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rica
l En
g
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m
p
u
t
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Science
Vo
l.
10
,
No
.
2
,
May
201
8
,
p
p
.
713
~7
2
4
I
SS
N:
2502
-
4752
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m
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1.
I
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RO
D
UCT
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N
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eleo
p
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y
s
te
m
s
ex
ten
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th
e
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u
m
a
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p
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ato
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ca
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ab
ilit
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to
p
er
f
o
r
m
ta
s
k
at
th
e
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e
m
o
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s
ite.
I
n
g
en
er
al,
th
e
teleo
p
er
atio
n
s
y
s
te
m
s
ca
n
b
e
ca
te
g
o
r
ized
in
to
b
ilater
al
teleo
p
er
atio
n
[
1
]
an
d
m
u
ltil
ater
al
teleo
p
er
atio
n
[
2
]
,
[
3
]
.
T
o
p
r
o
p
er
ly
co
n
tr
o
l
th
e
m
u
lt
il
ater
a
l
teleo
p
er
atio
n
s
y
s
te
m
p
o
s
e
s
o
m
e
ch
al
len
g
es,
esp
ec
iall
y
w
h
e
n
w
e
co
n
s
id
er
a
s
in
g
le
m
a
s
ter
w
it
h
m
u
lti
-
s
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v
es
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n
f
i
g
u
r
atio
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.
Ge
n
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all
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e
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ad
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ate
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r
ee
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of
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o
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as
t
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e
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e
f
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y
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a
n
ip
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l
ate
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s
la
v
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s
id
e,
h
e
n
ce
r
eq
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ir
es
t
h
e
s
la
v
es
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e
a
ce
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tai
n
d
eg
r
ee
o
f
s
el
f
-
c
o
n
tr
o
l.
T
o
ad
d
r
ess
th
e
is
s
u
e
s
r
elate
d
to
th
e
m
u
l
tilater
al
te
leo
p
er
atio
n
,
w
e
f
o
cu
s
o
n
t
w
o
m
ain
q
u
es
tio
n
s
:
1
)
Ho
w
ca
n
w
e
tr
ea
t
a
m
u
ltil
ater
al
s
y
s
te
m
as
a
b
ilater
al
s
y
s
te
m
?
,
an
d
2
)
I
s
t
h
er
e
an
y
m
ec
h
a
n
i
s
m
t
h
at
ca
n
b
e
im
p
le
m
en
ted
to
im
p
r
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e
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h
e
tr
an
s
p
ar
en
c
y
(
i.e
.
,
to
p
r
o
v
id
e
a
f
aith
f
u
l
tr
an
s
m
i
s
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io
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o
f
f
o
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ce
an
d
v
elo
cit
y
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b
et
w
ee
n
t
h
e
m
aster
an
d
m
u
ltip
le
-
s
la
v
es i
n
a
4
-
ch
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n
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els
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tr
u
ct
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r
e?
T
h
e
f
ac
ts
t
h
at
m
an
y
w
o
r
k
s
h
a
v
e
b
ee
n
d
o
n
e
i
n
th
e
p
as
t f
o
c
u
s
in
g
o
n
t
h
e
b
ilater
al
teleo
p
er
atio
n
s
[
4
]
–
[
6
]
,
th
en
co
n
v
er
ti
n
g
th
e
m
u
l
tilate
r
al
teleo
p
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atio
n
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te
m
to
s
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it
th
e
e
x
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tin
g
b
ilater
al
s
tr
u
ctu
r
e,
o
f
f
er
s
s
o
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e
ad
v
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ta
g
es
i
n
ter
m
s
o
f
t
h
e
co
n
tr
o
ller
d
esig
n
.
Fu
r
t
h
er
m
o
r
e,
as
th
e
to
tal
d
y
n
a
m
ic
s
o
f
s
la
v
e
m
an
ip
u
lato
r
s
ca
n
b
e
ch
an
g
ed
(
i.e
.
,
ad
d
in
g
o
r
s
u
b
tr
ac
tin
g
s
la
v
e
m
a
n
ip
u
lato
r
s
,
o
r
to
estab
lis
h
n
e
w
co
n
f
ig
u
r
atio
n
o
n
t
h
e
co
m
m
u
n
icatio
n
to
p
o
lo
g
y
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etw
ee
n
ag
e
n
t
s
)
,
it
is
ce
r
tain
l
y
co
s
t
in
e
f
f
ic
ien
t
if
t
h
e
d
y
n
a
m
ics
o
f
th
e
m
a
s
ter
m
an
ip
u
lato
r
h
as
al
s
o
to
b
e
r
ed
esig
n
ed
w
h
e
n
e
v
er
th
e
d
y
n
a
m
ic
s
o
f
s
la
v
e
m
a
n
ip
u
lat
o
r
s
h
av
e
ch
a
n
g
ed
.
T
h
er
ef
o
r
e,
b
y
in
tr
o
d
u
ci
n
g
a
s
i
n
g
le
t
u
n
ab
le
eq
u
alize
r
to
th
e
m
aster
s
id
e
r
en
d
er
s
f
le
x
ib
ilit
y
to
ad
j
u
s
t
th
e
o
v
er
all
d
y
n
a
m
ics
o
f
th
e
m
a
s
ter
m
a
n
ip
u
lato
r
to
ac
h
iev
e
s
y
m
m
etr
y
b
et
w
ee
n
b
o
th
s
id
es
o
f
tele
o
p
er
atio
n
.
B
y
th
is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
10
,
No
.
2
,
Ma
y
2
0
1
8
:
7
1
3
–
7
2
4
714
ap
p
r
o
ac
h
,
th
e
s
y
s
te
m
d
es
ig
n
e
r
r
eq
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ir
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o
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l
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n
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ass
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v
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d
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o
m
p
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s
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n
t
ec
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n
iq
u
e[
7
]
to
co
n
v
er
t
th
e
m
u
ltil
ater
al
teleo
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atio
n
s
y
s
te
m
i
n
to
th
e
b
ilater
al
f
o
r
m
.
Sin
ce
t
h
e
w
h
o
l
e
tele
o
p
er
atio
n
p
r
o
ce
s
s
ca
n
b
e
s
ep
ar
ated
in
to
tw
o
o
p
er
atio
n
s
,
n
a
m
el
y
g
r
asp
in
g
an
d
h
a
n
d
li
n
g
,
w
e
u
s
e
t
h
e
s
u
b
-
d
y
n
a
m
ic
s
f
r
o
m
th
e
r
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u
lt
o
f
d
ec
o
m
p
o
s
it
io
n
to
d
eter
m
in
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h
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ti
m
e
(
o
r
in
o
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r
ca
s
e,
)
,
th
at
d
if
f
er
e
n
tiate
s
t
h
e
ti
m
e
in
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er
v
a
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atch
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o
th
s
id
es o
f
teleo
p
er
atio
n
.
Du
e
to
t
h
e
o
r
th
o
n
o
r
m
a
l
p
r
o
p
er
ties
o
f
t
h
e
L
ag
u
er
r
e
f
u
n
cti
o
n
,
th
e
eq
u
al
izer
ca
n
b
e
r
ea
l
ized
b
y
a
L
a
g
u
er
r
e
n
et
w
o
r
k
o
f
h
ig
h
o
r
d
er
o
f
m
o
d
er
atel
y
d
a
m
p
ed
s
y
s
te
m
[
8
]
.
I
n
m
o
s
t
ap
p
licati
o
n
s
,
th
e
o
p
ti
m
u
m
s
tr
u
ct
u
r
e
o
f
t
h
is
n
et
w
o
r
k
ca
n
b
e
o
b
tain
ed
b
y
s
i
m
p
l
y
s
elec
ti
n
g
th
e
o
p
ti
m
al
v
alu
e
s
f
o
r
t
h
e
b
asis
o
f
t
h
e
L
a
g
u
er
r
e
f
ilter
s
[
9
]
.
T
h
e
eq
u
alize
r
s
h
o
u
l
d
b
e
p
r
o
p
er
ly
t
u
n
ed
to
i
m
p
r
o
v
e
th
e
o
v
er
all
p
er
f
o
r
m
a
n
ce
.
He
n
ce
,
w
e
ad
o
p
ted
th
e
so
-
ca
lled
Ficti
tio
u
s
-
R
e
f
er
en
ce
-
I
ter
ativ
e
T
u
n
in
g
(
F
R
I
T
)
alg
o
r
ith
m
in
o
u
r
p
r
o
b
le
m
f
o
r
m
u
la
tio
n
.
Un
l
ik
e
o
t
h
er
tu
n
in
g
alg
o
r
it
h
m
s
w
h
ich
r
eq
u
ir
es
m
at
h
e
m
a
tical
m
o
d
el
o
f
th
e
p
lan
t
p
r
io
r
t
u
n
in
g
,
FR
I
T
u
tili
ze
s
th
e
m
ea
s
u
r
ed
in
p
u
t
-
a
n
d
-
o
u
tp
u
t
d
ata
to
s
i
m
u
ltan
eo
u
s
l
y
attai
n
th
e
p
la
n
t
m
o
d
el
an
d
th
e
o
p
ti
m
u
m
co
n
tr
o
ll
er
p
ar
am
eter
s
[
1
0
]
.
I
n
ter
esti
n
g
l
y
,
it r
eq
u
ir
es o
n
l
y
a
s
in
g
le
-
s
h
o
t o
f
m
ea
s
u
r
e
m
e
n
t
d
ata
f
o
r
th
is
p
u
r
p
o
s
e[
1
1
]
.
2.
P
RO
B
L
E
M
F
O
R
M
UL
AT
I
O
N
2
.
1
.
N
o
t
a
t
io
ns
a
nd
g
ra
ph
t
he
o
ry
L
et
an
d
d
en
o
tes
t
h
e
s
et
o
f
r
ea
l
n
u
m
b
er
s
a
n
d
v
ec
to
r
s
o
f
d
i
m
en
s
io
n
,
r
esp
ec
tiv
el
y
.
L
et
b
e
a
v
ec
to
r
w
ith
all
ele
m
en
ts
o
f
an
d
is
th
e
tr
an
s
p
o
s
itio
n
.
W
e
u
s
e
to
d
en
o
te
th
e
id
en
tit
y
m
atr
i
x
.
T
o
d
en
o
te
th
e
in
n
er
an
d
cr
o
s
s
p
r
o
d
u
cts
f
o
r
,
w
e
u
s
e
an
d
,
r
esp
ec
tiv
el
y
.
T
h
e
v
ec
to
r
n
o
r
m
is
d
ef
i
n
ed
b
y
,
an
d
i
m
p
lies
Fo
r
an
d
,
th
e
Kr
o
n
ec
k
er
p
r
o
d
u
ct
is
d
ef
in
ed
b
y
Fo
r
n
u
m
b
er
o
f
a
g
en
t
s
,
a
g
r
ap
h
is
b
u
ilt
u
p
o
n
a
f
in
ite
s
et
ca
l
led
a
ve
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tex
s
e
t
m
ap
p
ed
b
y
an
d
th
e
ed
g
e
s
et
o
f
.
W
e
s
ay
if
t
h
er
e
is
a
co
m
m
u
n
icat
io
n
lin
k
b
et
w
ee
n
th
e
m
.
A
d
d
itio
n
all
y
,
is
t
h
e
n
eig
h
b
o
r
h
o
o
d
s
et
o
f
.
T
h
e
r
elatio
n
s
h
ip
b
et
w
ee
n
f
o
r
an
u
n
d
ir
ec
ted
g
r
ap
h
is
en
co
d
ed
b
y
t
h
e
ad
j
ac
en
c
y
m
a
tr
ix
,
w
h
er
e
T
h
e
d
eg
r
ee
m
atr
i
x
is
a
d
iag
o
n
al
m
atr
i
x
t
h
at
w
it
h
,
an
d
is
th
e
ca
r
d
in
alit
y
o
f
.
T
h
e
L
ap
lacia
n
m
atr
ix
as
s
o
ciate
d
w
it
h
i
s
d
ef
in
ed
b
y
[
1
2
]
:
2
.
2
.
T
eleo
pera
t
io
n a
rc
hite
ct
u
re
W
e
co
n
s
id
er
a
s
i
m
p
le
ag
e
n
t
as
th
e
m
a
s
ter
m
a
n
ip
u
lato
r
g
o
v
er
n
ed
b
y
th
e
eq
u
at
io
n
o
f
m
o
tio
n
C
o
n
v
er
s
el
y
,
th
e
s
la
v
e
m
a
n
i
p
u
lato
r
s
d
ep
icted
b
y
a
n
et
w
o
r
k
o
f
a
g
en
ts
s
u
c
h
t
h
at
e
ac
h
a
g
en
t
m
o
v
es
d
y
n
a
m
icall
y
t
h
r
o
u
g
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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esia
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E
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&
C
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N:
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4752
Da
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ig
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ar
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ip
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an
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o
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ap
p
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o
f
t
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u
m
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ato
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m
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er
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ch
a
g
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t
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h
e
f
o
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ce
is
th
e
esti
m
a
ted
en
v
ir
o
n
m
e
n
t
’
s
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o
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ce
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t
b
y
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c
h
ag
en
t
at
its
p
o
s
itio
n
r
elati
v
e
t
o
th
e
ce
n
ter
-
of
-
m
a
s
s
(
C
o
M)
o
f
th
e
en
v
ir
o
n
m
e
n
t.
T
h
e
o
b
j
ec
t
in
th
e
e
n
v
ir
o
n
m
e
n
t
is
co
n
s
id
er
ed
to
b
e
a
s
o
lid
d
is
k
o
f
r
ad
iu
s
th
a
t
m
o
v
es
o
n
a
s
lid
in
g
f
lat
s
u
r
f
ac
e.
A
s
s
u
m
i
n
g
th
at
al
l
ag
en
t
s
ar
e
f
r
ictio
n
-
less
(
i.e
.
,
th
e
y
m
o
v
e
o
n
f
r
ictio
n
-
le
s
s
wh
ee
ls
)
,
th
e
f
r
ict
io
n
f
o
r
ce
o
n
l
y
ex
is
t
s
b
et
w
ee
n
th
e
co
n
tact
o
f
th
e
d
is
k
an
d
th
e
s
l
id
in
g
s
u
r
f
ac
e.
T
h
e
d
esire
d
f
in
al
p
o
s
itio
n
o
f
ea
c
h
ag
en
t
o
n
th
e
e
n
v
ir
o
n
m
e
n
t i
s
d
ef
i
n
ed
as
w
h
er
e
is
th
e
d
esire
d
an
g
u
lar
p
o
s
itio
n
o
f
,
an
d
.
Me
an
w
h
il
e,
is
th
e
e
n
v
ir
o
n
m
e
n
t
's n
o
m
in
a
l a
n
g
u
lar
d
is
p
lace
m
en
t
u
s
ed
i
n
(
7
)
.
Fo
r
b
r
ev
it
y
,
w
e
d
r
o
p
th
e
tim
e
n
o
tatio
n
(
a)
I
m
p
ed
an
ce
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tc
h
in
g
b
et
wee
n
Ma
s
ter
an
d
L
o
c
k
ed
S
y
s
te
m
.
(
b
)
Velo
cities
Ma
tch
in
g
t
h
r
o
u
g
h
.
Fig
u
r
e
1
Gen
er
al
Stru
c
tu
r
e
o
f
T
eleo
p
er
atio
n
I
n
d
icatin
g
t
h
e
E
q
u
alize
r
an
d
I
n
ter
v
e
n
ien
t I
m
p
ed
an
ce
s
,
&
.
Fig
u
r
e
2
C
o
n
ce
p
t
o
f
I
m
p
ed
an
ce
Ma
tch
i
n
g
b
y
FR
I
T
.
in
m
o
s
t
eq
u
atio
n
s
,
b
u
t
u
s
e
s
o
w
h
en
e
v
er
to
e
m
p
h
asize
i
ts
ti
m
e
-
v
ar
y
in
g
p
r
o
p
er
ty
.
De
f
i
n
i
n
g
as
th
e
f
r
ict
io
n
f
o
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ce
,
th
e
d
y
n
a
m
ica
l e
q
u
atio
n
o
f
th
e
o
b
j
ec
t is d
en
o
ted
b
y
w
h
er
e
an
d
ar
e
t
h
e
m
a
s
s
an
d
C
o
M
'
s
p
o
s
i
tio
n
o
f
th
e
tar
g
et/o
b
j
ec
t,
r
esp
ec
tiv
el
y
.
T
h
e
f
o
r
ce
an
d
to
r
q
u
e
in
(
7
)
ar
e
d
ef
in
ed
b
y
an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
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2
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716
3.
M
UL
T
I
L
A
T
E
RAL
T
O
B
I
L
AT
E
RAL
T
E
L
E
O
P
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RA
T
I
O
N
3
.
1
.
T
o
t
a
l
Dy
na
m
ics
o
f
t
he
S
la
v
e
Ag
ent
s
Fo
llo
w
i
n
g
Ka
w
a
k
a
m
i &
Na
m
er
ik
a
w
a
[
1
3
]
an
d
to
u
s
e
(
6
)
,
w
e
in
tr
o
d
u
ce
a
ch
a
n
g
e
o
f
v
ar
iab
l
es a
s
T
h
e
f
o
r
ce
in
(
5
)
ca
n
b
e
s
e
p
ar
ated
in
to
t
w
o
co
n
tr
o
l
co
m
p
o
n
en
ts
d
ep
en
d
i
n
g
o
n
th
e
ti
m
e
in
ter
v
al,
i.e
.
,
g
r
asp
in
g
a
n
d
h
an
d
li
n
g
.
W
e
ex
p
r
ess
w
h
er
e
an
d
ar
e
th
e
f
o
r
m
a
tio
n
an
d
teleo
p
er
atio
n
co
n
tr
o
l la
w
s
,
r
esp
ec
tiv
el
y
.
T
h
e
co
n
s
e
n
s
u
s
co
n
tr
o
l la
w
is
u
s
ed
to
ac
h
iev
e
s
i
m
u
lta
n
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u
s
g
r
asp
i
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g
.
Her
e
if
ca
n
m
e
asu
r
e
it
s
r
elati
v
e
p
o
s
itio
n
s
a
n
d
v
elo
cit
y
w
it
h
r
esp
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t
to
o
b
j
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t'
s
C
o
M,
an
d
o
th
er
w
is
e.
T
h
e
g
a
in
co
r
r
esp
o
n
d
s
to
th
e
co
m
m
u
n
icat
io
n
to
p
o
lo
g
y
d
e
f
in
ed
i
n
(
2
)
,
w
h
i
le
th
e
v
ar
iab
les
ar
e
th
e
co
n
tr
o
l g
ain
s
.
T
h
e
g
ai
n
is
d
ef
in
ed
b
y
Su
b
s
ti
tu
t
in
g
(
8
)
an
d
(
10
)
in
to
(
5
)
an
d
s
in
ce
f
o
r
,
w
e
n
o
w
r
e
wr
ite
th
e
d
y
n
a
m
ics o
f
a
g
en
t
as
Su
p
p
o
s
e
th
e
tar
g
et
o
b
j
e
ct
ac
ts
as
t
h
e
v
ir
tu
al
th
ag
e
n
t
s
,
th
e
n
w
e
h
a
v
e
w
it
h
.
I
n
ad
d
itio
n
,
th
e
m
a
s
s
o
f
th
e
v
ir
tu
a
l
ag
e
n
t
is
to
tak
e
th
e
a
v
er
ag
e
m
as
s
o
f
all
ag
en
t
s
g
i
v
e
n
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y
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i
s
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ca
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itte
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F
ig
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3
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t
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Ne
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ig
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re
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o
m
m
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ica
ti
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T
o
p
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l
o
g
y
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n
A
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ts
(No
.
6
is t
h
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V
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u
a
l
A
g
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t
Re
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ti
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Ob
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t
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y
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f
ag
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i
v
en
b
y
Evaluation Warning : The document was created with Spire.PDF for Python.
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d
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Me
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atr
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3
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2
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iv
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Dec
o
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po
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it
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[
7
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in
H
a
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lin
g
I
n
tr
o
d
u
ce
a
n
e
w
co
o
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d
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ate
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m
i
n
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t
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tr
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ed
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h
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s
u
b
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co
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d
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ate
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t
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m
'
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ate.
A
cc
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ep
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t
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S
h
ap
e
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m
's
co
o
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d
in
ate
[
7
]
.
Su
b
s
tit
u
ti
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g
(
17
)
in
to
(
14
)
,
w
e
o
b
tain
th
e
to
tal
d
y
n
a
m
ics i
n
th
e
n
e
w
co
o
r
d
in
ate
s
y
s
te
m
a
s
W
ith
th
i
s
tr
an
s
f
o
r
m
atio
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,
it i
s
o
b
s
er
v
ed
th
at
th
e
m
as
s
m
a
tr
ix
(
19
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is
b
lo
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-
d
iag
o
n
alize
d
s
u
c
h
th
at
w
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.
Si
m
i
lar
l
y
,
t
h
e
in
f
o
r
m
atio
n
g
r
ap
h
(
16
)
is
d
ec
o
m
p
o
s
e
d
to
attain
w
h
er
e
th
e
s
tr
u
ct
u
r
es
o
f
an
d
ar
e
id
en
tical
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th
e
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n
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d
e
f
in
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d
b
y
L
ee
&
Sp
o
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g
[
7
]
.
T
h
e
L
o
ck
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d
Sh
ap
e
s
y
s
te
m
s
o
f
th
e
to
tal
d
y
n
a
m
ic
s
(
14
)
as
ar
e
o
b
tain
ed
as
w
h
er
e
an
d
.
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tice
th
at
th
e
L
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ed
s
y
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te
m
(
2
2
)
is
co
u
p
le
d
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it
h
t
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e
Sh
ap
e
s
y
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m
(
2
3
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th
r
o
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g
h
.
I
n
o
n
e
ap
p
r
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ac
h
,
Nam
&
Na
m
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a
w
a
[
1
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]
in
tr
o
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u
ce
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p
lin
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ee
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[
7
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em
p
h
a
s
ized
th
at
Evaluation Warning : The document was created with Spire.PDF for Python.
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2
4
718
ca
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m
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ted
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llo
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7
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ck
ed
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m
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2
2
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s
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m
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a)
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b
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Fig
u
r
e
5
.
A
s
y
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p
to
tic
C
o
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v
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ce
o
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Ag
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T
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Fin
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ar
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Ob
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w
it
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(
a)
A
g
en
t’
s
T
r
a
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to
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,
(
b
)
Velo
city
an
d
P
o
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itio
n
o
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e
S
h
ap
e
S
y
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te
m
.
T
h
e
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m
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to
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at
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in
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l ta
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g
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e
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n
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l la
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u
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.
3
.
3
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T
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o
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i
m
e
T
h
e
esti
m
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o
f
is
cr
u
cial
s
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ce
it
is
co
n
s
id
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ed
as
th
e
w
a
it
in
g
time
b
y
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e
m
a
s
ter
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ip
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r
b
ef
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a
n
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b
eg
in
s
.
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h
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ar
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m
eter
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s
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-
u
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iq
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s
i
n
ce
it
d
ep
en
d
s
o
n
th
e
p
o
s
itio
n
s
a
n
d
v
elo
cities o
f
all
s
la
v
e
ag
e
n
t
s
at
.
T
heo
re
m
1
.
S
u
p
p
o
s
e
f
o
r
an
y
an
d
s
atis
f
y
in
g
L
e
m
.
1
,
w
i
th
a
n
y
ar
b
itra
r
y
i
n
itial
p
o
s
itio
n
s
an
d
v
elo
cities
o
f
t
h
e
a
g
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ts
,
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en
t
h
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ap
p
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x
i
m
a
te
“m
ax
i
m
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m
”
ti
m
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k
en
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to
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p
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n
m
e
n
t
s
u
ch
th
at
f
o
r
a
s
m
all
s
ca
lar
,
f
o
r
.
P
r
o
o
f
.
A
s
f
o
r
,
w
e
h
a
v
e
.
T
h
e
n
th
e
Sh
ap
e
s
y
s
te
m
(
2
3
)
ca
n
b
e
w
r
itte
n
i
n
th
e
f
o
r
m
o
f
au
to
n
o
m
o
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s
L
T
I
s
y
s
t
e
m
o
f
w
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e
,
an
d
is
a
s
ta
b
le
m
atr
i
x
.
Hen
ce
,
th
er
e
e
x
is
t
an
d
s
u
c
h
t
h
at
.
T
h
en
,
Hen
ce
,
w
h
e
n
,
.
T
h
er
ef
o
r
e,
.
■
4.
I
M
P
E
DANC
E
M
AT
CH
I
N
G
B
Y
F
RIT
C
o
n
s
id
er
th
e
ti
m
e
i
n
ter
v
al
,
an
d
b
ased
o
n
t
h
e
b
lo
ck
d
iag
r
a
m
i
n
Fi
g
u
r
e
1
,
th
e
f
o
llo
w
in
g
co
n
tr
o
l la
w
s
f
o
r
th
e
s
u
b
-
d
y
n
a
m
ics o
f
(
2
4
)
an
d
(
2
3
)
ar
e
u
s
ed
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Da
ta
-
Dri
ve
n
I
mp
ed
a
n
ce
Ma
tc
h
in
g
in
Mu
ltil
a
tera
l Tele
o
p
era
tio
n
S
ystems
(
Mo
h
d
S
ya
kiri
n
R
a
mli
)
719
R
e
w
r
iti
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g
t
h
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y
n
a
m
ics
o
f
t
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m
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s
ter
a
n
d
s
lav
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(
L
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c
k
ed
)
m
an
ip
u
lato
r
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i
n
ter
m
s
o
f
th
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ir
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m
p
ed
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n
ce
y
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s
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s
to
w
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d
,
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esp
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tiv
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y
.
An
eq
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alize
r
is
p
lace
d
in
th
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ee
d
b
ac
k
lo
o
p
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f
th
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m
as
ter
m
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ip
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lato
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.
B
y
o
p
ti
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all
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u
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g
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h
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u
alize
r
w
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l s
y
m
m
e
t
r
ize
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e
i
m
p
ed
an
ce
i
n
b
o
th
s
id
es o
f
te
leo
p
er
atio
n
.
C
o
n
tr
ar
y
to
T
s
u
j
i
et.
al.
[
1
5
]
,
w
e
co
n
s
id
er
a
s
p
ec
ial
s
tr
u
ct
u
r
e
o
f
an
d
th
e
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n
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n
g
p
r
o
ce
d
u
r
e
is
ca
r
r
ied
-
o
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t
u
s
i
n
g
t
h
e
-
d
i
m
e
n
s
io
n
al
s
p
ac
e
d
ata.
Fig
u
r
e
1
also
ill
u
s
tr
ate
s
t
h
e
p
lace
m
en
t
o
f
th
e
eq
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alize
r
in
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e
g
e
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er
al
s
tr
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ct
u
r
e
o
f
o
u
r
teleo
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atio
n
s
y
s
te
m
.
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h
e
co
n
tr
o
l
g
ai
n
s
a
n
d
ca
n
b
e
d
esi
g
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ed
ac
co
r
d
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g
l
y
to
f
o
r
m
eit
h
er
“
p
o
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itio
n
-
p
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s
it
io
n
”,
“
p
o
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itio
n
-
f
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ce
”
o
r
“
o
p
tim
ized
”
teleo
p
er
atio
n
ar
ch
i
tec
tu
r
es
[
1
6
]
.
T
o
av
o
id
ac
ce
ler
atio
n
m
ea
s
u
r
e
m
en
t,
ad
d
itio
n
al
co
n
tr
o
ller
s
an
d
(
lo
w
-
g
ain
P
D
C
o
n
tr
o
l)
ar
e
em
p
l
o
y
ed
as
th
e
in
ter
v
e
n
ie
n
t i
m
p
ed
an
ce
to
th
e
o
r
ig
in
al
s
y
s
te
m
s
[
1
6
]
.
Hen
ce
,
(
2
9
)
is
r
ew
r
itte
n
as
w
h
er
e
an
d
.
4
.
1
.
F
ict
it
i
o
us
Ref
er
ence
I
t
er
a
t
iv
e
T
un
ing
(
F
RIT
)
FR
I
T
is
a
s
i
m
p
le
y
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p
o
w
er
f
u
l
tu
n
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n
g
alg
o
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it
h
m
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s
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th
at
w
e
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ir
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o
p
ti
m
u
m
co
n
tr
o
ller
p
ar
a
m
eter
s
[
1
0
]
.
Fig
u
r
e
2
d
ep
icts
th
e
m
ai
n
co
n
ce
p
ts
o
f
i
m
p
ed
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ce
m
atc
h
i
n
g
u
s
in
g
F
R
I
T
in
T
s
u
j
i
et.
al.
[
1
5
]
.
A
s
il
lu
s
tr
ated
i
n
F
ig
u
r
e
3
(
a)
,
th
e
u
lti
m
a
te
ai
m
o
f
in
tr
o
d
u
cin
g
t
h
e
eq
u
alize
r
is
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h
iev
e
.
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w
e
v
er
,
b
ef
o
r
e
ca
n
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e
tu
n
ed
,
it
i
s
n
ec
es
s
ar
y
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m
a
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h
t
h
e
v
e
lo
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o
f
t
h
e
m
as
ter
an
d
t
h
e
L
o
ck
ed
s
y
s
te
m
t
h
r
o
u
g
h
as
d
ep
icted
i
n
Fig
u
r
e
3
(
b
)
.
Hen
ce
,
w
e
s
o
lv
e
t
h
e
o
p
ti
m
izatio
n
p
r
o
b
lem
:
w
h
er
e
f
o
r
th
e
r
ec
o
r
d
ed
in
itial
d
ata
,
B
ased
o
n
th
e
o
p
ti
m
al
,
w
e
s
o
l
v
e
th
e
s
ec
o
n
d
o
p
ti
m
izatio
n
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r
o
b
lem
:
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h
er
e
f
o
r
th
e
r
ec
o
r
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ed
in
itial
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ata
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d
w
h
e
n
t
h
e
in
i
tial e
q
u
alize
r
is
u
s
ed
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an
d
th
e
f
ictitio
u
s
r
ef
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n
ce
s
i
g
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al
is
T
heo
re
m
2
.
S
u
p
p
o
s
e
th
at
an
d
attain
an
d
r
esp
ec
tiv
el
y
.
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h
e
n
,
if
t
h
e
s
i
g
n
al
is
r
ich
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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n
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o
m
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.
2
,
Ma
y
2
0
1
8
:
7
1
3
–
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2
4
720
4
.
2
.
L
a
g
uerr
e
net
w
o
rk
W
e
ca
n
ap
p
r
o
x
im
a
te
a
d
is
cr
ete
ti
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e
SISO
s
y
s
te
m
to
u
s
e
a
L
ag
u
er
r
e
f
u
n
ctio
n
as
(
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u
r
e
3
).
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e
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d
.
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h
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p
ar
a
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eter
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d
eter
m
i
n
ed
b
y
t
h
e
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y
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te
m
's
d
esig
n
er
an
d
is
t
h
e
s
a
m
p
le
t
i
m
e.
Me
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n
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h
ile
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e
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icie
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t
s
th
a
t
f
o
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m
th
e
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asi
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h
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L
a
g
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er
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n
et
w
o
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k
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e
t
r
ep
r
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ts
t
h
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u
tp
u
t
o
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e
th
-
o
r
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er
f
ilter
i
n
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e
L
a
g
u
er
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e
n
et
w
o
r
k
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h
en
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e
SISO
s
tate
-
s
p
ac
e
m
o
d
el
is
g
iv
e
n
b
y
w
h
er
e
,
,
,
,
T
h
e
MI
MO
tr
an
s
f
er
m
atr
ix
h
a
s
a
s
tate
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s
p
ac
e
r
ep
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tatio
n
g
iv
e
n
as
w
h
er
e
,
.
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h
e
ap
p
r
o
p
r
iate
d
esig
n
o
f
t
h
e
eq
u
alize
r
ca
n
b
e
o
b
tain
ed
b
y
a
s
s
i
g
n
i
n
g
(
44
)
in
to
.
T
o
en
s
u
r
e
f
as
ter
r
ate
co
n
v
er
g
e
n
ce
o
f
th
e
L
ag
u
er
r
e
n
et
w
o
r
k
,
W
a
h
lb
er
g
[
1
7
]
s
u
g
g
e
s
ted
t
h
at
t
h
e
v
al
u
e
o
f
in
(
4
3
)
s
h
o
u
ld
b
e
c
h
o
s
en
clo
s
e
to
th
e
i
n
v
er
s
e
o
f
th
e
s
y
s
te
m
d
o
m
i
n
a
n
t
ti
m
e
co
n
s
ta
n
t.
Ho
w
e
v
er
in
o
u
r
ca
s
e,
t
h
e
p
ar
a
m
eter
o
f
m
u
s
t
b
e
ch
o
s
en
s
o
t
h
at
t
h
e
d
es
ig
n
ed
e
q
u
alize
r
w
ill
b
e
in
-
s
y
n
c
w
i
th
t
h
e
S
h
ap
e
s
y
s
te
m
(
2
3
)
.
Hen
ce
,
th
e
p
ar
a
m
eter
is
to
u
s
e
t
h
e
p
ar
a
m
eter
’
s
v
al
u
e
o
f
in
(
2
6
)
s
u
c
h
th
at
.
T
h
er
ef
o
r
e,
w
e
ar
e
lef
t
w
i
th
t
h
e
t
u
n
ab
l
e
p
ar
am
eter
s
o
f
w
h
er
e
th
e
o
p
ti
m
u
m
eq
u
al
iz
er
ca
n
b
e
o
b
tain
ed
b
y
s
i
m
p
l
y
tu
n
in
g
t
h
e
b
asis
(
4
2
)
.
T
h
e
s
elec
tio
n
o
f
t
h
e
eq
u
alize
r
to
s
o
lv
e
th
e
o
p
ti
m
izatio
n
p
r
o
b
le
m
o
f
(
3
1
)
,
r
eq
u
ir
es
to
b
e
in
v
er
s
e
-
ab
le
a
n
d
is
s
tab
le.
T
h
er
ef
o
r
e,
w
e
s
elec
t a
b
ip
r
o
p
er
tr
an
s
f
er
f
u
n
ctio
n
i
n
th
e
f
o
r
m
o
f
to
y
ield
u
s
a
MI
MO
tr
an
s
f
er
m
atr
i
x
o
f
T
h
e
esti
m
atio
n
o
f
th
e
co
ef
f
icie
n
ts
in
(
4
5
)
ca
n
b
e
o
b
tain
ed
b
y
m
i
n
i
m
izi
n
g
(
32
)
th
r
o
u
g
h
lea
s
t
-
s
q
u
ar
e
m
e
th
o
d
(
L
SM)
.
Re
-
ar
r
an
g
i
n
g
d
at
a
s
u
c
h
th
at
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Da
ta
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Dri
ve
n
I
mp
ed
a
n
ce
Ma
tc
h
in
g
in
Mu
ltil
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o
p
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tio
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ystems
(
Mo
h
d
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ya
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a
mli
)
721
an
d
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to
g
iv
e
u
s
a
lin
ea
r
r
ela
tio
n
o
f
.
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h
en
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th
e
o
p
ti
m
al
co
e
f
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ien
t
s
ar
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tain
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b
y
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t
h
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en
r
o
s
e
p
s
eu
d
o
in
v
er
s
e
o
f
.
Nex
t,
w
e
illu
s
tr
ate
t
h
e
t
u
n
in
g
p
r
o
ce
d
u
r
e
to
o
b
tain
th
e
o
p
ti
m
u
m
eq
u
alize
r
.
T
h
e
co
s
t
f
u
n
cti
o
n
(
34
)
is
s
i
m
p
lif
ied
to
w
h
er
e
is
w
it
h
th
e
o
p
ti
m
ized
p
ar
am
eter
s
o
b
tain
ed
b
y
(
46
).
T
h
e
o
v
er
all
al
g
o
r
ith
m
to
o
b
tain
o
p
ti
m
u
m
is
s
u
m
m
ar
ized
as
f
o
llo
w
in
g
:
Step
1
:
Set a
L
a
g
u
er
r
e
n
e
t
w
o
r
k
u
s
in
g
(
6
3
)
an
d
w
it
h
an
ap
p
r
o
p
r
iate
in
itial
as
Step
2
:
P
er
f
o
r
m
a
n
ex
p
er
i
m
e
n
t to
g
e
n
er
ate
th
e
in
it
ial
d
ata
,
,
an
d
.
Step
3
:
C
h
o
o
s
e
a
b
i
-
p
r
o
p
er
tr
an
s
f
er
f
u
n
ctio
n
,
an
d
m
i
n
i
m
ize
(
3
2
)
b
y
(
4
6
)
u
s
in
g
d
ata
o
b
tain
ed
in
Ste
p
2.
Step
4
:
Usi
n
g
t
h
e
o
p
ti
m
all
y
t
u
n
ed
,
f
in
d
th
e
m
i
n
i
m
izer
to
m
i
n
i
m
ize
t
h
e
co
s
t f
u
n
ctio
n
(
4
7
)
.
T
h
e
s
u
b
-
al
g
o
r
ith
m
i
n
Step
4
to
tu
n
e
is
as f
o
llo
w
s
:
Step
1
:
Gen
er
ate
th
e
n
e
w
d
ata
.
Step
2
:
Usi
n
g
in
Step
2
,
g
en
er
ate
t
h
e
s
tate
d
ata
.
Step
3
:
Fin
d
t
h
e
m
i
n
i
m
izer
o
f
th
e
co
n
s
tr
ain
t
m
i
n
i
m
izatio
n
T
h
is
is
eq
u
i
v
alen
t to
T
h
en
,
th
e
m
in
i
m
izer
is
o
b
tai
n
e
d
b
y
w
h
er
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
10
,
No
.
2
,
Ma
y
2
0
1
8
:
7
1
3
–
7
2
4
722
5.
NUM
E
RICAL
E
XAM
P
L
E
A
n
u
m
er
ical
e
x
a
m
p
le
to
ill
u
s
t
r
ate
th
e
e
f
f
ec
ti
v
en
e
s
s
o
f
o
u
r
a
p
p
r
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ac
h
is
p
r
esen
ted
i
n
t
h
i
s
s
ec
tio
n
.
L
et
th
e
s
la
v
e
m
a
n
ip
u
la
to
r
s
co
m
p
r
i
s
ed
o
f
ag
en
ts
w
it
h
th
e
ir
co
m
m
u
n
icat
io
n
to
p
o
lo
g
y
as
s
h
o
w
n
in
Fi
g
u
r
e
4
.
T
h
e
d
ash
ed
-
ar
r
o
w
i
n
d
icate
s
t
h
at
o
n
l
y
a
g
en
t
ca
n
m
ea
s
u
r
e
th
e
p
o
s
itio
n
an
d
v
elo
cit
y
o
f
th
e
tar
g
et
o
b
j
ec
t
(
in
d
icate
d
b
y
v
ir
tu
al
ag
e
n
t
).
T
h
e
m
as
s
o
f
th
e
m
a
s
ter
,
s
la
v
e
a
g
en
t
s
a
n
d
th
e
e
n
v
ir
o
n
m
e
n
t
w
er
e
c
h
o
s
e
n
as
.
Me
an
w
h
i
le,
th
e
r
ad
iu
s
o
f
th
e
tar
g
et
o
b
j
ec
t/en
v
ir
o
n
m
en
t
w
as
ch
o
s
en
a
s
Fig
u
r
e
6
Velo
cit
y
Ma
tc
h
in
g
T
h
r
o
u
g
h
Gai
n
Fig
u
r
e
7
C
o
m
p
ar
is
o
n
o
f
Op
ti
m
ized
Fictit
io
u
s
Sig
n
al
(
35
)
w
it
h
t
h
e
I
n
itial
.
T
o
s
atis
f
y
L
e
m
m
a
1
,
th
e
s
p
r
i
n
g
an
d
d
a
m
p
i
n
g
c
o
n
s
ta
n
ts
in
(
1
2
)
w
er
e
s
el
ec
ted
as
.
W
ith
th
i
s
s
elec
tio
n
,
t
h
e
d
o
m
i
n
an
t
e
ig
e
n
v
alu
e
o
f
t
h
e
S
h
ap
e
s
y
s
te
m
(
2
3
)
h
a
s
b
ee
n
o
b
tain
ed
as
.
Fo
r
ea
s
e
o
f
an
al
y
s
is
,
w
e
a
s
s
u
m
e
th
at
t
h
e
f
r
ictio
n
f
o
r
ce
,
.
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h
e
in
itial
p
o
s
itio
n
s
o
f
t
h
e
m
a
s
ter
m
a
n
ip
u
lato
r
an
d
t
h
e
C
.
O.
M
o
f
t
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tar
g
et(
en
v
ir
o
n
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e
n
t)
w
er
e
s
et
at
an
d
b
ein
g
s
tatio
n
ar
y
a
t
.
Me
an
w
h
ile,
th
e
s
lav
e
a
g
e
n
ts
'
p
o
s
itio
n
s
w
er
e
in
itial
ized
ar
o
u
n
d
t
h
e
tar
g
e
t
in
t
h
e
r
eg
io
n
,
w
it
h
ze
r
o
v
elo
cit
y
at
i.e
.
,
.
I
n
Fi
g
u
r
e
5
(
a)
,
th
e
ag
e
n
ts
'
in
itia
l
p
o
s
itio
n
s
a
n
d
tr
aj
ec
to
r
ies
to
w
ar
d
s
t
h
eir
i
n
te
n
d
ed
f
i
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p
o
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itio
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th
e
o
b
j
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t
f
o
r
a
r
e
illu
s
tr
ated
.
Su
b
s
eq
u
e
n
tl
y
,
Fig
u
r
e
5
(
b
)
d
ep
icts
th
e
tr
a
j
ec
to
r
y
o
f
Sh
ap
e
s
y
s
te
m
's
v
elo
cit
y
a
n
d
p
o
s
itio
n
.
I
t
is
clea
r
ly
o
b
s
er
v
e
d
th
at
th
e
tr
aj
ec
to
r
ies
o
f
th
e
Sh
ap
e
s
y
s
te
m
w
er
e
as
y
m
p
to
ticall
y
co
n
v
er
g
i
n
g
s
u
ch
t
h
at
.
T
h
e
esti
m
ated
te
le
o
p
er
atio
n
ti
m
e
b
ased
o
n
th
e
g
i
v
e
n
i
n
itial
p
o
s
itio
n
s
w
er
e
o
b
tain
ed
as
s
.
I
n
th
i
s
ex
a
m
p
le,
w
e
u
s
ed
th
e
in
ter
v
e
n
ie
n
t
i
m
p
ed
an
ce
s
,
,
th
e
co
n
tr
o
ller
,
w
it
h
h
u
m
a
n
i
m
p
ed
a
n
ce
o
f
,
,
an
d
,
r
esp
ec
tiv
el
y
.
T
h
e
v
elo
cit
y
m
atc
h
i
n
g
p
er
f
o
r
m
an
ce
b
et
w
ee
n
an
d
as
p
r
e
s
en
ted
in
Fi
g
u
r
e
6
v
er
if
ies
th
at
t
h
er
e
e
x
is
ts
s
u
ch
th
a
t
t
h
e
co
s
t
f
u
n
ctio
n
(
3
2
)
is
m
i
n
i
m
ized
.
I
n
Fi
g
u
r
e
7
,
w
e
e
x
h
ib
it
th
e
co
m
p
ar
is
o
n
b
et
w
ee
n
an
d
th
e
r
e
s
p
o
n
s
e
o
f
f
ic
titi
o
u
s
s
ig
n
al
(
3
5
)
w
h
e
n
t
h
e
eq
u
alize
r
w
it
h
o
p
ti
m
all
y
t
u
n
ed
p
ar
am
eter
s
w
a
s
ap
p
lied
.
I
t
c
an
b
e
s
h
o
w
n
t
h
at
t
h
ese
t
w
o
s
ig
n
al
s
w
er
e
al
m
o
s
t
id
en
t
ical
in
b
o
th
an
d
d
ir
ec
tio
n
s
in
t
h
e
s
e
n
s
e
t
h
at
is
m
i
n
i
m
ized
.
6.
CO
NCLU
SI
O
N
I
n
th
i
s
p
ap
er
,
w
e
h
av
e
p
r
o
p
o
s
ed
tu
n
i
n
g
al
g
o
r
ith
m
to
i
m
p
r
o
v
e
tr
an
s
p
ar
en
c
y
th
r
o
u
g
h
i
m
p
ed
a
n
ce
m
atc
h
in
g
b
et
w
ee
n
m
as
ter
an
d
s
lav
e
m
a
n
ip
u
la
to
r
s
in
th
e
m
u
lt
ilater
al
teleo
p
er
atio
n
s
y
s
te
m
.
T
h
e
p
ass
i
v
e
d
ec
o
m
p
o
s
itio
n
tech
n
iq
u
e
h
as
p
r
o
v
id
ed
s
u
b
s
tan
tial
ap
p
r
o
ac
h
to
co
n
v
er
t
th
e
to
tal
d
y
n
a
m
ic
s
o
f
a
m
u
lti
-
s
la
v
e
s
y
s
te
m
in
to
th
e
b
ilater
al
teleo
p
er
atio
n
ar
ch
itect
u
r
e
s
o
t
h
at
t
h
e
ex
is
tin
g
b
ilater
al
co
n
tr
o
l
tec
h
n
iq
u
e
ca
n
b
e
u
s
ed
.
Su
b
s
eq
u
e
n
tl
y
,
f
r
o
m
t
h
e
r
es
u
lt
o
f
d
ec
o
m
p
o
s
i
tio
n
a
n
d
t
h
e
in
itial
s
tates
o
f
all
s
la
v
e
a
g
en
t
s
,
th
e
teleo
p
er
atio
n
ti
m
e,
th
at
s
ep
ar
ated
th
e
t
w
o
o
p
er
atio
n
s
(
g
r
asp
in
g
a
n
d
teleo
p
er
atio
n
)
h
as
b
ee
n
esti
m
at
ed
.
I
n
ter
m
s
o
f
o
b
tain
in
i
n
g
t
h
e
o
p
ti
m
al
eq
u
a
li
ze
r
,
w
e
co
n
cl
u
d
e
th
a
t
F
R
I
T
p
r
o
v
id
es
p
o
w
er
f
u
l
al
g
o
r
ith
m
s
s
in
ce
o
n
l
y
a
s
in
g
le
-
s
h
o
t
o
f
m
ea
s
u
r
e
m
e
n
t
d
ata
was
r
eq
u
ir
ed
f
o
r
tu
n
i
n
g
.
T
h
e
o
v
er
all
p
er
f
o
r
m
a
n
ce
an
d
co
m
p
ar
i
s
o
n
p
r
ese
n
ted
th
r
o
u
g
h
n
u
m
e
r
ical
e
x
a
m
p
le
h
a
s
illu
s
tr
ated
th
e
ap
p
licab
ilit
y
o
f
th
e
p
r
o
p
o
s
ed
tu
n
i
n
g
m
et
h
o
d
.
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