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.
11
,
No
.
1
,
Feb
r
u
ar
y
2021
,
p
p
.
34
7
~
355
I
SS
N:
2
0
8
8
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v
1
1
i
1
.
pp
3
4
7
-
355
347
J
o
ur
na
l ho
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ep
a
g
e
:
h
ttp
:
//ij
ec
e.
ia
esco
r
e.
co
m
Sy
s
tem
un
certainti
e
s
est
i
m
a
ti
o
n b
a
s
ed
a
da
pt
i
v
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bu
s
t b
a
ck
s
tepp
i
n
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c
o
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o
l
fo
r
D
C
D
C
bu
ck
conv
er
ter
Ali H
us
s
ien M
a
ry
1
,
Abba
s
H
us
s
ie
n M
i
ry
2
,
M
o
ha
m
m
ed
H
us
s
ei
n M
iry
3
1
M
e
c
h
a
tro
n
ics
E
n
g
in
e
e
rin
g
,
Un
iv
e
rsit
y
o
f
Ba
g
h
d
a
d
,
Ira
q
2
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
,
A
lm
u
sta
n
siriy
a
h
Un
iv
e
rsit
y
,
Ira
q
3
Co
m
m
u
n
ica
ti
o
n
E
n
g
in
e
e
rin
g
,
Un
iv
e
rsit
y
o
f
tec
h
n
o
lo
g
y
,
Ira
q
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ma
y
2
0
,
2
0
2
0
R
ev
i
s
ed
J
u
l 1
2
,
2
0
2
0
A
cc
ep
ted
J
u
l
28
,
2
0
2
0
T
h
is p
a
p
e
r
p
ro
p
o
se
d
a
n
o
v
e
l
a
d
a
p
ti
v
e
ro
b
u
st b
a
c
k
ste
p
p
in
g
c
o
n
tro
l
s
c
h
e
m
e
f
o
r
DC
-
DC
b
u
c
k
c
o
n
v
e
rter
su
b
jec
ted
to
e
x
tern
a
l
d
ist
u
rb
a
n
c
e
a
n
d
sy
st
e
m
u
n
c
e
rtain
ty
.
Un
c
e
rtain
ty
in
th
e
l
o
a
d
re
sista
n
c
e
a
n
d
t
h
e
in
p
u
t
v
o
lt
a
g
e
re
p
re
se
n
t
th
e
b
ig
c
h
a
ll
e
n
g
e
in
b
u
c
k
c
o
n
v
e
rter
c
o
n
tro
l.
In
t
h
is
w
o
rk
,
a
n
a
d
a
p
t
iv
e
e
sti
m
a
to
r
f
o
r
m
a
tch
e
d
a
n
d
m
ism
a
tch
e
d
u
n
c
e
rtain
ti
e
s
b
a
se
d
b
a
c
k
ste
p
p
in
g
c
o
n
tro
l
is
a
p
p
li
e
d
f
o
r
DC
-
DC
b
u
c
k
c
o
n
v
e
rter.
T
h
e
u
p
d
a
ti
n
g
law
s
a
re
d
e
term
in
e
d
b
a
se
d
o
n
th
e
ly
a
p
u
n
o
v
th
e
o
re
m
.
T
h
u
s,
th
e
d
if
f
e
r
e
n
c
e
b
e
twe
e
n
th
e
e
stim
a
ted
p
a
ra
m
e
ters
a
n
d
a
c
tu
a
l
p
a
ra
m
e
ters
c
o
n
v
e
rg
e
s
to
z
e
ro
.
T
h
e
p
ro
p
o
se
d
c
o
n
tro
l
m
e
th
o
d
i
s
c
o
m
p
a
re
d
w
it
h
th
e
c
o
n
v
e
n
ti
o
n
a
l
slid
i
n
g
m
o
d
e
c
o
n
tro
l
a
n
d
in
teg
ra
l
slid
in
g
m
o
d
e
c
o
n
tro
l.
S
im
u
lati
o
n
re
su
lt
s
d
e
m
o
n
stra
te
th
e
e
ff
e
c
ti
v
e
n
e
ss
a
n
d
ro
b
u
stn
e
ss
o
f
th
e
p
ro
p
o
se
d
c
o
n
tr
o
ll
e
r
.
K
ey
w
o
r
d
s
:
B
ac
k
s
tep
p
in
g
B
u
ck
co
n
v
er
t
e
r
C
o
n
tr
o
l
R
o
b
u
s
t c
o
n
tr
o
l
Un
ce
r
tai
n
ties
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
BY
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
A
li
Hu
s
s
ie
n
Ma
r
y
,
Dep
ar
t
m
en
t o
f
Me
ch
atr
o
n
ics
E
n
g
i
n
ee
r
i
n
g
,
Un
i
v
er
s
it
y
o
f
B
ag
h
d
ad
,
I
r
aq
.
E
m
ai
l:
ali
m
ar
y
7
6
@
k
ec
b
u
.
u
o
b
ag
h
d
ad
.
ed
u
.
iq
1.
I
NT
RO
D
UCT
I
O
N
R
ec
en
t
l
y
,
a
D
C
-
DC
co
n
v
er
ter
is
ap
p
lied
s
u
cc
es
s
f
u
l
l
y
in
m
an
y
m
o
d
er
n
ap
p
licatio
n
s
s
u
ch
as
w
i
n
d
tu
r
b
in
e
s
y
s
te
m
s
,
a
d
r
i
v
er
f
o
r
a
DC
m
o
to
r
,
co
m
m
u
n
icatio
n
s
y
s
te
m
s
,
au
to
m
atio
n
s
y
s
te
m
s
,
an
d
p
h
o
to
v
o
ltaic
s
y
s
te
m
s
[1
-
5
]
.
T
h
e
b
u
c
k
,
b
o
o
s
t,
an
d
b
u
c
k
/b
o
o
s
t
ar
e
i
m
p
o
r
tan
t
to
p
o
lo
g
ies
o
f
t
h
e
D
C
-
DC
co
n
v
er
ter
,
a
n
d
all
th
ese
to
p
o
lo
g
ies
tr
y
to
r
eg
u
lat
e
th
e
o
u
tp
u
t
v
o
lta
g
es
a
n
d
tr
ac
k
th
e
d
esire
d
v
o
ltag
e
i
n
th
e
p
r
esen
ce
o
f
t
h
e
s
y
s
te
m
u
n
ce
r
tai
n
t
y
an
d
ex
ter
n
al
d
is
t
u
r
b
an
ce
[6
-
8
]
.
T
h
e
DC
-
D
C
b
u
ck
co
n
v
er
ter
co
n
s
i
s
ts
o
f
a
n
in
d
u
cto
r
,
ca
p
ac
i
to
r
,
lo
ad
r
esis
tan
ce
,
a
n
d
s
w
itc
h
in
g
tr
an
s
i
s
to
r
.
T
h
e
s
w
itc
h
i
n
g
cir
c
u
it
i
s
t
h
e
i
m
p
o
r
tan
t
e
le
m
e
n
t
i
n
t
h
e
D
C
-
DC
b
u
c
k
co
n
v
er
ter
,
an
d
it
’
s
t
h
e
m
ain
r
ea
s
o
n
f
o
r
t
h
e
n
o
n
lin
ea
r
it
y
b
eh
av
io
r
o
f
th
e
D
C
-
DC
co
n
v
er
te
r
.
T
h
is
n
o
n
li
n
ea
r
it
y
an
d
u
n
ce
r
tai
n
t
y
o
f
th
e
D
C
-
D
C
co
n
v
er
ter
m
o
d
el
m
ak
e
t
h
e
co
n
tr
o
l
o
f
th
e
D
C
-
D
C
co
n
v
er
ter
as
a
b
i
g
c
h
alle
n
g
e.
Hen
ce
,
m
a
n
y
co
n
tr
o
l
s
ch
e
m
e
s
h
ad
b
ee
n
p
r
esen
ted
to
co
n
tr
o
l
th
e
DC
-
D
C
co
n
v
er
ter
[
9
-
1
3
]
.
So
f
t
co
m
p
u
ti
n
g
alg
o
r
th
i
m
s
h
ad
b
ee
n
ap
p
lied
s
u
ce
s
f
u
l
y
i
n
t
u
n
i
n
i
g
co
n
tr
o
lle
r
g
an
i
s
f
o
r
m
an
y
co
m
p
licate
d
s
y
s
te
m
s
[
1
4
-
1
8
]
.
s
lid
in
g
m
o
d
e
co
n
tr
o
l
(
SMC
)
is
an
ef
f
icie
n
t
an
d
p
o
p
u
lar
co
n
tr
o
l
ap
p
r
o
ac
h
th
at
h
as
b
ee
n
ap
p
lied
ef
f
ec
ti
v
el
y
f
o
r
co
n
tr
o
l
m
an
y
n
o
n
li
n
ea
r
s
y
s
te
m
s
s
u
c
h
as
r
o
b
o
tic
s
y
s
te
m
s
,
DC
-
DC
co
n
v
er
ter
,
etc.
Fas
t
r
esp
o
n
s
e
an
d
s
tr
o
n
g
r
o
b
u
s
tn
es
s
ar
e
th
e
i
m
p
o
r
tan
t
a
d
v
an
ta
g
es
o
f
SM
C
[
1
9
-
22
]
.
On
th
e
o
t
h
er
h
a
n
d
,
th
e
c
h
atter
i
n
g
an
d
s
tead
y
-
s
tate
er
r
o
r
s
ar
e
a
m
aj
o
r
d
r
aw
b
ac
k
o
f
th
e
SMC
.
Mo
r
eo
v
er
,
SM
C
is
r
o
b
u
s
t
o
n
l
y
to
th
e
m
atc
h
ed
u
n
ce
r
tain
t
y
a
n
d
d
is
tu
r
b
an
ce
.
As
a
r
e
s
u
l
t,
s
ta
n
d
ar
d
SMC
is
n
o
t
q
u
ali
f
ied
f
o
r
DC
-
DC
co
n
v
er
t
er
.
R
ec
e
n
t
p
u
b
licatio
n
s
i
n
d
icate
g
r
ea
t
atte
n
tio
n
o
f
r
esear
ch
er
s
ab
o
u
t
t
h
e
s
e
d
r
a
w
b
ac
k
s
b
y
s
u
g
g
est
in
g
d
i
f
f
er
en
t
s
tr
ate
g
i
es
li
k
e
d
is
tu
r
b
an
ce
o
b
s
er
v
er
w
i
th
SMC
[
23
]
,
u
n
ce
r
tain
t
y
an
d
d
is
tu
r
b
an
ce
o
b
s
er
v
er
w
it
h
SM
C
[
24
]
.
B
ac
k
s
tep
p
in
g
co
n
tr
o
l
is
an
o
th
er
e
f
f
icie
n
t
co
n
tr
o
l
s
c
h
e
m
e
t
h
at
h
a
s
b
ee
n
w
id
el
y
c
o
n
s
id
er
ed
d
u
e
to
its
s
i
m
p
lic
it
y
in
d
esi
g
n
a
n
d
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.
11
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
1
:
347
-
355
348
i
m
p
le
m
en
ta
tio
n
.
Ho
w
ev
er
,
it
s
co
n
tr
o
l
la
w
r
eq
u
ir
ed
th
e
e
x
ac
t
d
y
n
a
m
ic
m
o
d
el
o
f
t
h
e
co
n
tr
o
l
s
y
s
te
m
,
w
h
ich
i
s
n
o
t
p
o
s
s
ib
le
i
n
p
r
ac
tice
ap
p
licatio
n
s
.
T
h
e
m
o
ti
v
atio
n
o
f
t
h
i
s
w
o
r
k
i
s
to
i
m
p
r
o
v
e
th
e
B
ac
k
s
t
ep
p
in
g
co
n
tr
o
l
a
n
d
o
v
er
co
m
e
th
i
s
s
h
o
r
tag
e
b
y
a
p
p
ly
i
n
g
ad
ap
tiv
e
tech
n
iq
u
es
t
o
esti
m
ated
u
n
k
n
o
w
n
p
ar
a
m
e
ter
s
(
m
a
tch
ed
an
d
m
is
m
atc
h
ed
u
n
ce
r
tai
n
ties
)
i
n
t
h
e
p
r
esen
ce
o
f
t
h
e
lo
ad
r
esis
ta
n
ce
an
d
in
p
u
t
v
o
lta
g
e
v
ar
iatio
n
s
.
T
h
is
p
ap
er
ai
m
s
to
d
esig
n
a
n
ad
ap
tiv
e
r
o
b
u
s
t
co
n
tr
o
l
s
ch
e
m
e
f
o
r
DC
-
D
C
co
n
v
er
ter
w
ith
a
g
o
o
d
an
d
r
o
b
u
s
t
p
er
f
o
r
m
an
ce
r
eg
ar
d
less
o
f
th
e
v
ar
iatio
n
s
o
f
th
e
lo
ad
r
esis
tan
ce
,
th
e
i
n
p
u
t
v
o
ltag
e,
an
d
ex
ter
n
al
d
is
t
u
r
b
an
ce
.
A
n
o
v
el
co
n
tr
o
l
la
w
h
as
b
ee
n
p
r
esen
ted
to
en
s
u
r
e
th
e
r
o
b
u
s
t
n
e
s
s
o
f
DC
-
DC
co
n
v
er
ter
ag
ain
s
t
m
a
tch
ed
an
d
u
n
m
atch
ed
u
n
ce
r
tai
n
tie
s
.
2.
DC
-
DC
B
UCK
M
O
DE
L
DE
F
I
NI
T
I
O
N
T
h
is
s
ec
tio
n
d
escr
ib
es
t
h
e
d
y
n
a
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ic
m
o
d
el
o
f
t
h
e
D
C
-
D
C
b
u
c
k
co
n
v
er
t
e
r
,
w
h
ich
is
s
h
o
w
n
i
n
Fig
u
r
e
1
.
T
h
is
co
n
v
er
t
e
r
is
co
m
p
o
s
ed
o
f
DC
v
o
ltag
e
s
o
u
r
ce
,
tr
an
s
is
to
r
s
w
itch
,
Dio
d
e,
in
d
i
cto
r
,
ca
p
ac
ito
r
,
an
d
lo
ad
r
esis
tan
ce
.
T
h
er
e
ar
e
t
w
o
m
o
d
els
f
o
r
t
h
is
co
n
v
er
t
e
r
b
as
ed
o
n
th
e
p
o
s
itio
n
o
f
t
h
e
s
w
it
ch
(
ON
a
n
d
OF
F).
W
h
en
t
h
e
tr
an
s
is
to
r
s
w
itc
h
at
ON
p
o
s
itio
n
th
e
s
tate
-
s
p
ac
e
m
o
d
el
is
:
=
̇
+
̇
=
̇
−
}
(
1
)
At
O
FF
p
o
s
i
tio
n
,
t
h
e
s
ta
te
s
p
ac
e
m
o
d
el
is
0
=
̇
+
̇
=
̇
−
}
(
2
)
w
h
er
e
is
th
e
D
C
i
n
p
u
t
v
o
ltag
e,
is
th
e
lo
ad
r
esis
tan
ce
,
is
th
e
in
d
u
cta
n
ce
,
̇
is
th
e
in
d
icato
r
cu
r
r
en
t,
is
th
e
ca
p
ac
itan
ce
,
a
n
d
is
t
h
e
o
u
tp
u
t
v
o
ltag
e.
T
h
e
av
er
a
g
e
s
tate
-
s
p
ac
e
m
o
d
el
o
f
t
h
e
co
n
v
er
t
e
r
ca
n
b
e
ex
p
r
ess
ed
as f
o
llo
w
s
[
1
8
]:
=
1
̇
−
1
(
3
)
̇
=
−
1
+
1
(
4
)
∈
[
0
,
1
]
d
en
o
tes
th
e
co
n
tr
o
l
s
ig
n
al
t
h
at
r
eg
u
lates
t
h
e
d
u
t
y
r
atio
o
f
PW
M
in
s
u
ch
w
a
y
t
h
at
m
a
k
es
o
u
tp
u
t
v
o
ltag
e
tr
ac
k
s
t
h
e
s
o
u
r
ce
v
o
l
tag
e.
T
h
e
a
v
er
ag
e
m
o
d
el
o
f
th
e
b
u
ck
co
n
v
er
ter
as
s
u
m
e
s
id
ea
l
co
m
p
o
n
e
n
ts
.
Ho
w
e
v
er
,
in
p
r
ac
tice,
th
e
lo
ad
r
esis
tan
ce
an
d
in
p
u
t
v
o
ltag
e
a
r
e
u
n
k
n
o
w
n
e
x
ac
tl
y
an
d
th
e
y
r
ep
r
esen
t
th
e
s
i
g
n
i
f
ican
t
u
n
ce
r
tain
ties
o
f
th
is
co
n
v
er
t
e
r
.
T
h
er
ef
o
r
e,
th
e
s
tate
-
s
p
ac
e
m
o
d
el
w
ill
b
e
r
ew
r
itte
n
i
n
ter
m
s
o
f
n
o
m
i
n
al
lo
ad
r
esis
ta
n
ce
,
an
d
n
o
m
i
n
al
i
n
p
u
t
v
o
ltag
e
.
=
1
̇
−
[
1
]
=
1
̇
−
+
[
1
−
1
]
(
5
)
̇
=
−
1
+
1
+
1
(
−
)
(
6
)
T
h
en
th
e
b
u
c
k
m
o
d
el
i
n
(
6
)
an
d
(
8
)
c
an
b
e
r
ep
r
esen
t a
s
̇
1
=
1
2
−
1
+
1
(
7
)
̇
2
=
−
1
1
+
1
+
2
(8
)
w
h
er
e
1
=
,
2
=
̇
,
1
=
[
1
−
1
]
,
an
d
2
=
1
(
−
)
.
L
et
=
1
−
1
(
9
)
=
−
(1
0
)
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
S
ystem
u
n
ce
r
ta
in
ties
esti
ma
tio
n
b
a
s
ed
a
d
a
p
tive
r
o
b
u
s
t b
a
ck
s
tep
p
in
g
…
(
A
li Hu
s
s
ien
Ma
r
y
)
349
T
h
en
1
an
d
2
b
ec
o
m
e
1
=
1
(1
1
)
2
=
1
(1
2
)
I
t c
an
b
e
n
o
tice
d
th
a
t
an
d
ar
e
u
n
k
n
o
w
n
d
u
e
to
t
h
e
u
n
ce
r
tain
t
y
o
f
th
e
lo
ad
r
esis
ta
n
ce
a
n
d
t
h
e
in
p
u
t
s
o
u
r
ce
.
I
n
liter
atu
r
e,
s
i
n
ce
th
e
u
n
ce
r
tai
n
t
y
1
ap
p
ea
r
s
in
th
e
d
iv
er
tiv
e
o
f
t
h
e
lo
ad
v
o
ltag
e
ex
p
r
ess
io
n
(
1
1
)
,
w
h
ic
h
is
n
o
t
d
ep
en
d
e
nt
d
ir
ec
tl
y
on
th
e
i
n
p
u
t
;
t
h
u
s
1
is
ca
lled
m
is
m
atc
h
ed
u
n
ce
r
tain
t
y
,
an
d
2
th
at
ex
p
r
es
s
ed
in
(
12
)
is
ca
lled
a
m
atc
h
ed
u
n
ce
r
tain
t
y
.
T
h
e
o
b
j
ec
tiv
e
o
f
th
is
w
o
r
k
is
to
d
esig
n
a
r
o
b
u
s
t
co
n
tr
o
ller
th
at
m
a
k
es
th
e
o
u
tp
u
t v
o
lta
g
e
tr
ac
k
s
th
e
r
ef
er
en
ce
v
o
ltag
e
i
n
t
h
e
p
r
esen
ce
o
f
m
is
m
atc
h
ed
an
d
m
atch
e
d
u
n
ce
r
tai
n
ties
.
Fig
u
r
e
1
.
DC
-
D
C
b
u
c
k
co
n
v
er
ter
3.
P
O
P
O
SE
D
CO
NT
RO
L
SC
H
E
M
E
T
o
co
m
p
en
s
ate
e
f
f
ec
t
s
o
f
ex
t
er
n
al
d
is
t
u
r
b
an
ce
,
m
atc
h
ed
an
d
m
is
m
atc
h
ed
u
n
ce
r
tai
n
tie
s
t
h
at
ca
u
s
e
d
m
ai
n
l
y
d
u
e
to
th
e
ch
a
n
g
es
in
t
h
e
lo
ad
r
esi
s
ta
n
ce
a
n
d
i
n
p
u
t
v
o
lta
g
e,
t
h
is
p
ap
er
p
r
e
s
en
t
ed
a
n
ad
ap
tiv
e
esti
m
atio
n
f
o
r
th
e
m
is
m
atc
h
ed
u
n
ce
r
tain
t
y
a
n
d
m
atc
h
ed
u
n
ce
r
tai
n
t
y
in
s
u
c
h
a
w
a
y
t
h
at
en
s
u
r
e
s
th
e
co
n
v
er
g
en
ce
o
f
t
h
ese
u
n
ce
r
tain
ties
b
ased
o
n
ad
ap
ti
v
e
b
ac
k
s
tep
p
in
g
co
n
tr
o
l.
At
f
ir
s
t,
m
is
m
atc
h
ed
u
n
ce
r
tai
n
t
y
1
an
d
m
atc
h
ed
u
n
ce
r
tain
t
y
2
ar
e
e
s
ti
m
ated
,
th
e
n
,
th
ese
est
i
m
a
ted
v
al
u
es
ar
e
u
s
ed
i
n
d
esig
n
th
e
r
o
b
u
s
t
ad
ap
tiv
e
b
ac
k
s
tep
p
in
g
co
n
tr
o
ller
.
T
h
e
b
lo
ck
d
iag
r
a
m
o
f
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
s
h
o
w
n
in
Fig
u
r
e
2.
Fig
u
r
e
2
.
B
lo
ck
d
iag
r
a
m
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
l sch
e
m
e
3
.
1
.
Ada
ptiv
e
E
s
t
i
m
a
t
io
n o
f
un
k
no
w
n pa
ra
m
et
er
s
l
a
w
T
h
is
s
ec
tio
n
ex
p
lai
n
s
t
h
e
s
tep
s
r
elate
d
to
esti
m
at
in
g
th
e
u
n
k
n
o
w
n
b
u
ck
m
o
d
el
p
ar
am
eter
s
r
eq
u
ir
ed
in
d
esi
g
n
t
h
e
co
n
tr
o
l
s
i
g
n
al
f
o
r
th
e
DC
-
D
C
b
u
c
k
co
n
v
er
ter
.
T
h
e
p
r
o
p
o
s
ed
co
n
tr
o
l
s
ch
e
m
e
a
s
s
u
m
es
th
e
f
o
llo
w
i
n
g
:
A
ll
s
tates
ar
e
m
ea
s
u
r
ab
le
T
h
is
w
o
r
k
a
s
s
u
m
e
s
co
n
s
tan
t o
r
s
lo
w
v
ar
i
at
i
on
s of
t
he
l
o
ad
r
es
i
s
t
anc
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.
11
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
1
:
347
-
355
350
Step
1
:
Def
in
e
t
h
e
tr
ac
k
i
n
g
er
r
o
r
1
an
d
its
d
er
iv
at
iv
e,
1
=
1
−
1
(
1
3
)
̇
1
=
̇
1
−
̇
1
(1
4
)
w
h
er
e
1
=
d
en
o
tes
th
e
d
es
ir
ed
r
ef
er
en
ce
v
o
lta
g
e.
L
e
t
̂
r
ep
r
ese
n
t
t
h
e
est
i
m
a
tio
n
o
f
t
h
e
m
is
m
atc
h
ed
u
n
ce
r
tai
n
t
y
an
d
it is
u
p
d
ated
as f
o
llo
w
s
:
̂
̇
=
1
1
1
(1
5
)
w
h
er
e
1
is
ad
ap
tio
n
r
ate.
A
ls
o
,
m
a
tch
ed
u
n
ce
r
tai
n
t
y
r
ep
r
es
n
tes
b
y
̂
ca
n
b
e
esti
m
ated
an
d
u
p
d
ated
w
it
h
th
e
ad
ap
tio
n
r
ate
2
ac
co
r
d
in
g
to
th
e
f
o
llo
w
i
n
g
s
u
g
g
ested
f
o
r
m
u
la
.
̂
̇
=
2
1
2
(1
6
)
3
.
2
.
Ro
bu
s
t
ba
ck
s
t
epp
ing
co
ntr
o
l desig
n
No
w
,
to
d
esig
n
t
h
e
p
r
o
p
o
s
ed
c
o
n
tr
o
ller
Step
2
:
Def
in
e
a
v
ir
t
u
al
co
n
tr
o
l in
p
u
t
2
as
2
=
(
1
0
−
̂
)
+
̇
1
−
1
1
(1
7
)
Step
3
:
L
et
2
d
en
o
tes th
e
d
i
f
f
er
en
ce
b
et
w
ee
n
t
h
e
v
ir
t
u
al
co
n
tr
o
l in
p
u
t a
n
d
t
h
e
in
d
icato
r
cu
r
r
en
t
2
=
2
−
2
(
18
)
Step
4
:
Fin
all
y
,
t
h
e
p
r
o
p
o
s
ed
c
o
n
tr
o
l la
w
ca
n
b
e
ex
p
r
ess
ed
as
=
+
[
−
2
2
−
(
1
−
1
)
1
+
1
1
+
̇
2
]
(
19
)
3
.
3
.
St
a
bil
it
y
a
na
ly
s
is
T
heo
re
m
1
:
C
o
n
s
id
er
t
h
e
D
C
-
DC
b
u
ck
co
n
v
er
ter
s
y
s
te
m
d
escr
ib
ed
in
(
1
)
w
it
h
u
n
k
n
o
w
n
m
is
m
atc
h
ed
an
d
m
atc
h
ed
u
n
ce
r
tai
n
ties
.
I
f
th
e
r
o
b
u
s
t
b
ac
k
s
tep
p
in
g
co
n
tr
o
l
s
ch
e
m
e
d
es
ig
n
ed
w
it
h
a
d
ap
tatio
n
la
w
s
o
f
m
is
m
atc
h
ed
a
n
d
m
atc
h
ed
u
n
c
er
tain
ties
ar
e
d
er
iv
ed
as i
n
(
1
5
)
an
d
(
1
6
)
an
d
th
e
r
o
b
u
s
t
co
n
tr
o
ller
w
h
ic
h
d
er
iv
ed
as in
(
19
)
,
th
en
t
h
e
clo
s
ed
-
lo
o
p
s
y
s
te
m
is
a
s
y
m
p
to
ticall
y
s
ta
b
le.
P
ro
o
f
.
:
Def
in
e
V
1
as
q
u
ad
r
atic
L
y
ap
u
n
o
v
f
u
n
ctio
n
a
s
V
1
=
1
2
e
1
2
+
1
2
ρ
1
−
1
θ
̃
2
(2
0
)
w
h
er
e
θ
̃
is
esti
m
at
io
n
er
r
o
r
o
f
m
is
m
atc
h
ed
u
n
ce
r
tai
n
t
y
a
n
d
g
iv
e
as
θ
̃
=
θ
−
θ
̂
(2
1
)
V
̇
1
=
e
1
e
1
̇
+
ρ
1
−
1
θ
̃
θ
̃
̇
(2
2
)
=
e
1
(
x
̇
1
−
x
̇
1d
)
+
ρ
−
1
θ
̃
θ
̃
̇
(2
3
)
θ
̃
̇
=
θ
̇
−
θ
̂
̇
V
̇
1
=
e
1
(
1
C
x
2
−
x
1
C
R
o
+
d
1
−
x
̇
1d
)
+
ρ
1
−
1
θ
̃
(
θ
̇
−
θ
̂
̇
)
(2
4
)
=
e
1
(
1
C
(
e
2
+
x
2d
)
−
x
1
C
R
o
+
d
1
−
x
̇
1d
)
+
ρ
1
−
1
θ
̃
(
θ
̇
−
θ
̂
̇
)
(2
5
)
=
1
C
e
1
e
2
+
e
1
(
x
2d
C
−
x
1
C
R
o
+
x
1
C
(
θ
̃
+
θ
̂
)
−
x
̇
1d
)
+
ρ
1
−
1
θ
̃
(
θ
̇
−
θ
̂
̇
)
(2
6
)
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
S
ystem
u
n
ce
r
ta
in
ties
esti
ma
tio
n
b
a
s
ed
a
d
a
p
tive
r
o
b
u
s
t b
a
ck
s
tep
p
in
g
…
(
A
li Hu
s
s
ien
Ma
r
y
)
351
=
1
C
e
1
e
2
+
e
1
(
x
2d
C
−
x
1
C
R
o
+
x
1
C
θ
̂
−
x
̇
1d
)
+
(
e
1
x
1
C
−
ρ
−
1
θ
̂
̇
)
θ
̃
+
ρ
1
−
1
θ
̃
θ
̇
(2
7
)
=
1
C
e
1
e
2
−
k
1
e
1
2
+
ρ
1
−
1
θ
̃
θ
̇
(
28
)
R
e
m
ar
k
1
.
A
s
d
escr
ib
ed
in
Ass
u
m
p
tio
n
2
,
if
th
e
lo
ad
u
n
ce
r
tain
t
y
i
s
s
lo
w
l
y
ti
m
e
-
v
ar
y
i
n
g
o
r
lo
ad
r
esis
tan
ce
i
s
a
co
n
s
tan
t v
al
u
e,
th
e
n
θ
̇
is
ze
r
o
,
o
r
it c
an
b
e
n
eg
lecte
d
.
T
h
er
ef
o
r
e,
(
28
)
b
ec
o
m
es
V
̇
1
=
1
C
e
1
e
2
−
k
1
e
1
2
(
29
)
R
e
m
ar
k
2
.
I
f
th
e
lo
ad
r
esis
ta
n
c
e
is
v
ar
y
i
n
g
f
a
s
t
w
it
h
t
h
e
ti
m
e,
th
en
,
(
29
)
ca
n
b
e
w
r
itte
n
as
V
̇
1
=
1
C
e
1
e
2
−
k
1
e
1
2
+
ϵ
(3
0
)
ϵ
=
ρ
1
−
1
θ
̃
θ
̇
(3
1
)
I
n
t
h
is
ca
s
e,
ap
p
r
o
p
r
iate
ch
o
ice
f
o
r
t
h
e
ad
ap
tio
n
r
ate
a
n
d
p
o
s
itiv
e
g
ai
n
(
ρ
1
an
d
k
)
ca
n
e
n
s
u
r
es
a
m
i
n
i
m
u
m
tr
ac
k
in
g
er
r
o
r
.
B
y
i
n
te
g
r
atin
g
(
6
)
w
.
r
.
t.
ti
m
e,
e
x
p
licit
e
x
p
r
ess
io
n
o
f
t
h
e
e
s
ti
m
ated
m
is
m
atc
h
ed
u
n
ce
r
tai
n
t
y
ca
n
b
e
w
r
itte
n
as
θ
̂
=
∫
e
1
ρ
1
x
1
C
t
0
d
τ
(3
2
)
R
e
m
ar
k
3
.
T
h
is
u
p
d
atin
g
la
w
s
h
o
w
s
t
h
at
t
h
er
e
i
s
n
o
n
ee
d
to
d
eter
m
i
n
e
t
h
e
d
er
iv
at
iv
e
o
f
a
n
y
m
ea
s
u
r
ed
s
i
g
n
a
l
w
h
ic
h
is
v
er
y
i
m
p
o
r
t
a
n
t i
n
a
p
ar
ticu
lar
ap
p
licatio
n
b
ec
au
s
e
t
h
e
d
if
f
er
en
t
ial
p
r
o
d
u
ce
s
a
n
o
is
y
s
i
g
n
a
l.
A
s
ec
o
n
d
L
y
ap
u
n
o
v
f
u
n
ctio
n
is
a
ca
n
d
id
ate
to
d
esig
n
co
n
tr
o
l
la
w
o
f
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l
ler
as
w
el
l
as u
p
d
atin
g
la
w
o
f
t
h
e
m
atch
e
d
u
n
ce
r
tai
n
t
y
.
T
h
e
f
u
n
ctio
n
i
s
V
2
=
V
1
+
1
2
e
2
2
+
1
2
ρ
2
−
1
δ
̃
2
(3
3
)
w
h
er
e
δ
̃
=
δ
−
δ
̂
.
δ
̃
d
en
o
tes
th
e
esti
m
ati
o
n
er
r
o
r
o
f
th
e
m
atch
ed
u
n
ce
r
t
ain
t
y
.
V
̇
2
=
V
̇
1
+
e
2
e
̇
2
+
ρ
2
−
1
δ
̃
δ
̃
̇
(3
4
)
V
̇
2
=
V
̇
1
+
e
2
e
̇
2
+
ρ
2
−
1
δ
̃
δ
̃
̇
(3
5
)
V
̇
2
=
1
C
e
1
e
2
−
k
1
e
1
2
+
e
2
(
x
̇
2
−
x
̇
2d
)
+
ρ
2
−
1
δ
̃
(
δ
̇
−
δ
̂
̇
)
(3
6
)
V
̇
2
=
1
C
e
1
e
2
−
k
1
e
1
2
+
e
2
(
−
1
L
x
1
+
1
L
μ
E
o
+
d
2
−
x
̇
2d
)
+
ρ
2
−
1
δ
̃
(
δ
̇
−
δ
̂
̇
)
(3
7
)
V
̇
2
=
−
k
1
e
1
2
+
e
2
(
(
1
C
−
1
L
)
e
1
−
1
L
x
1d
+
1
L
(
E
o
+
δ
̂
)
μ
−
x
̇
2d
)
+
(
1
L
μ
e
2
−
ρ
2
−
1
δ
̂
̇
)
δ
̃
+
ρ
2
−
1
δ
̃
δ
̇
(
38
)
V
̇
2
=
−
k
1
e
1
2
−
k
2
e
2
2
+
ρ
2
−
1
δ
̃
δ
̇
(
39
)
R
e
m
ar
k
4
.
I
f
th
e
in
p
u
t
s
o
u
r
ce
is
s
lo
w
l
y
t
i
m
e
-
v
ar
y
i
n
g
o
r
it’
s
co
n
s
tan
t,
th
e
n
δ
̇
is
ze
r
o
,
o
r
it
ca
n
b
e
n
eg
lecte
d
.
T
h
er
ef
o
r
e,
(
30
)
b
ec
o
m
es
V
̇
1
=
−
k
1
e
1
2
−
k
2
e
2
2
(
40
)
R
e
m
a
r
k
5
.
I
f
th
e
i
n
p
u
t
s
o
u
r
ce
i
s
v
ar
y
i
n
g
f
a
s
t
w
it
h
t
h
e
ti
m
e,
th
en
,
(
40
)
ca
n
b
e
w
r
itte
n
as
V
̇
1
=
−
k
1
e
1
2
−
k
2
e
2
2
+
ϵ
2
(4
1
)
ϵ
2
=
ρ
2
−
1
δ
̃
δ
̇
(4
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.
11
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
1
:
347
-
355
352
I
n
th
i
s
ca
s
e,
a
n
ap
p
r
o
p
r
iate
ch
o
ice
f
o
r
th
e
ad
ap
tio
n
r
ate
an
d
p
o
s
itiv
e
g
a
in
(
ρ
2
k
1
an
d
k
2
)
ca
n
en
s
u
r
e
th
e
m
in
i
m
u
m
tr
ac
k
i
n
g
er
r
o
r
.
T
h
u
s
V
̇
2
=
−
k
1
e
1
2
−
k
2
e
2
2
+
0
≤
0
(4
3
)
Sin
ce
V
̇
2
≤
0
,
w
h
ich
m
ea
n
s
V
2
(
t
)
≤
V
2
(
0
)
,
th
is
i
n
d
i
ca
te
th
at
t
h
e
e
1
(
t
)
an
d
e
2
(
t
)
ar
e
b
o
u
n
d
ed
.
Def
i
n
e
ψ
=
−
V
̇
2
(
44
)
∫
ψ
(
τ
)
d
τ
=
V
2
(
0
)
−
V
2
(
t
)
t
0
(
45
)
Sin
ce
V
2
(
0
)
is
b
o
u
n
d
ed
an
d
V
2
(
t
)
is
les
s
t
h
an
V
2
(
0
)
,
th
en
,
it e
a
s
il
y
o
b
tai
n
ed
th
e
f
o
llo
w
in
g
r
es
u
lt
l
im
t
→
∞
∫
ψ
(
τ
)
d
τ
<
∞
t
0
(
46
)
A
cc
o
r
d
in
g
to
th
e
B
ar
b
alat’
s
L
e
m
m
a,
it
ca
n
b
e
g
et
l
im
t
→
∞
ψ
(
τ
)
=
0
.
T
h
is
in
d
icate
th
at
th
e
e
1
(
t
)
an
d
e
2
(
t
)
co
n
v
er
g
e
to
ze
r
o
as
t
→
∞
.
A
cc
o
r
d
in
g
to
t
h
is
p
r
o
v
e,
th
e
m
e
n
tio
n
t
h
eo
r
e
m
ca
n
b
e
co
n
cl
u
d
ed
.
4.
SI
M
UL
AT
I
O
N
R
E
S
UL
T
S
T
o
illu
s
tr
ate
th
e
e
f
f
ec
ti
v
en
e
s
s
an
d
r
o
b
u
s
tn
e
s
s
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
l
m
et
h
o
d
,
a
s
i
m
u
latio
n
m
o
d
el
o
f
th
e
D
C
-
D
C
b
u
c
k
co
n
v
er
t
e
r
i
s
b
u
i
lt
b
y
u
s
i
n
g
M
A
T
L
A
B
.
T
h
e
n
o
m
i
n
al
m
o
d
el
p
ar
a
m
ete
r
s
o
f
th
e
co
n
v
er
ter
s
elec
ted
as
f
o
llo
w
s
:
=
20
,
=
10
,
=
100
Ω
,
=
1
0
0
0
µF
,
a
n
d
=
4
.
7
m
H
.
C
o
n
v
e
n
tio
n
al
S
MC
(
C
S
MC
)
an
d
I
n
teg
r
al
S
MC (
I
SM
C
)
ar
e
tak
en
f
o
r
co
m
p
ar
is
o
n
.
T
h
e
co
n
tr
o
l la
w
o
f
C
SM
C
is
:
=
[
1
0
+
1
]
1
−
1
2
−
2
(
)
(
4
7
)
=
2
+
1
(
4
8
)
Fo
r
th
e
I
SMC
d
esi
g
n
,
t
h
is
s
ec
t
io
n
ap
p
lies
th
e
p
r
o
ce
d
u
r
es
o
f
I
SMC
d
esig
n
in
[
2
5
]
f
o
r
co
n
tr
o
l
DC
-
D
C
b
u
ck
co
n
v
er
ter
.
T
h
e
s
lid
in
g
s
u
r
f
ac
e
is
ad
o
p
ted
to
tack
le
th
e
ef
f
ec
ts
o
f
m
atch
ed
an
d
m
i
s
m
a
tch
ed
u
n
ce
r
tai
n
tie
s
.
T
h
e
f
o
llo
w
i
n
g
s
lid
i
n
g
s
u
r
f
ac
e
is
u
s
ed
,
=
2
+
1
1
+
2
∫
1
(
4
9
)
T
h
en
I
SMC
co
n
tr
o
l la
w
w
ill b
e
as
=
[
1
0
−
2
+
1
]
1
−
1
2
−
(
)
(
5
0
)
Fo
r
b
est
co
m
p
ar
is
o
n
b
et
w
ee
n
th
ese
co
n
tr
o
ller
s
,
t
h
eir
p
ar
a
m
e
ter
s
h
a
v
e
b
ee
n
s
elec
ted
to
ac
h
iev
e
t
h
eir
o
p
tim
a
l
p
er
f
o
r
m
a
n
ce
s
.
T
h
en
,
th
e
p
ar
a
m
eter
s
o
f
t
h
ese
co
n
tr
o
ller
s
ar
e
ch
o
s
e
n
as
f
o
llo
w
s
:
1
=
1
=
30
,
2
=
275
,
an
d
2
=
=4
5
0
,
w
h
ile
t
h
e
p
r
o
p
o
s
ed
c
o
n
tr
o
lle
r
’
s
p
ar
a
m
et
er
s
elec
ted
as:
1
=
75
,
2
=
50
,
1
=
100
,
an
d
2
=
100
.
T
h
e
o
b
j
ec
tiv
e
o
f
t
h
is
w
o
r
k
is
to
k
ee
p
s
a
s
tab
le
lo
ad
v
o
ltag
e
i
n
s
p
ite
o
f
t
h
e
p
r
esen
ce
of
m
is
m
atc
h
ed
an
d
m
atch
ed
u
n
ce
r
tain
ties
.
I
n
teg
r
al
ab
s
o
l
u
te
er
r
o
r
(
I
A
E
)
,
I
n
teg
r
al
ti
m
e
ab
s
o
lu
te
er
r
o
r
(
I
T
A
E
)
,
an
d
p
er
ce
n
tag
e
o
v
er
s
h
o
o
t (
P
O)
h
av
e
b
ee
n
u
s
ed
f
o
r
th
e
p
er
f
o
r
m
an
ce
co
m
p
ar
i
s
o
n
.
=
∫
|
(
)
|
0
(
5
7
)
=
∫
|
(
)
|
0
(
5
8
)
T
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
t
h
r
ee
co
n
tr
o
ller
s
ar
e
test
ed
in
t
h
r
ee
d
if
f
er
e
n
t si
m
u
latio
n
s
ce
n
ar
io
s
.
C
ase
1
: Step
ch
a
n
g
e
o
f
th
e
lo
a
d
r
esis
tan
ce
T
h
e
r
o
b
u
s
tn
es
s
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
test
ed
b
y
ch
a
n
g
in
g
th
e
lo
ad
r
esis
ta
n
ce
f
r
o
m
1
0
0
to
6
0
at
5
s
ec
an
d
th
e
n
s
w
itc
h
to
8
5
at
1
5
s
ec
. T
h
e
r
esu
lt
s
ar
e
s
h
o
w
n
in
Fig
u
r
e
3
.
I
t i
s
s
ee
n
th
a
t t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
an
d
I
SMC
p
r
o
v
id
e
a
g
o
o
d
an
d
r
o
b
u
s
t
r
esp
o
n
s
e
w
it
h
ze
r
o
s
tead
y
tr
ac
k
in
g
er
r
o
r
ag
ai
n
s
t
t
h
e
s
tep
v
ar
iatio
n
o
f
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
S
ystem
u
n
ce
r
ta
in
ties
esti
ma
tio
n
b
a
s
ed
a
d
a
p
tive
r
o
b
u
s
t b
a
ck
s
tep
p
in
g
…
(
A
li Hu
s
s
ien
Ma
r
y
)
35
3
th
e
lo
ad
r
esis
tan
ce
.
Ho
w
e
v
e
r
,
th
e
co
n
v
en
tio
n
al
SMC
is
u
n
ab
le
to
ac
h
ie
v
e
t
h
e
d
esi
r
ed
v
o
ltag
e
d
u
e
to
th
e
u
n
m
atc
h
ed
u
n
ce
r
tai
n
t
y
.
I
n
ad
d
itio
n
,
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l
s
ch
e
m
e
r
esp
o
n
s
e
w
it
h
a
v
e
r
y
s
m
all
o
v
er
s
h
o
o
t
w
it
h
r
esp
ec
t
to
th
e
I
SM
C
,
wh
ich
r
esp
o
n
d
s
w
it
h
a
v
er
y
h
ig
h
o
v
er
s
h
o
o
t.
Mo
r
eo
v
er
,
t
h
e
co
n
tr
o
l
s
ig
n
al
o
f
th
e
p
r
o
p
o
s
ed
c
o
n
tr
o
ller
is
s
m
o
th
er
in
g
th
a
n
o
th
er
co
n
tr
o
l
s
i
g
n
al
s
.
T
ab
le
1
lis
ts
th
e
I
A
E
,
I
T
A
E
,
an
d
P
O
v
alu
es
f
o
r
all
co
n
tr
o
ller
s
.
T
h
is
tab
le
in
d
icate
s
th
e
e
f
f
ec
t
iv
e
n
es
s
o
f
all
m
e
th
o
d
s
b
u
t
w
i
th
s
l
ig
h
tl
y
b
etter
p
er
f
o
r
m
a
n
ce
f
o
r
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l sch
em
e.
Fig
u
r
e
3
.
R
esp
o
n
s
e
o
f
t
h
e
b
u
c
k
co
n
v
er
ter
w
h
en
s
u
b
j
ec
ted
to
s
tep
v
ar
y
i
n
g
lo
ad
T
ab
le
1
.
C
o
m
p
ar
is
o
n
p
er
f
o
r
m
an
ce
s
o
f
ca
s
e
1
I
A
E
I
TA
E
PO
P
r
o
p
o
se
d
0
.
4
3
3
7
0
.
1
3
2
7
0
.
0
0
0
9
I
S
M
C
0
.
7
6
6
8
0
.
3
2
3
8
0
.
0
1
1
0
C
S
M
C
2
.
1
9
6
9
0
.
6
0
2
3
0
.
0
1
3
6
C
ase
2
: Co
n
tin
u
o
u
s
v
ar
y
i
n
g
o
f
th
e
lo
ad
r
esis
tan
ce
T
o
ap
p
r
o
v
e
th
e
s
u
cc
e
s
s
es
a
n
d
r
o
b
u
s
t
n
es
s
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
l
s
c
h
e
m
e
i
n
t
h
e
p
r
esen
ce
o
f
a
co
n
tin
u
o
u
s
ti
m
e
-
v
ar
y
in
g
o
f
u
n
m
atc
h
ed
u
n
ce
r
tain
t
y
,
at
t=5
s
ec
,
th
e
lo
ad
r
esis
ta
n
c
e
is
ch
a
n
g
ed
f
r
o
m
th
e
n
o
m
i
n
al
v
al
u
e
(
1
0
0
)
to
=
100
+
50
s
in
(
)
.
T
h
e
p
er
f
o
r
m
an
ce
s
o
f
t
h
e
co
n
tr
o
ller
s
ar
e
s
h
o
w
n
i
n
Fig
u
r
e
4.
A
s
s
ee
n
,
C
SM
C
is
u
n
ab
le
to
tr
ac
k
th
e
d
esire
d
v
o
ltag
e
w
ith
h
i
g
h
o
s
cilla
tio
n
ab
o
u
t
th
e
d
esire
d
o
u
tp
u
t
v
o
ltag
e.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
I
SMC
i
s
b
etter
th
a
n
C
SMC
b
u
t
w
i
th
n
o
n
ze
r
o
s
tea
d
y
tr
ac
k
i
n
g
er
r
o
r
.
Ho
w
e
v
er
,
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l sc
h
e
m
e
p
r
o
v
id
es
g
o
o
d
an
d
r
o
b
u
s
t p
er
f
o
r
m
an
ce
w
it
h
ze
r
o
s
t
ea
d
y
tr
ac
k
i
n
g
er
r
o
r
an
d
f
a
s
t
r
esp
o
n
s
e
to
th
e
c
h
a
n
g
e
o
f
th
e
lo
ad
r
esis
ta
n
ce
.
Mo
r
eo
v
er
,
th
e
co
n
tr
o
l
s
ig
n
al
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
is
u
n
c
h
a
n
g
ed
d
esp
ite
th
e
p
r
es
en
ce
o
f
th
e
lo
ad
u
n
ce
r
tai
n
t
y
.
T
ab
le
2
lis
ts
th
e
I
A
E
,
I
T
A
E
,
a
n
d
P
O
v
alu
es
f
o
r
all
co
n
tr
o
ller
s
.
T
h
ese
v
alu
es
r
ev
ea
l
th
e
s
u
p
er
io
r
it
y
o
f
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l
m
eth
o
d
in
ter
m
s
o
f
tr
an
s
ie
n
t
s
p
ec
if
icatio
n
s
a
n
d
s
tead
y
-
s
ta
te
.
Fig
u
r
e
4
.
R
esp
o
n
s
e
o
f
t
h
e
b
u
c
k
co
n
v
er
ter
w
h
en
s
u
b
j
ec
ted
to
co
n
tin
u
o
u
s
v
ar
y
in
g
lo
ad
0
5
10
15
20
8
8
.
5
9
9
.
5
10
1
0
.
5
t
i
m
e
(
s)
o
u
t
p
u
t
V
o
l
t
a
g
e
P
r
o
p
o
se
d
C
S
M
C
I
S
M
C
0
5
10
15
20
-
0
.
1
5
-
0
.
1
-
0
.
0
5
0
0
.
0
5
0
.
1
0
.
1
5
0
.
2
t
i
m
e
(
s)
t
r
a
cki
n
g
e
r
r
o
r
p
r
o
p
o
se
d
C
S
M
C
I
S
M
C
0
5
10
15
20
8
.
5
9
9
.
5
10
1
0
.
5
t
i
m
e
(
s)
O
u
t
p
u
t
V
o
l
t
a
g
e
P
r
o
p
o
se
d
C
S
M
C
I
S
M
C
0
5
10
15
20
-
0
.
1
-
0
.
0
5
0
0
.
0
5
0
.
1
0
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1
5
0
.
2
t
i
m
e
(
s)
t
r
a
cki
n
g
e
r
r
o
r
p
r
o
p
o
se
d
C
S
M
C
I
S
M
C
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.
11
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
1
:
347
-
355
354
T
ab
le
2
.
C
o
m
p
ar
is
o
n
p
er
f
o
r
m
an
ce
s
o
f
ca
s
e
2
I
A
E
I
TA
E
PO
P
r
o
p
o
se
d
0
.
1
8
8
6
0
.
0
3
6
6
0
.
0
0
0
7
I
S
M
C
0
.
4
0
1
5
2
.
3
2
9
0
0
.
0
1
3
6
CS
M
C
1
.
3
5
7
6
1
4
.
0
4
6
2
0
.
0
0
4
2
C
ase
3
: Step
ch
a
n
g
e
o
f
th
e
i
n
p
u
t
v
o
lta
g
e
R
o
b
u
s
t
n
es
s
to
th
e
m
atch
ed
u
n
ce
r
tain
t
y
i
s
c
h
ec
k
ed
b
y
c
h
a
n
g
i
n
g
D
C
v
o
ltag
e
f
r
o
m
2
4
V
to
2
0
V
at
t=4
s
ec
an
d
t
h
en
d
r
o
p
to
1
8
V
at
t=1
0
s
ec
.
th
e
s
i
m
u
latio
n
r
e
s
p
o
n
s
e
to
t
h
e
m
atc
h
ed
u
n
ce
r
tain
t
y
w
h
ich
r
ep
r
ese
n
ted
b
y
t
h
e
s
tep
ch
a
n
g
e
o
f
th
e
in
p
u
t
v
o
lta
g
e
is
s
h
o
w
n
i
n
Fi
g
u
r
e
5
an
d
p
er
o
m
an
ce
i
n
d
ex
e
s
lis
ted
in
T
ab
le
3
.
As
ex
p
ec
t
ed
,
d
u
e
to
th
e
in
h
er
en
t
s
tab
ilit
y
o
f
SM
C
an
d
I
SM
C
,
th
e
p
er
f
o
r
m
a
n
ce
s
o
f
t
h
ese
co
n
tr
o
ller
s
ac
h
ie
v
e
g
o
o
d
p
er
f
o
r
m
a
n
ce
s
an
d
s
tr
o
n
g
r
o
b
u
s
t
n
es
s
a
g
ai
n
s
t
th
e
m
atc
h
ed
u
n
ce
r
tai
n
ties
w
h
en
th
e
m
atch
e
d
u
n
ce
r
tai
n
t
y
r
e
m
ain
s
u
n
d
er
th
e
u
p
p
er
b
o
u
n
d
o
f
u
n
ce
r
tai
n
t
y
.
Fig
u
r
e
5
s
h
o
w
s
t
h
e
u
n
d
esire
d
tr
an
s
ie
n
ts
r
esp
o
n
s
e
o
f
th
e
I
S
MC
at
t=
4
s
ec
d
u
e
to
th
e
h
ig
h
o
v
er
s
h
o
o
t
to
th
e
tr
an
s
ie
n
t
r
esp
o
n
s
e
o
f
t
h
e
p
r
o
p
o
s
ed
c
o
n
tr
o
ller
.
T
h
e
p
r
o
b
lem
ap
p
ea
r
s
if
th
e
m
a
g
n
i
t
u
d
e
o
f
th
e
m
atch
ed
u
n
ce
r
tai
n
t
y
is
g
r
ea
ter
th
a
n
t
h
e
s
w
itch
in
g
g
ain
.
I
n
th
i
s
ca
s
e
,
th
e
o
u
tp
u
t
v
o
lta
g
e
o
f
C
SM
C
w
ill
b
e
u
n
ab
le
to
tr
ac
k
th
e
d
esire
d
v
o
lta
g
e
,
as
s
h
o
w
n
i
n
Fi
g
u
r
e
5
w
h
e
n
th
e
i
n
p
u
t
v
o
ltag
e
c
h
a
n
g
e
s
to
2
0
at
t=1
4
s
ec
.
I
n
o
th
er
w
o
r
d
s
,
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l
s
ch
e
m
e
p
r
o
v
id
es
g
o
o
d
p
er
f
o
r
m
an
ce
s
an
d
k
ee
p
s
a
s
tab
le
o
u
tp
u
t
v
o
lta
g
e
w
it
h
a
v
er
y
s
h
o
r
t
ti
m
e
tr
an
s
ien
t
at
t
=4
s
ec
an
d
t=1
0
s
ec
in
w
h
ich
th
e
i
n
p
u
t
v
o
lta
g
e
h
ad
b
ee
n
c
h
an
g
ed
.
Mo
r
eo
v
er
,
th
e
co
n
tr
o
l
s
i
g
n
al
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
l
i
s
v
er
y
s
m
o
o
th
co
n
ce
r
n
i
n
g
t
h
e
C
SM
C
a
n
d
SMC
,
w
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ic
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RE
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NC
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[1
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N.I
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P
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DC
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DC b
u
c
k
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v
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rter,”
IS
A
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ra
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ti
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s,
2
0
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0
.
[2
]
S
.
K.
P
a
n
d
e
y
,
e
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l
,
“
Ro
b
u
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slid
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355
[3
]
P
.
Da
i,
S
.
Ca
u
e
t,
a
n
d
P
.
Co
ira
u
lt
,
“
Distu
rb
a
n
c
e
re
jec
ti
o
n
o
f
b
a
tt
e
ry
/u
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a
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h
y
b
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n
e
rg
y
so
u
rc
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s,”
Co
n
tro
l
En
g
i
n
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rin
g
Pra
c
ti
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e
,
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l.
5
4
,
p
p
.
1
6
6
-
1
7
5
,
2
0
1
6
.
[4
]
W
.
Qi,
S
.
L
i,
S
.
T
a
n
,
S
.
R.
H
u
i,
“
P
a
ra
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o
li
c
-
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late
d
sli
d
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n
g
-
m
o
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e
c
o
n
tr
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b
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k
c
o
n
v
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rter,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
stri
a
l
El
e
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tr
o
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ics
,
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l
.
6
5
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o
.
1
,
p
p
.
8
4
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5
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2
0
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8
.
[5
]
Z.
T
ian
,
Z.
Ly
u
,
J.
Yu
a
n
,
C.
W
a
n
g
,
“
UDE
-
b
a
s
e
d
slid
in
g
m
o
d
e
c
o
n
tr
o
l
o
f
DC
–
DC
p
o
w
e
r
c
o
n
v
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it
h
u
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c
e
rtain
ti
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s,”
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n
tro
l
E
n
g
i
n
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Pr
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o
.
8
3
,
p
p
.
116
-
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8
,
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9
.
[6
]
Z.
Ch
e
n
,
W
.
G
a
o
,
J
.
Hu
,
X.
Ye
,
“
Clo
se
d
-
lo
o
p
a
n
a
ly
sis
a
n
d
c
a
sc
a
d
e
c
o
n
tro
l
o
f
a
n
o
n
m
in
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m
p
h
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se
b
o
o
st
c
o
n
v
e
rter,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
p
o
we
r e
lec
tro
n
ics
,
v
o
l.
2
6
,
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o
.
4
,
p
p
.
1
2
3
7
-
1
2
5
2
,
2
0
1
1
.
[7
]
M
Ra
n
jan
i,
a
n
d
P
M
u
ru
g
e
sa
n
.
,
“
Op
ti
m
a
l
f
u
z
z
y
c
o
n
tro
ll
e
r
p
a
ra
m
e
ters
u
sin
g
P
S
O
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sp
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e
d
c
o
n
tro
l
o
f
Qu
a
si
-
Z
So
u
rc
e
DC/DC c
o
n
v
e
rter f
e
d
d
riv
e
,
”
Ap
p
li
e
d
S
o
ft
C
o
mp
u
ti
n
g
,
v
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l.
1
,
n
o
.
2
7
,
p
p
.
3
3
2
-
56
,
2
0
1
5
.
[8
]
S
R
Re
x
,
a
n
d
DMM
S
R
P
ra
b
a
,
“
De
sig
n
o
f
P
W
M
w
it
h
f
o
u
r
tran
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r
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o
m
p
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r
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to
r
f
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r
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–
DC
b
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st
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v
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rters
,
”
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ro
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e
ss
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rs
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n
d
M
icr
o
sy
ste
ms
,
v
o
l.
7
2
,
2
0
2
0
.
[9
]
M
M
o
u
tch
o
u
,
a
n
d
A
Jb
a
ri
,
“
F
a
st
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h
o
t
o
v
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lt
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ic
In
c
Co
n
d
-
M
P
P
T
a
n
d
b
a
c
k
ste
p
p
in
g
c
o
n
tr
o
l,
u
sin
g
DC
-
DC
b
o
o
st
c
o
n
v
e
rter,”
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
C
o
mp
u
te
r
En
g
i
n
e
e
rin
g
(
IJ
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)
,
v
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l.
1
0
,
n
o
.
1
,
p
p
.
1
1
0
1
-
1
1
1
2
,
2
0
2
0
.
[1
0
]
RA
.
K
a
d
h
im
,
“
De
s
ig
n
a
n
d
s
im
u
la
ti
o
n
o
f
c
l
o
se
d
l
o
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p
p
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t
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ra
l
(
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I
)
c
o
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t
r
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l
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d
b
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s
t
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o
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v
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te
r
a
n
d
3
-
p
h
a
s
e
i
n
v
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t
e
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f
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t
o
v
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l
t
a
i
c
(
P
V)
a
p
p
l
i
c
a
t
i
o
n
s
,
”
Al
-
K
h
w
a
r
i
zm
i
E
n
g
i
n
e
e
r
in
g
J
o
u
r
n
a
l
,
v
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l
.
1
5
,
n
o
.
1
,
p
p
.
10
-
22
,
2
0
1
9
.
[1
1
]
T
.
M
.
A
li
,
a
n
d
B
.
M
.
H
.
Ja
ss
i
m
,
“
M
o
d
e
li
n
g
a
n
d
S
im
u
la
ti
o
n
o
f
S
e
n
so
rles
s
S
p
e
e
d
Co
n
tr
o
l
o
f
a
Bu
c
k
Co
n
v
e
rter
Co
n
tr
o
ll
e
d
Dc
M
o
t
o
r,
”
Al
-
K
h
wa
ri
zm
i
En
g
i
n
e
e
rin
g
J
o
u
r
n
a
l,
v
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l.
6
,
n
o
.
1
,
p
p
.
8
0
-
8
7
,
2
0
1
0
.
[1
2
]
S
in
g
h
,
G
.
a
n
d
Ku
n
d
u
,
S
.
,
“
A
n
e
ff
ici
e
n
t
DC
-
DC
b
o
o
st
c
o
n
v
e
rter
f
o
r
th
e
r
m
o
e
lec
tri
c
e
n
e
rg
y
h
a
rv
e
stin
g
,
”
AEU
-
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
tro
n
i
c
s a
n
d
Co
mm
u
n
ica
ti
o
n
s,
v
o
l.
1
1
8
,
2
0
2
0
.
[1
3
]
Ku
m
a
r
,
S
.
a
n
d
V
ij
a
y
a
k
u
m
a
r,
K.
,
“
S
im
u
latio
n
a
n
d
e
x
p
e
rim
e
n
tal
c
o
m
p
a
ra
ti
v
e
a
n
a
l
y
sis
o
f
th
e
DC
-
DC
c
o
n
v
e
rter
to
p
o
lo
g
ies
f
o
r
w
i
n
d
d
riv
e
n
S
EIG
f
e
d
DC n
a
n
o
g
rid
,
”
El
e
c
tric P
o
we
r S
y
ste
ms
Re
se
a
rc
h
,
v
o
l.
1
8
1
,
2
0
2
0
.
[1
4
]
M
.
H
.
M
iry
,
A
.
H
.
M
ir
y
,
H
.
K
.
Kh
lea
f
,
“
A
d
a
p
ti
v
e
n
o
ise
c
a
n
c
e
ll
a
ti
o
n
f
o
r
sp
e
e
c
h
e
m
p
lo
y
in
g
f
u
z
z
y
a
n
d
n
e
u
ra
l
n
e
tw
o
rk
,
”
1
st i
n
ter
n
a
ti
o
n
C
o
n
fer
e
n
c
e
o
n
En
e
rg
y
,
p
o
we
r
a
n
d
Co
n
tro
l
(
EP
C
-
IQ),
2
0
1
0
.
[1
5
]
A
.
H
.
M
a
r
y
,
“
G
e
n
e
rialize
d
P
ID
c
o
n
tro
ll
e
r
b
a
se
d
o
n
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
”
Ira
q
i
J
o
u
r
n
a
l
o
f
C
o
mp
u
ter
s,
Co
mm
u
n
ica
ti
o
n
a
n
d
Co
n
tro
l
&
S
y
ste
ms
En
g
in
e
e
rin
g
,
v
o
l.
1
1
,
n
o
.
1
,
p
p
.
1
1
4
-
1
2
2
,
2
0
1
1
.
[1
6
]
A
.
H
.
M
ir
y
,
A
.
H
.
M
a
r
y
,
M
.
H
.
M
iry
,
“
M
ix
e
d
ro
b
u
st
c
o
n
tro
ll
e
r
w
it
h
o
p
ti
m
ize
d
w
e
ig
h
ted
se
le
c
ti
o
n
fo
r
a
DC
se
rv
o
m
o
to
r,
”
Pro
c
e
.
o
f
th
e
In
t.
C
o
n
fer
e
n
c
e
o
n
I
n
f
o
rm
a
ti
o
n
a
n
d
Co
mm
u
n
i
c
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
,
p
p
.
1
7
8
-
1
8
3
,
2
0
1
9
.
[1
7
]
A
.
H.
M
ir
y
,
A
.
H
.
M
a
r
y
,
M
.
H
.
M
ir
y
,
“
I
m
p
ro
v
in
g
o
f
m
a
x
i
m
u
m
p
o
we
r
p
o
in
t
trac
k
in
g
f
o
r
p
h
o
to
v
o
l
taic
s
y
ste
m
s
b
a
se
d
o
n
sw
a
r
m
o
p
ti
m
iza
ti
o
n
tec
h
n
i
q
u
e
s,”
IOP
Co
n
fer
e
n
c
e
S
e
rie
s:
M
a
ter
ia
ls
S
c
ien
c
e
a
n
d
E
n
g
in
e
e
rin
g
,
v
o
l.
5
1
8
,
n
o
.
4
,
2
0
1
9
.
[1
8
]
A
.
H
.
M
a
r
y
,
T
.
Ka
r
a
,
A
.
H.
M
ir
y
.
,
“
In
v
e
rse
k
in
e
m
a
ti
c
s
so
lu
ti
o
n
f
o
r
ro
b
o
ti
c
m
a
n
ip
u
lat
o
rs
b
a
se
d
o
n
f
u
z
z
y
lo
g
ic
a
n
d
P
D
c
o
n
tr
o
l,
”
Al
-
S
a
d
e
q
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
u
lt
id
isc
ip
li
n
a
ry
i
n
IT
a
n
d
Co
mm
u
n
ica
ti
o
n
S
c
ien
c
e
a
n
d
Ap
p
li
c
a
ti
o
n
s (
AIC
-
M
IT
CS
A),
p
p
.
1
-
6
,
2
0
1
6
.
[1
9
]
T
.
Ka
ra
,
A
.
H
.
M
a
ry
,
“
Ro
b
u
st
traje
c
to
ry
trac
k
in
g
c
o
n
tro
l
o
f
ro
b
o
ti
c
m
a
n
ip
u
lat
o
rs
b
a
se
d
o
n
m
o
d
e
l
-
fre
e
P
ID
-
S
M
C
a
p
p
ro
a
c
h
,
”
J
o
u
rn
a
l
o
f
E
n
g
in
e
e
rin
g
Res
e
a
rc
h
,
v
o
l
.
6
,
n
o
.
3
,
p
p
.
1
7
0
-
1
8
8
,
2
0
1
8
.
[2
0
]
T
.
Ka
r
a
,
A
.
H
.
M
a
r
y
,
“
F
e
e
d
b
a
c
k
-
b
a
se
d
IKP
so
l
u
ti
o
n
w
it
h
S
M
C
f
o
r
ro
b
o
ti
c
m
a
n
ip
u
lato
rs:
T
h
e
S
CA
R
A
e
x
a
m
p
le,”
In
ter
n
a
t
io
n
a
l
Ad
v
a
n
c
e
d
Res
e
a
rc
h
e
s a
n
d
En
g
i
n
e
e
rin
g
J
o
u
rn
a
l,
v
o
l
.
2
,
n
o
.
1
,
p
p
.
27
-
3
2
,
2
0
1
8
.
[2
1
]
T
.
Ka
ra
,
A
.
H
.
M
a
r
y
.,
“
A
d
a
p
ti
v
e
P
D
-
S
M
C
f
o
r
No
n
li
n
e
a
r
Ro
b
o
t
ic
M
a
n
ip
u
lato
r
T
ra
c
k
in
g
Co
n
tro
l,
”
S
t
u
d
ies
in
In
fo
rm
a
t
ics
a
n
d
C
o
n
tr
o
l,
v
o
l
.
1
,
n
o
.
2
6
,
p
p
.
4
9
-
5
8
,
2
0
1
7
.
[2
2
]
A
.
H
.
M
a
r
y
,
T
.
K
a
ra
,
“
Ro
b
u
s
t
p
r
o
p
o
rti
o
n
a
l
c
o
n
tr
o
l
f
o
r
traje
c
to
ry
trac
k
in
g
o
f
a
n
o
n
li
n
e
a
r
ro
b
o
ti
c
m
a
n
ip
u
lato
r:
L
M
I
o
p
ti
m
iza
ti
o
n
a
p
p
ro
a
c
h
,
”
Ara
b
ia
n
J
o
u
rn
a
l
f
o
r S
c
ien
c
e
a
n
d
En
g
in
e
e
r
in
g
,
v
o
l.
4
1
,
n
o
.
1
2
,
p
p
.
5
0
2
7
-
5
0
3
6
,
2
0
1
6
.
[2
3
]
S
.
Ou
c
h
e
riah
,
L
.
G
u
o
,
“
P
W
M
-
b
a
se
d
a
d
a
p
ti
v
e
slid
i
n
g
-
m
o
d
e
c
o
n
tro
l
f
o
r
b
o
o
st
DC
–
DC
c
o
n
v
e
rters
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
stri
a
l
El
e
c
tr
o
n
ics
,
v
o
l
.
6
0
,
n
o
.
8
,
p
p
.
3
2
9
1
-
3
2
9
4
,
2
0
1
3
.
[2
4
]
W
.
H.
Ch
e
,
“
Distu
rb
a
n
c
e
o
b
se
rv
e
r
b
a
se
d
c
o
n
tro
l
f
o
r
n
o
n
l
in
e
a
r
sy
ste
m
s,”
IEE
E/
AS
M
E
tra
n
s
a
c
ti
o
n
s
o
n
me
c
h
a
tro
n
ics
,
v
o
l.
9
,
n
o
.
4
,
p
p
.
7
0
6
-
7
1
0
,
2
0
0
4
.
[2
5
]
Y.
P
a
n
,
C.
Ya
n
g
,
L
.
P
a
n
,
H.
Yu
,
“
In
teg
ra
l
slid
in
g
m
o
d
e
c
o
n
tro
l:
p
e
rf
o
r
m
a
n
c
e
,
m
o
d
if
ica
ti
o
n
,
a
n
d
im
p
ro
v
e
m
e
n
t,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
stri
a
l
In
fo
rm
a
t
ics
,
v
o
l.
1
4
,
n
o
.
7
,
p
p
.
3
0
8
7
-
9
6
,
2
0
1
8
.
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