m
u
m
v
al
u
e
o
f
b
et
w
ee
n
w
h
o
l
l
y
s
y
s
te
m
m
o
d
es
(
)
.
T
h
e
tar
g
et
p
r
o
ce
s
s
o
f
o
p
ti
m
izatio
n
is
ap
p
lied
f
o
r
m
ax
i
m
izin
g
J
v
al
u
e
s
o
as
to
a
cc
o
m
p
li
s
h
a
s
u
itab
le
d
a
m
p
in
g
f
o
r
w
h
o
ll
y
m
o
d
es
co
n
ta
in
i
n
g
elec
tr
o
m
ec
h
a
n
ical
m
o
d
e,
an
d
m
ax
i
m
u
m
J
is
e
x
a
m
i
n
ed
w
i
th
i
n
t
h
e
r
estricte
d
ch
o
ice
o
f
P
OD
co
n
tr
o
ller
p
ar
am
eter
s
as:
R
min
≤
R
≤
R
m
ax
,
R
min
≤
R
≤
R
m
a
x
,
RI
m
in
≤
RI
≤
RI
m
ax
R
=
P
SS
,
mE
-
POD
(
i.e
.
UP
FC
-
P
OD)
,
i =
1
,
3
,
an
d
I
=
2
,
4
.
T
y
p
ical
r
an
g
e
s
o
f
K
R
i
s
(
0
.
0
1
–
1
0
0
)
,
R
is
(
0
.
0
0
1
–
1
)
an
d
T
RI
is
(
0
.
0
0
1
–
0
.
1
)
.
5.
O
P
T
I
M
I
Z
AT
I
O
N
T
E
CH
NI
Q
U
E
S
T
h
e
m
ai
n
tar
g
et
o
f
o
p
tim
iz
atio
n
alg
o
r
ith
m
is
to
d
eter
m
i
n
e
o
p
tim
a
l
p
ar
am
eter
s
v
alu
e
o
f
b
o
th
in
d
ep
en
d
en
t
co
n
tr
o
ller
s
(
P
SS
o
n
l
y
)
o
r
(
UP
FC
-
P
OD
o
n
l
y
)
an
d
s
i
m
u
lta
n
eo
u
s
co
o
r
d
in
ated
d
esig
n
s
a
m
o
n
g
(
P
SS
an
d
UP
FC
-
P
OD)
to
e
n
h
a
n
ce
s
y
s
te
m
o
s
cillatio
n
s
d
a
m
p
in
g
an
d
d
y
n
a
m
ic
s
tab
ili
t
y
p
er
f
o
r
m
an
ce
f
o
r
a
SMI
B
.
I
n
th
is
s
t
u
d
y
,
DE
O
a
n
d
P
SO a
lg
o
r
ith
m
s
ar
e
u
tili
ze
d
f
o
r
s
o
lv
in
g
t
h
e
d
escr
ib
ed
p
r
o
b
le
m
.
5
.
1
.
(
)
a
lg
o
rit
h
m
I
t
is
f
ir
s
t
in
tr
o
d
u
ce
d
an
d
d
ev
elo
p
ed
b
y
E
b
er
h
ar
t
an
d
Ken
n
ed
y
in
y
ea
r
1
9
9
5
[
19
]
.
T
h
e
b
eh
av
io
r
o
f
s
w
ar
m
s
o
f
b
ir
d
s
,
ea
ch
n
o
m
i
n
e
e
s
o
lu
tio
n
to
t
h
e
o
p
ti
m
iza
tio
n
p
r
o
b
lem
w
as r
ep
r
esen
ted
r
an
d
o
m
l
y
a
s
a
“
p
ar
ticle”
in
t
h
e
id
e
n
tit
y
D
-
d
i
m
e
n
s
io
n
s
p
ac
e,
an
d
ea
ch
g
r
o
u
p
o
f
p
ar
tic
les
co
n
ta
in
s
a
“
p
o
p
u
latio
n
”
[
2
0
,
2
1
]
.
T
h
e
p
o
s
itio
n
ar
r
an
g
ed
f
o
r
ea
c
h
p
ar
t
icle
i
n
a
h
y
p
er
s
p
ac
e
i
s
s
to
ck
ed
i
n
a
m
e
m
o
r
y
n
a
m
ed
“
p
b
est”,
w
h
ic
h
is
i
n
li
n
k
to
f
itted
s
o
lu
tio
n
in
ea
ch
e
x
p
er
ien
ce
.
F
u
r
th
er
m
o
r
e,
t
h
e
lo
ca
tio
n
ar
r
an
g
ed
to
th
e
b
est
v
al
u
e
u
p
to
n
o
w
a
m
o
n
g
s
t
en
tire
l
y
th
e
p
o
p
u
lated
p
ar
ticles
i
n
t
h
e
m
e
m
o
r
y
t
h
at
i
s
d
en
o
ted
as
“g
b
est”.
T
h
e
“
p
b
est”
a
n
d
“g
b
est
”
ch
an
g
ed
f
o
r
ev
er
y
iter
atio
n
o
f
t
h
e
P
SO
al
g
o
r
it
h
m
,
a
n
d
ev
er
y
v
elo
cit
y
o
f
t
h
e
p
ar
ticle
is
c
h
a
n
g
ed
to
w
ar
d
s
th
e
m
r
an
d
o
m
l
y
.
T
h
e
v
elo
cit
y
an
d
p
o
s
itio
n
o
f
e
ac
h
ag
e
n
t a
r
e
[
2
2
]
:
ν
i
k
+
1
=
w
.
ν
i
k
+
c
1
.r
1
.
(
p
b
esti
-
si
k
)
+
c
2
.r
2
.
(
g
b
esti
-
si
k
)
(
24
)
S
i
k+
1
= S
i
k
+
ν
i
k
+
1
(
25
)
w
h
er
e,
S
is
th
e
p
o
s
it
io
n
o
f
a
g
en
t,
ν
is
t
h
e
v
elo
cit
y
,
k
i
s
th
e
i
ter
atio
n
s
n
u
m
b
er
,
w
d
ep
icts
t
h
e
w
ei
g
h
t,
c
1
,
c
2
ar
e
th
e
co
g
n
iti
v
e
a
n
d
aso
cial
p
o
s
iti
v
e
co
n
s
tan
ts
t
h
at
u
tili
ze
to
p
u
ll
ev
er
y
i
n
d
i
v
id
u
al
o
n
t
h
e
w
a
y
to
p
o
s
itio
n
a
n
d
p
o
s
itio
n
w
ith
in
r
an
g
e
[
0
to
2
.
05
]
an
d
r
1
,
r
2
ar
e
th
e
t
w
o
r
an
d
o
m
n
u
m
b
er
s
w
i
th
i
n
li
m
it [
0
to
1
]
.
5
.
2
.
(
DE
O
)
a
lg
o
rit
h
m
Kav
e
h
an
d
Far
h
o
u
d
i
h
a
v
e
b
e
en
d
ev
elo
p
ed
an
d
en
h
an
ce
d
a
n
e
w
tec
h
n
iq
u
e
o
f
o
p
ti
m
izat
io
n
ca
lled
th
e
Do
lp
h
i
n
ec
h
o
lo
ca
tio
n
o
p
ti
m
izat
io
n
(
DE
O)
m
eth
o
d
i
n
y
ea
r
2
0
1
3
[
2
3
]
.
Do
lp
h
in
s
ca
n
d
is
co
v
er
t
h
eir
en
v
ir
o
n
m
e
n
t
b
y
u
s
i
n
g
th
e
b
e
n
ef
its
o
f
ec
h
o
lo
ca
tio
n
.
T
h
e
b
asic
id
ea
o
f
DE
O
alg
o
r
ith
m
co
m
e
f
r
o
m
m
i
m
ic
k
i
n
g
th
e
b
eh
a
v
io
r
o
f
Do
lp
h
in
s
w
h
e
n
h
u
n
tin
g
.
T
h
e
Do
lp
h
in
ca
n
g
i
f
t
s
o
u
n
d
in
t
h
e
t
y
p
e
o
f
a
tap
in
d
if
f
er
e
n
t
lo
ca
tio
n
s
an
d
as
s
o
o
n
a
s
t
h
is
s
o
u
n
d
h
it
s
s
o
m
et
h
i
n
g
,
m
a
n
y
o
f
t
h
e
s
o
u
n
d
p
o
w
er
is
r
et
u
r
n
b
ac
k
to
w
ar
d
s
th
e
Do
lp
h
i
n
s
u
c
h
as
ec
h
o
es.
So
,
th
e
Do
lp
h
i
n
is
lis
te
n
in
g
to
th
e
m
an
d
n
o
w
w
a
n
ts
to
m
ak
e
a
ch
o
ice.
D
o
lp
h
in
r
ec
o
g
n
izes
a
d
is
tan
ce
to
th
e
b
aits
an
d
w
h
er
e
th
e
y
ar
e.
T
r
ac
in
g
s
tag
e
is
b
eg
u
n
an
d
Do
lp
h
i
n
m
o
v
e
to
b
ait,
co
n
tin
u
e
s
e
n
d
in
g
s
o
u
n
d
i
n
ad
d
itio
n
to
r
ec
eiv
in
g
ec
h
o
es
u
n
t
il
Do
lp
h
i
n
ac
ce
s
s
t
h
e
p
r
ey
s
.
Du
r
i
n
g
t
h
is
ap
p
r
o
ac
h
,
th
e
p
r
o
b
ab
ilit
y
o
f
th
e
h
u
n
ti
n
g
in
cr
ea
s
es
e
v
er
y
t
i
m
e
a
n
d
s
ea
r
ch
s
p
ac
e
r
ed
u
ce
d
co
n
tin
u
o
u
s
l
y
.
W
h
en
d
o
lp
h
in
r
ec
eiv
ed
ec
h
o
es
f
r
o
m
d
if
f
er
e
n
t
lo
ca
tio
n
s
,
at
t
h
is
ti
m
e
th
e
Do
lp
h
i
n
ca
n
p
r
o
ce
s
s
an
d
ev
alu
ate
t
h
i
s
i
n
f
o
r
m
a
tio
n
a
n
d
d
ec
id
e
to
s
elec
t
th
e
n
e
x
t s
tep
,
w
h
ic
h
is
a
v
er
y
ess
e
n
tial step
[
2
4
]
.
Fig
u
r
e
4
s
h
o
w
s
t
h
e
p
r
o
ce
s
s
o
f
DE
O
al
g
o
r
ith
m
.
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
Op
tima
l c
o
o
r
d
in
a
ted
d
esig
n
o
f
P
S
S
a
n
d
UP
F
C
−
P
OD
u
s
in
g
…
(
Oma
r
Mu
h
a
mme
d
N
ed
a
)
6117
Fig
u
r
e
4
.
R
ea
l D
o
lp
h
in
ca
tc
h
i
n
g
it
s
v
icti
m
5
.
2
.
1
.
M
a
t
he
m
a
t
ica
l f
o
r
m
ula
t
io
n o
f
t
he
DE
O
a
lg
o
ri
t
h
m
T
h
e
ty
p
ical
f
lo
w
c
h
ar
t
o
f
DE
O
tech
n
iq
u
e
i
s
p
r
esen
ted
in
Fig
u
r
e
5
an
d
th
e
s
tep
s
o
f
th
e
tu
n
i
n
g
p
r
o
ce
s
s
ar
e
[
2
5
]
:
Step
1
:
I
n
itializatio
n
C
h
o
o
s
e
t
h
e
m
ax
i
m
u
m
n
u
m
b
er
o
f
lo
o
p
s
N,
n
u
m
b
er
o
f
lo
ca
tio
n
s
N
L
r
an
d
o
m
l
y
a
n
d
n
u
m
b
er
o
f
v
ar
iab
les
NV
w
h
ich
ar
e
(
K
R
,
T
Ri
an
d
T
RI
)
in
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
(
i.e
.
P
SS
o
r
UP
FC
-
P
OD)
.
T
h
is
s
tep
en
clo
s
e
cr
ea
tin
g
L
N
L
+N
V
m
atr
i
x
.
Ma
x
i
m
u
m
alter
n
ati
v
e
n
u
m
b
er
M
A
in
t
h
e
s
ea
r
ch
s
p
ac
e
to
cr
ea
tin
g
alter
n
ati
v
e
m
a
tr
ix
w
i
th
d
i
m
en
s
io
n
[
M
A
×N
V]
.
Step
2
: CF
f
i
n
d
i
n
g
a
n
d
p
r
ed
ef
in
in
g
C
o
m
p
u
te
th
e
P
P
o
f
th
e
lo
o
p
u
tili
zin
g
f
o
llo
w
in
g
eq
u
atio
n
:
PP
(
L
oop
i
)
=
PP
1
+
(
1
−
PP
1
)
−
1
(
)
−
1
(
26
)
w
h
er
e,
P
P
is
th
e
p
r
o
b
ab
ilit
y
,
P
P
1
=
0
.
1
is
th
e
f
ir
s
t
lo
o
p
C
o
n
v
e
r
g
en
ce
Facto
r
(
C
F)
w
h
er
e
t
h
e
r
esu
lt
s
ar
e
r
an
d
o
m
l
y
ch
o
s
en
,
L
o
o
p
i
n
u
m
b
er
o
f
th
e
lo
o
p
in
w
h
ic
h
o
p
ti
m
izatio
n
p
r
o
ce
s
s
is
p
er
f
o
r
m
in
g
as
w
ell
as
p
o
w
er
is
d
eg
r
ee
o
f
th
e
cu
r
v
e.
P
o
w
er
<
1
w
h
ich
g
e
n
er
all
y
o
f
f
er
s
b
est r
esu
l
ts
.
Step
3
:
Fi
tn
es
s
ca
lcu
latio
n
I
n
th
i
s
w
o
r
k
,
th
e
s
u
g
g
ested
o
b
jectiv
e
f
u
n
ctio
n
f
o
r
th
e
co
n
tr
o
ll
er
h
as b
ee
n
ca
lcu
lated
as f
o
llo
w
i
n
g
:
J
=
Min
.
(
)
: O
b
j
ec
tiv
e
f
u
n
ctio
n
Ma
x
.
(
J
)
: Fitn
e
s
s
f
u
n
ctio
n
Step
4
: Fitn
es
s
ac
cu
m
u
lated
(
F
A
)
C
alc
u
latio
n
C
o
m
p
u
te
F
A
a
n
d
f
i
n
d
L
(
i,j
)
in
j
th
co
lu
m
n
p
o
s
it
io
n
o
f
th
e
m
atr
ic
o
f
alter
n
ati
v
es
d
en
o
ted
as
A
.
X
=
−
Re
to
Re
AF
(A+
X)j
=
(
1
/R
e)
*
(
R
e
-
|
X
|
)
Fi
tn
es
s
(
i)
+
A
F
(
A+
Xij)j
(
27
)
Fro
m
th
e
ab
o
v
e
eq
u
atio
n
:
A
F
(A+
X)
j
:
is
t
h
e
A
cc
u
m
u
lati
v
e
Fi
t
n
es
s
o
f
th
e
(
A
+X
)
.
R
e
d
ep
icts
th
e
af
f
ec
ted
r
ad
iu
s
w
h
er
e
A
F
o
f
t
h
e
alter
n
ati
v
e
A’
s
n
ei
g
h
b
o
u
r
s
i
s
i
n
f
l
u
e
n
ce
d
f
o
r
th
eir
f
it
n
ess
th
e
n
ca
lc
u
late
s
t
h
e
A
F
f
o
r
e
v
er
y
j
th
v
ar
iab
le
in
L
(
i,j
)
lo
ca
tio
n
b
y
u
tili
zi
n
g
t
h
e
Do
lp
h
in
eq
u
atio
n
g
i
v
en
i
n
eq
.
3
0
.
T
h
is
r
ad
iu
s
w
a
s
c
h
o
s
en
as
b
ei
n
g
less
th
a
t
1
/
4
o
f
th
e
s
ea
r
ch
s
p
ac
e
s
i
ze
.
I
t
is
w
o
r
th
t
h
at
th
e
clo
s
e
ag
e
alter
n
ati
v
es
(
A
+
X
<
0
o
r
A
+
X
>
L
A
j
,
w
h
er
e
A
+
X
is
n
o
t a
v
a
lid
)
,
th
e
ca
lcu
latio
n
o
f
A
F
is
p
er
f
o
r
m
ed
b
y
u
s
i
n
g
a
r
ef
lecti
v
e
c
h
ar
ac
ter
is
tic.
I
n
o
r
d
er
to
h
an
d
o
u
t
t
h
e
s
ea
r
ch
s
p
ac
e
alter
n
ativ
e,
a
s
m
all
a
m
o
u
n
t
o
f
is
ap
p
lied
to
th
e
w
h
o
ll
y
g
r
o
u
p
s
as
AF
=
A
F
+
.
No
w
,
is
b
etter
to
b
e
less
th
a
n
an
y
p
o
s
s
ib
le
f
itn
e
s
s
.
Step
5
: Fin
d
in
g
b
est lo
ca
tio
n
F
i
n
d
t
h
e
b
e
s
t
l
o
c
a
t
i
o
n
,
w
h
e
r
e
w
il
l
h
a
v
e
f
i
n
e
s
t
A
F
a
n
d
l
e
t
A
F
f
o
r
f
i
n
e
s
t
l
o
c
a
t
i
o
n
a
l
t
e
r
n
a
t
i
v
e
e
q
u
a
l
z
e
r
o
.
Step
6
:
Dete
r
m
in
a
tio
n
o
f
p
r
o
b
ab
ilit
y
as
w
el
l a
s
allo
ca
tio
n
C
alcu
late
th
e
p
r
o
b
ab
ilit
y
P
(
i,j)
as f
o
llo
w
in
g
:
P
(
i,
j
)
=
A
F
i
j
∑
A
F
i
j
LAj
i
=
1
(
28
)
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.
10
,
No
.
6
,
Dec
em
b
er
2
0
2
0
:
6
1
1
1
-
6
1
2
1
6118
L
et
p
r
o
b
ab
ilit
y
eq
u
al
to
:
P
(
i,
j
)
=
PP
f
o
r
w
h
o
ll
y
v
ar
iab
l
es o
f
th
e
f
i
n
est p
o
s
itio
n
.
P
(
i,
j
)
=
(
1
-
PP
loopi
)
.
P(i,
j)
else.
Step
7
:
Select
lo
ca
tio
n
o
f
th
e
n
ex
t lo
o
p
Mo
d
if
y
t
h
e
lo
ca
tio
n
s
o
f
th
e
n
e
x
t lo
o
p
ac
co
r
d
in
g
to
allo
ca
ted
p
r
o
b
a
b
ilit
y
o
f
it
s
alter
n
ati
v
e.
Step
8
: Reiter
atio
n
T
h
e
u
lti
m
ate
cr
iter
io
n
o
f
ter
m
i
n
atio
n
is
ac
h
ie
v
ed
o
r
o
n
ce
th
e
v
alu
e
o
f
J
is
m
a
x
i
m
u
m
,
if
y
es
s
to
p
th
e
o
p
ti
m
izatio
n
a
n
d
p
r
in
t
th
e
b
est
r
esu
l
ts
;
o
t
h
er
w
is
e,
r
ep
ea
t step
s
2
to
7
.
T
h
e
u
s
er
-
p
r
o
v
id
ed
p
ar
am
eter
s
f
o
r
t
h
e
DE
O
an
d
P
SO a
lg
o
r
ith
m
s
ar
e
tab
u
lated
in
T
ab
le
2
.
Fig
u
r
e
5
.
Flo
w
c
h
ar
t o
f
t
h
e
DE
O
alg
o
r
ith
m
T
ab
le
2
.
A
lg
o
r
ith
m
s
p
r
o
p
er
p
a
r
a
m
eter
s
PSO
D
EO
N
(
N
o
.
o
f
sw
a
r
ms)
30
N
L
(
N
o
.
o
f
l
o
c
a
t
i
o
n
)
30
V
a
r
i
a
b
l
e
s
5
V
a
r
i
a
b
l
e
s
5
c
1
,
c
2
2
N
a
l
t
.
90
w
0
.
3
L
o
o
p
s No
.
50
I
t
e
r
a
t
i
o
n
50
6.
SI
M
UL
AT
I
O
N
S RE
SU
L
T
S
I
n
th
i
s
s
ec
tio
n
,
t
h
e
ca
p
ab
ilit
ie
s
o
f
t
h
e
p
r
esen
ted
d
u
al
a
n
d
m
u
ltip
le
co
o
r
d
in
ated
d
esig
n
s
ar
e
ev
al
u
ated
to
i
m
p
r
o
v
e
th
e
s
y
s
te
m
's
d
y
n
a
m
ic
s
tab
il
it
y
b
y
d
a
m
p
i
n
g
t
h
e
L
FO.
Fig
u
r
e
6
s
h
o
w
s
t
h
e
s
p
ee
d
d
ev
iatio
n
r
esp
o
n
s
e
w
it
h
o
u
t
an
y
co
n
tr
o
ller
is
n
o
t
s
tab
le
w
it
h
o
u
t
a
n
y
co
n
tr
o
ller
an
d
th
er
e
is
i
n
cr
ea
s
i
n
g
o
f
th
e
o
s
cillatio
n
s
.
So
as
to
o
b
tain
th
e
o
p
ti
m
al
r
esp
o
n
s
e
o
f
th
e
P
SS
&
P
OD
co
n
tr
o
ller
,
u
s
e
th
e
DE
O
alg
o
r
it
h
m
a
n
d
it
is
co
m
p
ar
ed
w
it
h
P
SO.
T
h
e
f
in
al
v
alu
e
s
o
f
o
p
ti
m
ized
p
ar
am
eter
s
an
d
d
a
m
p
i
n
g
r
atio
(
ζ
)
ar
e
g
iv
es i
n
T
ab
le
3
.
Fig
u
r
e
7
d
is
p
la
y
s
SMI
B
's
r
esp
o
n
s
e
to
s
p
ee
d
d
ev
iatio
n
with
t
h
e
tr
ad
itio
n
al
i
n
d
i
v
id
u
al
co
n
tr
o
ller
(
i.e
.
P
SS
o
n
ly
)
.
I
t c
an
b
e
s
ee
n
th
at
P
SS
co
n
tr
o
ller
h
as e
f
f
ec
ti
v
e
d
a
m
p
in
g
t
h
e
s
y
s
te
m
o
s
cilla
tio
n
s
b
y
u
s
i
n
g
DE
O
alg
o
r
ith
m
co
m
p
ar
ed
to
th
e
PS
O.
W
h
er
e
th
e
s
p
e
ed
d
ev
iatio
n
r
esp
o
n
s
es
v
i
a
u
s
i
n
g
DE
O
alg
o
r
ith
m
s
h
o
w
t
h
at
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
Op
tima
l c
o
o
r
d
in
a
ted
d
esig
n
o
f
P
S
S
a
n
d
UP
F
C
−
P
OD
u
s
in
g
…
(
Oma
r
Mu
h
a
mme
d
N
ed
a
)
6119
th
e
p
ar
a
m
eter
s
i
m
p
r
o
v
ed
an
d
th
e
y
ar
e
h
i
g
h
er
th
a
n
s
ettli
n
g
ti
m
e
in
co
m
p
ar
is
o
n
to
th
eir
P
SO.
Fig
u
r
e
8
d
is
p
la
y
s
SMI
B
'
s
r
esp
o
n
s
e
to
s
p
ee
d
d
ev
iatio
n
w
it
h
th
e
p
r
o
p
o
s
ed
in
d
iv
i
d
u
al
UP
FC
-
P
OD
co
n
tr
o
ller
,
w
e
s
e
lecte
d
ex
citatio
n
a
m
p
lit
u
d
e
m
o
d
u
latio
n
r
atio
(
i.e
.
ch
an
n
el
mE
o
n
ly
)
to
test
th
e
d
am
p
in
g
o
f
o
s
cillatio
n
.
I
t
ca
n
b
e
s
ee
n
th
at
th
e
ch
a
n
n
el
is
ac
ce
p
tab
le
f
o
r
d
a
m
p
in
g
o
s
cilla
tio
n
s
.
Fig
u
r
e
9
illu
s
tr
ates
th
e
s
p
ee
d
d
ev
iatio
n
r
esp
o
n
s
e
s
o
f
SMI
B
w
it
h
th
e
p
r
o
p
o
s
ed
co
o
r
d
in
ated
d
esig
n
b
et
w
ee
n
P
SS
&
UP
FC
-
P
OD
(
ch
an
n
el
mE
o
n
l
y
)
s
i
m
u
l
tan
eo
u
s
l
y
.
I
t c
an
b
e
n
o
ticed
th
at
b
etter
d
y
n
a
m
ic
r
esp
o
n
s
e
is
ac
h
ie
v
ed
b
y
th
e
co
o
r
d
in
ate
d
d
esig
n
b
et
w
ee
n
P
SS
&
UP
FC
-
P
OD.
Usi
n
g
DE
O
is
m
o
s
t
s
u
p
er
io
r
,
w
h
ic
h
h
a
s
f
e
w
er
o
s
cillatio
n
s
in
ad
d
itio
n
to
m
u
ch
q
u
ic
k
er
th
a
n
P
SO
tech
n
iq
u
e.
Settli
n
g
ti
m
e
i
s
(
2
s
ec
.
)
as
w
ell
as
o
v
er
s
h
o
o
t
is
(
0
.
0
0
6
6
7
p
.
u
)
b
y
DE
O
b
u
t P
SO th
e
s
et
tli
n
g
ti
m
e
is
(
6
.
6
2
s
ec
.
)
an
d
o
v
er
s
h
o
o
t is (
0
.
0
0
9
7
5
7
p
.
u
)
.
S
o
,
it c
an
b
e
n
o
ticed
th
at
th
e
s
et
tli
n
g
ti
m
e
a
n
d
o
v
er
s
h
o
o
t
o
b
tain
ed
b
y
DE
O
is
less
th
a
n
th
a
t
o
b
tain
ed
b
y
P
SO
as
d
em
o
n
s
tr
ated
in
T
ab
le
4
.
Fig
u
r
e
6
.
Sp
ee
d
v
ar
iatio
n
(
∆ω
)
w
it
h
o
u
t
an
y
co
n
tr
o
ller
Fig
u
r
e
7
.
Sp
ee
d
v
ar
iatio
n
(
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RE
F
E
R
E
NC
E
S
[1
]
S
e
th
i,
I.
,
S
h
a
rm
a
,
K.
K.,
a
n
d
V
e
rm
a
,
S.
,
"
L
o
w
f
r
e
q
u
e
n
c
y
o
sc
il
latio
n
in
p
o
w
e
r
s
y
ste
m
:a
su
rv
e
y
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Rec
e
n
t
Res
e
a
rc
h
As
p
e
c
ts,
v
o
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2
,
n
o
.
3
,
p
p
.
1
1
0
-
1
1
7
,
2
0
1
5
.
[2
]
Ch
a
u
d
h
a
ri,
P
.
B
.
a
n
d
P
a
tel,
M
.
V.
,
"
De
si
g
n
o
f
p
o
we
r
s
y
ste
m
st
a
b
il
ize
r
(P
S
S
)
t
o
e
n
h
a
n
c
e
p
o
w
e
r
s
y
st
e
m
sta
b
il
it
y
in
p
o
w
e
r
s
y
st
e
m
,
"
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
Res
e
a
rc
h
a
n
d
T
e
c
h
n
o
lo
g
y
,
v
o
l.
5
,
n
o
.
3
,
p
p
.
3
3
9
-
3
4
1
,
2
0
1
6
.
[3
]
Kh
a
n
c
h
i,
S
.
,
a
n
d
G
a
rg
,
V.
K.
,
"
Un
if
ied
P
o
w
e
r
F
lo
w
Co
n
tro
ll
e
r
(T
S
F
A
C
De
v
ice
):
A
Re
v
ie
w
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
E
n
g
i
n
e
e
rin
g
Res
e
a
rc
h
a
n
d
A
p
p
li
c
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ti
o
n
s (
IJ
ER
A),
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o
l.
3
,
n
o
.
4
,
p
p
.
1
4
3
0
-
1
4
3
5
,
2
0
1
3
.
[4
]
Y.
Ku
m
a
ri,
A
.
G
u
p
ta,
S
.
P
.
Bih
a
ri,
R.
Ch
a
u
b
e
y
,
a
n
d
B.
S
e
h
g
a
l,
"
P
e
rf
o
rm
a
n
c
e
a
n
d
A
n
a
l
y
sis
o
f
Re
a
c
ti
v
e
P
o
w
e
r
Co
m
p
e
n
sa
ti
o
n
b
y
Un
if
ied
P
o
w
e
r
F
lo
w
Co
n
tro
ll
e
r,
"
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
E
lec
trica
l
E
n
g
i
n
e
e
rin
g
a
n
d
In
f
o
rm
a
ti
c
s
(
IJ
EE
I)
,
v
o
l.
3
,
n
o
.
3
,
p
p
.
1
4
1
-
1
4
9
,
2
0
1
5
.
[5
]
N.
T
a
m
b
e
y
,
a
n
d
M
.
L
.
K
o
th
a
ri,
"
Da
m
p
in
g
o
f
p
o
w
e
r
s
y
ste
m
o
sc
il
la
ti
o
n
s
w
it
h
u
n
if
ied
p
o
w
e
r
f
lo
w
c
o
n
tro
ll
e
r
(U
P
F
C),
"
IEE
Pro
c
.
-
Ge
n
e
r.
T
r
a
n
sm
.
Distri
b
.
,
v
o
l
.
1
5
0
,
n
o
.
2
,
p
p
.
1
2
9
-
1
4
0
,
M
a
r.
2
0
0
3
.
[6
]
N.
T
a
m
b
e
y
,
a
n
d
M
.
L
.
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