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Feb
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I
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52
In
d
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J
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&
C
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m
p
Sci
,
Vo
l.
3
7
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No
.
2
,
Feb
r
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a
r
y
20
2
5
:
77
1
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7
8
0
772
th
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Fo
r
in
s
tan
ce
,
s
tu
d
ies
s
u
ch
as
[
3
]
em
p
h
asize
th
e
s
ig
n
if
ican
t
in
f
lu
en
ce
o
f
c
o
n
tr
o
l
v
alv
e
an
d
p
is
to
n
ar
ea
s
o
n
o
u
tlet
p
r
ess
u
r
e
r
eg
u
latio
n
,
p
ar
ticu
lar
ly
u
n
d
e
r
v
ar
y
in
g
o
p
er
atin
g
co
n
d
itio
n
s
.
Mo
r
eo
v
er
,
wo
r
k
s
lik
e
[
4
]
p
r
o
v
id
e
in
s
ig
h
ts
in
to
th
e
im
p
o
r
tan
ce
o
f
s
tatic
an
d
d
y
n
a
m
ic
ch
ar
ac
ter
is
tics
m
o
d
elin
g
,
h
ig
h
lig
h
tin
g
th
e
cr
itical
r
o
le
o
f
p
u
m
p
p
r
o
p
er
ties
in
p
r
ess
u
r
e
co
n
tr
o
l.
As
ex
p
lo
r
ed
in
[
5
]
,
clo
s
ed
-
f
o
r
m
d
esig
n
e
q
u
atio
n
s
o
f
f
er
a
s
tr
u
ctu
r
ed
a
p
p
r
o
ac
h
to
ad
d
r
ess
p
ar
am
eter
v
ar
iatio
n
s
,
wh
ile
in
v
esti
g
atio
n
s
in
to
co
n
tr
o
l
s
tr
a
teg
ies,
in
clu
d
in
g
f
u
zz
y
lo
g
ic
an
d
n
o
n
lin
ea
r
g
ain
ad
ap
tatio
n
[
6
]
,
u
n
d
er
s
co
r
e
th
e
p
o
ten
tial
f
o
r
en
h
a
n
ce
d
p
r
ess
u
r
e
co
n
tr
o
l.
Fu
r
th
e
r
m
o
r
e
,
r
e
s
ea
r
ch
s
u
ch
as
[
7
]
em
p
h
asizes
th
e
im
p
o
r
tan
ce
o
f
o
p
tim
izin
g
p
u
m
p
-
a
n
d
-
v
alv
e
co
n
f
ig
u
r
atio
n
s
to
im
p
r
o
v
e
b
a
n
d
wid
th
f
r
eq
u
en
cy
.
E
x
p
an
d
i
n
g
o
n
th
ese
f
in
d
in
g
s
,
s
tu
d
ies
lik
e
[
8
]
in
t
r
o
d
u
ce
in
n
o
v
ativ
e
co
n
tr
o
l
s
tr
ateg
ies
tailo
r
ed
to
s
p
ec
if
ic
p
u
m
p
ap
p
licatio
n
s
,
s
h
o
wca
s
in
g
r
o
b
u
s
t
p
er
f
o
r
m
an
ce
th
r
o
u
g
h
ex
p
er
im
en
tal
v
alid
atio
n
.
Ad
d
itio
n
ally
,
in
v
esti
g
atio
n
s
in
to
ae
r
o
n
au
tical
ax
ial
p
is
to
n
p
u
m
p
s
[
9
]
an
d
v
a
r
iab
le
d
is
p
la
ce
m
en
t
r
ad
ial
p
is
to
n
p
u
m
p
s
[
1
0
]
s
h
ed
lig
h
t
o
n
k
ey
p
ar
am
eter
s
in
f
lu
en
ci
n
g
p
u
m
p
p
er
f
o
r
m
an
ce
an
d
co
n
tr
o
l
m
ec
h
an
is
m
s
.
Fu
r
th
er
m
o
r
e
,
n
o
v
el
co
n
f
ig
u
r
atio
n
s
s
u
ch
as
th
e
s
in
g
le
-
ac
tu
ato
r
s
etu
p
p
r
o
p
o
s
ed
in
[
1
1
]
ad
d
r
ess
co
n
v
en
tio
n
al
lim
itatio
n
s
,
wh
ile
r
esear
ch
o
n
r
o
b
u
s
t
co
n
tr
o
l
m
eth
o
d
s
[
1
2
]
an
d
p
o
wer
co
n
tr
o
l
s
y
s
tem
s
[
1
3
]
o
f
f
er
av
en
u
es
f
o
r
im
p
r
o
v
ed
s
tab
ilit
y
an
d
ef
f
icien
cy
.
Mo
r
eo
v
er
,
ad
v
a
n
ce
m
en
ts
in
e
lectr
o
-
h
y
d
r
au
lic
s
y
s
tem
s
[
1
4
]
,
[
1
5
]
an
d
m
ec
h
a
n
ical
co
m
p
o
n
en
t
o
p
tim
izatio
n
s
[
1
6
]
,
[
1
7
]
f
u
r
th
e
r
co
n
tr
i
b
u
te
to
th
e
ev
o
lv
in
g
la
n
d
s
ca
p
e
o
f
p
u
m
p
co
n
tr
o
l.
No
tab
ly
,
ef
f
o
r
ts
f
o
cu
s
ed
o
n
v
i
b
r
atio
n
co
n
tr
o
l
[
1
8
]
,
[
1
9
]
an
d
v
al
v
e
d
esig
n
en
h
an
ce
m
en
ts
[
2
0
]
u
n
d
er
s
co
r
e
th
e
in
ter
d
is
cip
lin
ar
y
n
atu
r
e
o
f
p
u
m
p
s
y
s
tem
o
p
tim
izatio
n
.
Ad
d
iti
o
n
ally
,
r
esear
ch
o
n
elec
tr
o
-
pn
eu
m
atic
p
r
o
p
o
r
tio
n
al
s
y
s
tem
s
[
2
1
]
h
i
g
h
lig
h
ts
r
eliab
le
co
n
s
tan
t
p
r
ess
u
r
e
co
n
t
r
o
l
d
esp
ite
in
h
er
en
t d
elay
s
in
v
alv
e
m
ec
h
an
is
m
s
.
Fin
ally
,
s
tu
d
ies
lik
e
[
2
2
]
,
[
2
3
]
ad
v
o
ca
te
f
o
r
r
o
b
u
s
t
co
n
tr
o
l
m
eth
o
d
o
l
o
g
ies,
em
p
h
asizin
g
th
eir
s
u
p
er
io
r
ity
in
r
esil
ien
ce
an
d
p
r
ec
is
i
o
n
o
v
e
r
tr
ad
itio
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al
p
r
o
p
o
r
tio
n
al
-
in
teg
r
al
-
d
er
iv
ativ
e
(
PID
)
co
n
tr
o
ller
s
[
2
4
]
,
[
2
5
]
.
T
h
e
T
-
SP
I
D
c
o
n
tr
o
ller
im
p
r
o
v
es
s
tab
ilit
y
an
d
r
esp
o
n
s
iv
en
ess
,
cu
ttin
g
ad
ju
s
tm
en
t
tim
e
b
y
5
0
%
[
2
6
]
.
MA
T
L
AB
/Si
m
u
lin
k
s
im
u
latio
n
s
id
en
tify
k
ey
p
ar
a
m
eter
s
f
o
r
e
n
h
an
ci
n
g
ac
cu
r
ac
y
an
d
p
e
r
f
o
r
m
an
ce
[
2
7
]
,
[
2
8
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
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N:
2
5
0
2
-
4
7
52
Op
timiz
in
g
d
yn
a
mic
r
esp
o
n
s
e
a
n
d
s
ta
b
ilit
y
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f
p
r
ess
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r
e
-
co
n
tr
o
lled
…
(
V
ivek
V
erma
)
773
T
h
r
o
u
g
h
o
n
g
o
in
g
r
esear
ch
a
n
d
d
e
v
elo
p
m
e
n
t,
th
e
f
ield
h
as
m
ad
e
s
ig
n
if
ican
t
s
tr
id
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p
r
o
v
id
i
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g
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etailed
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s
ig
h
ts
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d
p
r
ac
tic
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s
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lu
tio
n
s
f
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r
im
p
r
o
v
in
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p
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m
p
p
e
r
f
o
r
m
an
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an
d
co
n
t
r
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l
ac
r
o
s
s
v
ar
io
u
s
ap
p
licatio
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s
.
Ho
wev
e
r
,
t
h
e
co
n
tr
o
ller
s
d
esig
n
e
d
in
e
ar
lier
s
tu
d
ies
h
a
v
e
g
e
n
er
all
y
n
o
t
in
c
o
r
p
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r
ated
co
m
p
en
s
ato
r
s
to
e
n
h
an
ce
th
e
p
er
f
o
r
m
an
ce
o
f
v
a
r
iab
le
ax
ial
p
is
to
n
p
u
m
p
s
(
VAPP).
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s
t
o
f
th
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s
tu
d
ies
h
av
e
f
o
cu
s
ed
o
n
o
p
tim
izin
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a
s
p
e
cif
ic
asp
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t
s
u
ch
as
r
ed
u
cin
g
p
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r
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f
lu
ctu
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s
o
r
m
ax
im
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f
icien
cy
.
T
h
er
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is
a
clea
r
g
ap
in
th
e
d
ev
elo
p
m
e
n
t
o
f
co
m
p
en
s
ato
r
d
esig
n
s
th
at
ca
n
o
p
tim
ize
p
u
m
p
p
er
f
o
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m
a
n
ce
,
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clu
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m
in
im
izin
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en
er
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y
co
n
s
u
m
p
tio
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r
ed
u
cin
g
wea
r
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d
tea
r
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an
d
m
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ta
in
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tem
r
esp
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T
h
u
s
,
th
e
cu
r
r
en
t
s
tu
d
y
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ets
its
o
b
jectiv
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s
b
ased
o
n
a
th
o
r
o
u
g
h
r
ev
ie
w
o
f
th
e
e
x
is
tin
g
liter
atu
r
e,
with
r
ec
en
t w
o
r
k
s
u
m
m
ar
ized
in
T
a
b
le
1
as f
o
llo
ws:
−
T
o
d
ev
elo
p
d
y
n
am
ic
p
u
m
p
m
o
d
el.
−
T
o
d
ev
elo
p
an
al
g
o
r
ith
m
f
o
r
im
p
lem
en
tin
g
lea
d
-
lag
c
o
m
p
en
s
ato
r
f
o
r
im
p
r
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v
e
d
VAPP p
er
f
o
r
m
an
ce
.
−
T
o
d
esig
n
a
co
n
tr
o
ller
f
o
r
th
e
o
p
tim
u
m
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r
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n
s
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f
a
p
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co
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tr
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lled
s
wash
p
late
-
ty
p
e
ax
ial
p
is
to
n
p
u
m
p
.
T
ab
le
1
.
Su
m
m
a
r
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r
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e
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ch
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k
A
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Y
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R
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d
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F
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l
.
2
0
2
3
[
2
2
]
Th
e
st
u
d
y
mo
d
e
l
l
e
d
t
h
e
V
A
P
P
a
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p
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∞
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∞
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me
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me.
G
h
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a
l
.
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2
3
[
2
0
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Th
e
st
u
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p
t
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d
a
s
p
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v
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V
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f
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.
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l
.
2
0
2
3
[
2
7
]
To
d
e
v
e
l
o
p
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m
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t
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mat
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a
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mo
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a
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l
.
2
0
2
2
[
2
8
]
Th
e
st
u
d
y
a
n
a
l
y
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e
s
t
h
e
c
o
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p
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v
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M
A
TLA
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/
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ma
n
c
e
.
Q
i
a
n
et
a
l
.
2
0
2
1
[
2
6
]
I
n
v
e
st
i
g
a
t
e
d
a
n
e
l
e
c
t
r
o
-
h
y
d
r
a
u
l
i
c
ser
v
o
sy
st
e
m f
o
r
c
o
n
t
r
o
l
l
i
n
g
a
h
y
d
r
a
u
l
i
c
mo
t
o
r
.
S
i
mu
l
a
t
i
o
n
s
c
o
n
f
i
r
me
d
P
I
D
c
o
n
t
r
o
l
l
e
r
'
s
e
f
f
e
c
t
i
v
e
s
p
e
e
d
c
o
n
t
r
o
l
,
a
t
6
0
–
70
°
C
,
w
i
t
h
st
a
b
l
e
p
e
r
f
o
r
ma
n
c
e
u
n
d
e
r
d
i
s
t
u
r
b
a
n
c
e
s.
K
u
mar
a
n
d
M
a
n
d
a
l
2
0
2
1
[
1
0
]
P
r
e
ssu
r
e
c
o
n
t
r
o
l
i
n
a
v
a
r
i
a
b
l
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d
i
s
p
l
a
c
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me
n
t
r
a
d
i
a
l
p
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p
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m
p
(V
D
R
P
P
)
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si
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g
a
P
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D
c
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t
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l
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d
v
a
l
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p
l
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t
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d
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si
g
n
o
p
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z
a
t
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n
.
A
n
o
p
t
i
m
i
z
e
d
v
a
l
v
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p
l
a
t
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d
u
c
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s l
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a
k
a
g
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a
n
d
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n
h
a
n
c
e
s e
f
f
i
c
i
e
n
c
y
.
S
i
mu
l
i
n
k
a
n
a
l
y
si
s
c
o
n
f
i
r
ms
e
f
f
e
c
t
i
v
e
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
a
n
d
d
e
t
a
i
l
e
d
f
l
o
w
b
e
h
a
v
i
o
r
i
n
t
h
e
V
D
R
P
P
.
Zh
a
o
a
n
d
H
u
a
n
g
2
0
2
0
[
2
1
]
D
e
v
e
l
o
p
a
c
o
n
st
a
n
t
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
met
h
o
d
u
s
i
n
g
p
r
o
p
o
r
t
i
o
n
a
l
a
n
d
o
p
e
n
-
l
o
o
p
t
e
c
h
n
o
l
o
g
y
.
Ex
p
e
r
i
m
e
n
t
s
d
e
mo
n
st
r
a
t
e
t
h
e
f
e
a
s
i
b
i
l
i
t
y
o
f
t
h
i
s a
p
p
r
o
a
c
h
,
h
i
g
h
l
i
g
h
t
i
n
g
i
t
s
h
i
g
h
p
r
e
c
i
si
o
n
a
n
d
c
o
s
t
-
e
f
f
e
c
t
i
v
e
n
e
ss
.
C
h
e
n
et
a
l
.
2
0
1
6
[
9
]
D
e
v
e
l
o
p
e
d
a
m
o
d
e
l
t
o
s
t
u
d
y
p
r
e
ss
u
r
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d
r
o
p
s
i
n
a
n
a
i
r
c
r
a
f
t
h
y
d
r
a
u
l
i
c
a
x
i
a
l
p
i
s
t
o
n
p
u
mp
a
t
v
a
r
y
i
n
g
sp
e
e
d
s.
Th
e
y
i
d
e
n
t
i
f
i
e
d
p
r
e
ss
u
r
e
d
r
o
p
c
a
u
ses
a
n
d
e
f
f
e
c
t
s
o
f
sp
o
o
l
-
mass
,
s
p
r
i
n
g
st
i
f
f
n
e
s
s,
a
n
d
p
i
s
t
o
n
c
o
u
n
t
,
f
o
r
i
m
p
r
o
v
e
d
p
u
mp
p
e
r
f
o
r
m
a
n
c
e
.
2.
M
AT
H
E
M
AT
I
CA
L
M
O
D
E
L
L
I
NG
A
ND
ANA
L
Y
SI
S
O
F
P
R
E
SS
URE
-
CO
NT
RO
L
L
E
D
VARIA
B
L
E
D
E
L
I
VE
RY
A
XIAL
P
I
S
T
O
N
P
UM
P
T
h
e
m
ath
em
atica
l
m
o
d
elin
g
o
f
t
h
e
p
r
ess
u
r
e
-
co
n
tr
o
lled
v
ar
iab
le
d
eliv
e
r
y
a
x
ial
p
is
to
n
p
u
m
p
is
d
ev
elo
p
e
d
in
th
is
s
ec
tio
n
.
T
o
ac
co
m
p
lis
h
th
e
r
esear
ch
o
b
jectiv
e,
th
e
tr
an
s
f
er
f
u
n
ctio
n
f
o
r
th
e
eq
u
iv
alen
t
h
y
d
r
o
m
ec
h
an
ical
s
y
s
tem
o
f
a
v
ar
iab
le
d
eliv
er
y
ax
ial
p
is
to
n
p
u
m
p
was
f
o
r
m
u
lated
.
T
h
e
g
o
v
er
n
in
g
eq
u
ati
o
n
s
f
o
r
th
e
d
y
n
am
ic
s
y
s
tem
wer
e
d
er
iv
ed
b
y
co
n
s
id
er
in
g
th
e
d
y
n
am
ics
o
f
th
e
b
ar
r
el,
wh
ic
h
in
f
lu
en
ce
s
d
eliv
er
y
p
r
ess
u
r
e,
th
e
s
wash
p
late,
wh
i
ch
ac
ts
as
a
m
ec
h
a
n
is
m
to
co
n
v
er
t
r
o
tatio
n
al
m
o
tio
n
in
t
o
r
e
cip
r
o
ca
tin
g
m
o
tio
n
f
o
r
v
a
r
iab
le
d
is
ch
ar
g
e
,
an
d
th
e
3
-
way
s
p
o
o
l v
alv
e.
2
.
1
.
Dy
na
m
ics o
f
deliv
er
y
press
ure
C
o
n
s
id
er
in
g
th
e
f
u
n
d
am
en
tal
p
r
ess
u
r
e
-
r
is
e
-
r
ate
e
q
u
atio
n
,
f
ac
to
r
in
g
in
f
l
u
id
co
m
p
r
ess
ib
ilit
y
an
d
i
n
s
t
a
n
ta
n
e
o
u
s
d
is
c
h
a
r
g
e
f
l
o
w
v
a
r
i
a
t
i
o
n
s
,
w
e
d
e
r
i
v
e
t
h
e
g
o
v
e
r
n
i
n
g
e
q
u
a
t
i
o
n
f
o
r
d
i
s
c
h
a
r
g
e
p
r
e
s
s
u
r
e
(
P
d
)
[
1
4
]
,
[
2
5
]
.
̇
+
=
−
(
1
)
T
h
e
m
o
d
el
in
cl
u
d
es
V
(
f
lu
id
v
o
lu
m
e
in
d
is
ch
ar
g
e
lin
e)
,
(
b
u
lk
m
o
d
u
l
u
s
)
,
K
(
p
u
m
p
le
ak
ag
e
co
ef
f
icien
t)
,
Q
(
f
lo
w
r
ate
f
r
o
m
p
u
m
p
)
,
an
d
Q
sys
(
f
lo
w
r
ate
d
r
awn
b
y
t
h
e
d
o
wn
s
tr
ea
m
s
y
s
tem
)
.
Fo
r
s
tead
y
-
s
tate
o
p
er
atin
g
co
n
d
itio
n
s
,
=
0
−
0
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
7
,
No
.
2
,
Feb
r
u
a
r
y
20
2
5
:
77
1
-
7
8
0
774
wh
er
e
Q
o
is
a
v
er
ag
e
p
u
m
p
d
i
s
ch
ar
g
e
an
d
0
is
av
e
r
ag
e
d
eliv
er
y
p
r
ess
u
r
e.
R
ep
lacin
g
th
is
o
u
tco
m
e
in
(
1
)
y
ield
s
th
e
g
o
v
e
r
n
in
g
eq
u
atio
n
f
o
r
th
e
p
u
m
p
'
s
d
eliv
er
y
p
r
ess
u
r
e
:
̇
+
(
−
0
)
=
−
0
(
3
)
a
s
th
ese
p
u
m
p
s
m
ain
tain
a
c
o
n
s
tan
t a
n
g
u
lar
v
el
o
city
o
f
t
h
e
s
h
af
t,
h
en
ce
:
−
0
=
(
−
0
)
(
4
)
wh
er
e
is
p
itch
p
late
an
g
le,
is
p
u
m
p
g
ai
n
g
iv
e
n
b
y
,
=
(
5
)
wh
er
e
N
=n
u
m
b
er
o
f
p
is
to
n
s
,
A
p
=
p
is
to
n
x
-
s
ec
tio
n
,
r
=p
is
to
n
p
itch
r
ad
iu
s
,
an
d
=
s
h
af
t
an
g
u
lar
s
p
ee
d
.
Usi
n
g
(
3
)
an
d
(
4
)
th
e
g
o
v
er
n
in
g
e
q
u
a
tio
n
b
ec
o
m
es
,
̇
+
(
−
0
)
=
(
−
0
)
(
6
)
t
h
is
eq
u
atio
n
im
p
lies
th
at
ch
a
n
g
es in
th
e
ca
n
d
ir
ec
tly
in
f
lu
e
n
ce
th
e
d
is
ch
ar
g
e
p
r
ess
u
r
e
P
d
.
2
.
2
.
Swa
s
h
pla
t
e
dy
na
m
ics
Neg
lectin
g
th
e
s
wash
p
late's
d
y
n
am
ics
an
d
tr
a
n
s
ien
t
co
n
t
r
o
l
p
r
ess
u
r
e
ef
f
ec
ts
,
f
o
r
in
co
m
p
r
ess
ib
le
f
lu
id
th
e
co
n
s
er
v
atio
n
o
f
m
ass
y
ield
:
0
=
1
−
2
+
̇
(
7
)
wh
er
e
1
an
d
2
ar
e
th
e
f
lo
w
r
ates
o
f
th
e
3
-
way
v
al
v
e.
Fro
m
3
-
w
ay
v
alv
e
a
n
aly
s
is
,
1
−
2
=
2
(
8
)
wh
er
e
an
d
x
a
r
e
v
alv
e
,
f
lo
w
g
ain
an
d
d
is
p
lace
m
en
t
r
esp
ec
t
iv
ely
(
p
r
o
v
id
e
d
th
at
th
e
=
1
2
)
.
In
(
7
)
an
d
(
8
)
,
g
i
v
es th
e
g
o
v
er
n
i
n
g
eq
u
atio
n
f
o
r
s
wash
p
late
d
y
n
a
m
ics as:
̇
=
−
(
9
)
2
.
3
.
Va
l
v
e
dis
pla
ce
m
ent
(
x
)
T
h
e
eq
u
atio
n
o
f
m
o
tio
n
o
f
3
-
way
s
p
o
o
l v
alv
e:
=
+
−
0
(
1
0
)
wh
er
e
is
v
alv
e
s
p
r
in
g
r
ate,
is
th
e
v
alv
e
x
-
s
ec
tio
n
al
ar
ea
,
F
x
is
th
e
v
alv
e
f
lo
w
f
o
r
ce
,
a
n
d
0
is
s
p
r
in
g
p
r
elo
ad
o
n
th
e
v
alv
e
at
x
=
0
.
T
h
e
f
lo
w
f
o
r
ce
o
n
th
e
3
-
way
o
p
en
-
ce
n
ter
ed
v
alv
e:
=
−
2
(
1
1
)
w
h
er
e
is
th
e
v
alv
e
f
lo
w
f
o
r
ce
g
ain
.
At
th
e
s
tead
y
o
p
er
atin
g
c
o
n
d
itio
n
s
,
th
e
v
alv
e
s
p
r
in
g
p
r
e
lo
ad
:
0
=
0
(
1
2
)
wh
er
e
0
is
th
e
d
esire
d
p
u
m
p
d
eliv
er
y
p
r
ess
u
r
e.
C
o
m
b
in
i
n
g
(
1
1
)
with
d
esig
n
c
o
n
s
tr
ain
ts
in
to
(
1
0
)
,
t
h
e
eq
u
atio
n
o
f
m
o
tio
n
f
o
r
th
e
3
-
way
s
p
o
o
l v
alv
e
will b
e:
=
(
+
2
)
(
−
0
)
(
1
3
)
2
.
4
.
P
re
s
s
ure
-
co
ntr
o
lled a
x
i
a
l pis
t
o
n
pu
m
ps
dy
na
m
ic
eq
ua
t
io
ns
T
h
e
eq
u
atio
n
o
f
m
o
tio
n
f
o
r
th
e
s
p
o
o
l
v
alv
e
in
d
icate
s
th
at
ad
ju
s
tm
en
ts
to
its
p
o
s
itio
n
ar
e
ex
ec
u
ted
b
ased
o
n
th
e
s
en
s
ed
er
r
o
r
in
th
e
d
is
ch
ar
g
e
p
r
ess
u
r
e.
Utilizin
g
(
6
)
,
(
9
)
,
an
d
(
1
3
)
,
we
c
an
s
u
m
m
ar
ize
th
e
d
y
n
am
ic
e
q
u
atio
n
s
f
o
r
th
e
p
r
e
s
s
u
r
e
-
co
n
tr
o
lled
p
u
m
p
as f
o
llo
ws:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Op
timiz
in
g
d
yn
a
mic
r
esp
o
n
s
e
a
n
d
s
ta
b
ilit
y
o
f
p
r
ess
u
r
e
-
co
n
tr
o
lled
…
(
V
ivek
V
erma
)
775
̇
=
−
(
−
0
)
+
(
−
0
)
(
1
4
)
̇
=
−
2
(
+
2
)
(
−
0
)
(
1
5
)
T
h
e
ch
ar
ac
ter
is
tic
eq
u
atio
n
f
o
r
th
e
d
y
n
a
m
ic
s
y
s
tem
d
ep
icted
in
F
ig
u
r
e
2
ca
n
b
e
f
o
r
m
u
l
ated
u
s
in
g
eith
er
s
tate
s
p
ac
e
m
eth
o
d
s
o
r
t
h
e
L
ap
lace
tr
an
s
f
o
r
m
.
2
+
+
=
0
(
1
6
)
wh
er
e
th
e
co
e
f
f
icien
ts
ar
e
,
=
=
2
(
+
2
)
(
1
7
)
n
o
w,
th
e
tr
a
n
s
f
er
f
u
n
ctio
n
G
(
s
)
o
f
th
e
s
y
s
tem
ca
n
b
e
d
ef
in
ed
as
(
1
8
)
.
(
)
=
(
)
(
)
=
2
+
+
(
1
8
)
On
ce
we
h
av
e
t
h
e
d
esire
d
p
o
les,
we
ca
n
d
esig
n
a
lead
-
la
g
co
m
p
e
n
s
ato
r
to
s
h
if
t
th
e
p
o
les
to
th
e
d
esire
d
lo
ca
tio
n
s
.
T
h
e
lag
-
le
ad
co
m
p
e
n
s
ato
r
co
m
b
in
es
a
g
ain
,
two
p
o
les,
an
d
two
z
er
o
s
,
m
ir
r
o
r
in
g
t
h
e
in
teg
r
atio
n
o
f
a
lag
a
n
d
lead
c
o
m
p
en
s
ato
r
.
Fo
llo
win
g
co
m
m
o
n
elec
tr
o
n
ic
im
p
lem
en
tatio
n
[
2
7
]
,
its
s
tr
u
ctu
r
e
is
:
_
_
(
)
=
1
(
+
+
)
∗
1
(
+
+
)
=
(
+
1
+
1
)
x
(
+
1
+
1
)
(
2
0
)
w
ith
,
>
0
,
>
0
,
=
<
1
,
=
1
=
1
>
0
,
>
0
,
=
>
1
,
=
1
=
1
(
2
1
)
t
he
s
u
b
s
cr
ip
t d
in
d
icate
s
th
e
lead
co
m
p
e
n
s
ato
r
,
an
d
th
e
s
u
b
s
c
r
ip
t g
in
d
icate
s
th
e
lag
co
m
p
e
n
s
ato
r
.
Fig
u
r
e
2
.
Sch
em
atic
d
iag
r
am
o
f
th
e
h
y
d
r
o
-
m
ec
h
a
n
ical
co
n
tr
o
l sy
s
tem
2
.
5
.
Alg
o
rit
hm
:
le
a
d
-
la
g
co
m
pens
a
t
io
n desi
g
n f
o
r
press
ure
-
co
ntr
o
lled a
x
ia
l pis
t
o
n pum
ps
L
ea
d
-
lag
c
o
m
p
en
s
atio
n
en
h
a
n
ce
s
s
tab
ilit
y
an
d
r
esp
o
n
s
e
in
p
r
ess
u
r
e
-
co
n
tr
o
lled
ax
ial
p
is
to
n
p
u
m
p
s
b
y
ad
ju
s
tin
g
p
h
ase
an
d
g
ain
.
T
h
is
alg
o
r
ith
m
d
esig
n
s
a
lead
-
lag
co
m
p
en
s
ato
r
f
o
r
a
v
ar
iab
l
e
d
eliv
er
y
p
u
m
p
to
im
p
r
o
v
e
t
r
an
s
ien
t r
esp
o
n
s
e,
r
e
d
u
ce
s
tead
y
-
s
tate
er
r
o
r
,
an
d
en
s
u
r
e
p
r
ec
is
e
p
r
ess
u
r
e
co
n
tr
o
l.
Inputs:
Steady
-
state error (SSE) e
ss
_specified;
Phase margin (PM
specified
);
Gain x
-
over frequency ω
x
.
Plant Transfer function: G(s) = b / (s
2
+ as + b), 'a' and 'b' are parameters of the plant
Outputs:
Transfer function of the lag
-
lead compensator
Procedure:
1. Increase System Type (if necessary):
Augment system with required poles at s = 0 to meet SSE specs:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
7
,
No
.
2
,
Feb
r
u
a
r
y
20
2
5
:
77
1
-
7
8
0
776
(
)
=
(
)
(
−
)
⁄
Compute K
c
for steady
-
state error
2. Generate Bode Plots:
Plot G
augmented
(s) to analyze system dynamics.
3. Design Lead Compensator:
Compute phase shift at specified gain crossover frequency
:
=
arg
[
(
)
]
Compute the uncompensated phase margin PM
uncompensated
=
180
0
+
∠
(
)
Compute parameters for desired phase
margin:
=
+
10
0
−
,
=
1
−
si
n
(
)
1
+
si
n
(
)
Compute lead compensator's zero and pole:
=
√
,
=
4. Design Lag Compensator:
Determine magnitude at specified gai
n crossover frequency
:
(
)
Compute attenuation required for desired gain margin:
=
1
|
(
)
(
)
|
Compute lag compensator's zero and pole:
=
10
,
=
5. Impleme
ntation:
Choose resistor and capacitor values for compensator design.
Output:
The designed lag
-
lead compensator meets specified input parameters criteria.
End Algorithm
2
.
6
.
L
ea
d
-
la
g
co
m
pens
a
t
o
r
im
plem
ent
a
t
io
n
Og
ata
[
2
9
]
d
is
cu
s
s
ed
im
p
lem
en
tatio
n
s
o
f
an
alo
g
cir
cu
it
f
o
r
all
ty
p
es
o
f
co
m
p
en
s
ato
r
s
.
T
h
e
lead
-
lag
co
m
p
en
s
ato
r
cir
cu
it
u
s
es
two
in
v
er
tin
g
o
p
er
atio
n
al
am
p
l
if
ier
s
in
s
er
ies
to
ad
ju
s
t
p
h
ase
an
d
m
ag
n
itu
d
e
ef
f
ec
tiv
ely
.
T
h
e
f
ir
s
t
am
p
lifi
er
’
s
in
p
u
t
im
p
e
d
an
ce
d
esig
n
e
d
as
r
esis
to
r
R
1
in
s
er
ies
wit
h
ca
p
ac
ito
r
C
1
,
in
p
ar
allel
with
r
esis
to
r
R
3
.
T
h
e
f
ee
d
b
ac
k
im
p
ed
an
ce
is
d
ef
i
n
ed
as
r
esis
to
r
R
2
in
s
er
ies
with
c
ap
ac
ito
r
C
2
,
an
d
in
p
ar
allel
with
r
esis
to
r
R
4
.
T
h
e
s
ec
o
n
d
am
p
lifie
r
is
d
esig
n
ed
w
ith
in
p
u
t
r
esis
to
r
s
R
5
an
d
f
ee
d
b
ac
k
R
6
.
Ass
u
m
in
g
th
at
th
e
o
u
tp
u
t a
m
p
s
ar
e
i
d
ea
l,
th
e
tr
an
s
f
er
f
u
n
ctio
n
f
o
r
th
is
cir
cu
it is
:
(
)
(
)
=
6
4
5
3
[
(
3
+
3
)
1
+
1
]
(
1
1
+
1
)
(
2
2
+
1
)
[
(
2
+
4
)
2
+
1
]
6
4
5
3
.
2
(
1
+
3
)
1
(
2
+
4
)
.
(
+
1
(
1
+
3
)
1
)
(
+
1
1
1
)
.
(
+
1
2
2
)
(
+
1
(
2
+
4
)
2
)
}
(
22
)
c
o
m
p
ar
in
g
th
e
(
2
2
)
a
n
d
(
2
0
)
,
we
g
et,
=
6
4
5
3
,
=
1
(
1
+
3
)
1
,
=
1
1
1
,
=
1
1
+
3
=
1
2
2
,
=
1
(
2
+
4
)
2
,
=
2
+
4
2
}
(
2
3
)
3.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
I
n
th
e
d
esig
n
o
f
a
f
ee
d
b
ac
k
c
o
n
tr
o
l
s
y
s
tem
,
tar
g
etin
g
a
p
h
a
s
e
m
ar
g
in
o
f
3
0
–
6
0
d
eg
r
ee
s
a
n
d
a
g
ai
n
m
ar
g
in
o
f
2
–
1
0
d
B
is
k
ey
to
o
p
tim
al
s
tab
ilit
y
an
d
r
esp
o
n
s
e
[
3
0
]
.
L
ar
g
e
m
ar
g
i
n
s
y
ield
s
tab
ilit
y
b
u
t
s
lo
w
r
esp
o
n
s
e,
wh
ile
s
m
all
m
ar
g
in
s
o
f
f
er
q
u
ic
k
er
r
esp
o
n
s
e
b
u
t
m
ay
in
d
u
ce
o
s
cillatio
n
.
B
alan
cin
g
th
ese
m
ar
g
in
s
is
k
ey
to
m
a
x
im
izin
g
s
y
s
tem
p
er
f
o
r
m
an
ce
[
3
1
]
.
E
m
p
lo
y
in
g
th
e
d
ata
f
r
o
m
th
e
T
ab
le
2
tr
an
s
f
er
f
u
n
ctio
n
f
o
r
t
h
e
s
ec
o
n
d
-
o
r
d
er
u
n
d
er
d
am
p
ed
s
y
s
tem
is
,
(
)
=
10000
2
+
3
+
10000
(
2
4
)
B
y
u
s
in
g
th
e
alg
o
r
ith
m
illu
s
tr
ated
in
s
ec
tio
n
2
.
5
,
th
e
tr
an
s
f
er
f
u
n
ctio
n
o
f
t
h
e
d
esig
n
ed
lead
-
lag
co
m
p
en
s
ato
r
d
ep
icted
in
F
ig
u
r
e
3
with
s
p
ec
if
icatio
n
is
g
iv
en
as:
−
−
=
27
.
3
∗
(
+
1
.
34
)
(
+
1
)
∗
(
+
18
.
66
)
(
+
.
039
)
=
27
.
3
∗
(
2
+
2
.
34
+
1
.
34
)
(
3
+
18
.
7
2
+
0
.
73
)
(
2
5
)
−
−
(
)
=
10000
∗
27
.
3
∗
(
2
+
2
.
34
+
1
.
34
)
(
2
+
3
+
10000
)
(
3
+
18
.
7
2
+
0
.
73
)
(
2
6
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Op
timiz
in
g
d
yn
a
mic
r
esp
o
n
s
e
a
n
d
s
ta
b
ilit
y
o
f
p
r
ess
u
r
e
-
co
n
tr
o
lled
…
(
V
ivek
V
erma
)
777
Fig
u
r
e
3
.
B
lo
ck
d
iag
r
am
o
f
th
e
lead
-
lag
co
m
p
en
s
ato
r
T
h
e
b
o
d
e
p
lo
ts
in
Fig
u
r
e
4
an
d
s
tep
r
esp
o
n
s
es
in
Fig
u
r
e
s
5
to
9
o
f
th
e
u
n
co
m
p
e
n
s
ated
an
d
co
m
p
en
s
ated
s
y
s
tem
ar
e
d
r
a
wn
u
s
in
g
MA
T
L
AB
v
er
s
io
n
R
2
0
2
3
b
f
o
r
ac
ad
em
ic
u
s
e.
An
aly
s
in
g
th
e
r
esu
lts
d
ep
icted
in
F
ig
u
r
e
s
4
t
o
9
s
u
m
m
ar
ized
in
T
ab
le
3
in
d
icate
s
th
at
th
e
b
asic
p
lan
t
Gp
(
s
)
h
a
s
a
p
h
ase
m
ar
g
in
o
f
2
4
.
5
°,
a
g
ain
cr
o
s
s
o
v
er
f
r
eq
u
en
cy
o
f
3
.
3
8
r
ad
/s
,
an
d
a
m
o
d
er
ate
p
er
f
o
r
m
an
ce
with
a
s
ettlin
g
tim
e
o
f
2
.
3
9
s
ec
o
n
d
s
an
d
2
0
.
5
%
o
v
e
r
s
h
o
o
t.
T
h
e
lead
co
m
p
en
s
atio
n
p
r
o
v
i
d
es
a
g
o
o
d
b
alan
ce
,
ac
h
ie
v
in
g
a
p
h
ase
m
ar
g
in
o
f
4
0
.
4
°
an
d
a
g
ain
cr
o
s
s
o
v
er
f
r
eq
u
en
c
y
o
f
3
0
r
ad
/s
,
th
o
u
g
h
it
h
as
a
lo
n
g
e
r
tim
e
d
elay
o
f
1
.
1
s
ec
o
n
d
s
.
I
n
co
n
tr
ast,
th
e
p
r
o
p
o
r
tio
n
al
co
n
t
r
o
l
is
u
n
s
tab
le,
with
th
e
h
ig
h
e
s
t
o
v
er
s
h
o
o
t
o
f
6
0
%,
t
h
e
lo
n
g
est
s
ettlin
g
tim
e
o
f
7
.
4
2
s
ec
o
n
d
s
,
an
d
a
n
u
n
s
tab
le
g
ain
m
ar
g
i
n
.
T
h
e
lag
-
lead
co
m
p
en
s
ated
s
y
s
tem
o
f
f
er
s
th
e
b
est
o
v
er
all
r
esu
lts
,
with
th
e
h
i
g
h
est
p
h
ase
s
tab
ilit
y
m
ar
g
in
o
f
5
5
.
7
°,
lo
w
o
v
er
s
h
o
o
t
o
f
1
2
.
1
%,
an
d
th
e
f
astes
t
s
ettlin
g
tim
e
o
f
1
.
9
5
s
ec
o
n
d
s
.
Fig
u
r
e
4
.
B
o
d
e
p
lo
t f
o
r
u
n
co
m
p
en
s
ated
an
d
co
m
p
en
s
ated
s
y
s
tem
s
Fig
u
r
e
5
.
C
lo
s
ed
lo
o
p
s
tep
r
es
p
o
n
s
e
o
f
t
h
e
G
p
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52
In
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I
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Op
timiz
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°),
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west
o
v
er
s
h
o
o
t
(
1
2
.
1
%),
a
n
d
f
astes
t
s
ettli
n
g
tim
e
(
1
.
9
5
s
ec
o
n
d
s
)
,
m
ak
in
g
it
th
e
m
o
s
t
ef
f
ec
tiv
e
co
n
tr
o
l
s
tr
a
teg
y
th
an
th
e
H
∞
co
n
tr
o
ller
.
Strik
in
g
a
p
r
u
d
en
t
e
q
u
ilib
r
iu
m
b
etwe
en
ef
f
icien
c
y
an
d
d
y
n
am
ic
r
esp
o
n
s
e
is
a
cr
i
tical
asp
ec
t
in
d
esig
n
in
g
a
p
r
e
s
s
u
r
e
-
co
n
tr
o
lled
p
u
m
p
s
y
s
tem
s
u
ited
to
s
p
ec
if
ic
ae
r
o
s
p
ac
e
ap
p
licatio
n
s
.
T
h
is
a
s
p
ec
t
u
n
d
er
s
co
r
es
th
e
r
atio
n
ale
b
eh
in
d
th
e
a
d
o
p
tio
n
o
f
a
la
g
-
lead
co
m
p
en
s
ato
r
,
wh
ich
f
ac
ilit
ates
th
e
o
p
tim
izatio
n
o
f
s
y
s
tem
p
er
f
o
r
m
a
n
ce
wh
ile
ad
d
r
ess
in
g
th
e
in
h
e
r
en
t
tr
ad
e
-
o
f
f
s
b
etwe
en
ef
f
icien
cy
an
d
d
y
n
am
ic
r
es
p
o
n
s
e.
Fu
tu
r
e
wo
r
k
s
h
o
u
ld
co
n
ce
n
tr
ate
o
n
a
d
v
an
ce
d
co
n
tr
o
l
tech
n
iq
u
es,
in
co
r
p
o
r
atin
g
r
ea
l
-
tim
e
test
in
g
,
an
d
ex
p
lo
r
in
g
p
r
ed
ictiv
e
m
eth
o
d
s
lik
e
ad
ap
tiv
e
m
o
d
el
p
r
ed
ictiv
e
co
n
tr
o
l.
I
m
p
r
o
v
in
g
r
o
b
u
s
tn
ess
an
d
tailo
r
in
g
s
tr
ateg
ies
f
o
r
s
p
ec
if
ic
ae
r
o
s
p
ac
e
ap
p
licatio
n
s
will
f
u
r
th
er
en
h
a
n
ce
s
y
s
tem
s
tab
ilit
y
,
r
esp
o
n
s
e,
an
d
o
v
er
all
p
er
f
o
r
m
an
ce
.
RE
F
E
R
E
NC
E
S
[
1
]
N
.
D
.
M
a
n
r
i
n
g
a
n
d
R
.
C
.
F
a
l
e
s
,
H
y
d
r
a
u
l
i
c
c
o
n
t
ro
l
s
y
st
e
m
s
.
J
o
h
n
W
i
l
e
y
& S
o
n
s
,
2
0
1
9
.
[
2
]
S
.
J.
Li
n
a
n
d
A
.
A
k
e
r
s,
“
O
p
t
i
ma
l
c
o
n
t
r
o
l
t
h
e
o
r
y
a
p
p
l
i
e
d
t
o
p
r
e
ss
u
r
e
-
c
o
n
t
r
o
l
l
e
d
a
x
i
a
l
p
i
s
t
o
n
p
u
m
p
d
e
s
i
g
n
,
”
J
o
u
rn
a
l
o
f
D
y
n
a
m
i
c
S
y
s
t
e
m
s,
Me
a
s
u
rem
e
n
t
,
a
n
d
C
o
n
t
r
o
l
,
v
o
l
.
1
1
2
,
n
o
.
3
,
p
p
.
4
7
5
–
4
8
1
,
S
e
p
.
1
9
9
0
,
d
o
i
:
1
0
.
1
1
1
5
/
1
.
2
8
9
6
1
6
7
.
[
3
]
D
.
M
c
C
a
n
d
l
i
s
h
a
n
d
R
.
E
.
D
o
r
e
y
,
“
Th
e
ma
t
h
e
ma
t
i
c
a
l
m
o
d
e
l
l
i
n
g
o
f
h
y
d
r
o
s
t
a
t
i
c
p
u
m
p
s
a
n
d
m
o
t
o
r
s,
”
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
I
n
st
i
t
u
t
i
o
n
o
f
Me
c
h
a
n
i
c
a
l
En
g
i
n
e
e
rs,
P
a
rt
B
:
J
o
u
r
n
a
l
o
f
E
n
g
i
n
e
e
ri
n
g
M
a
n
u
f
a
c
t
u
re
,
v
o
l
.
1
9
8
,
n
o
.
3
,
p
p
.
1
6
5
–
1
7
4
,
1
9
8
4
,
d
o
i
:
1
0
.
1
2
4
3
/
P
I
M
E_
P
R
O
C
_
1
9
8
4
_
1
9
8
_
0
6
2
_
0
2
.
[
4
]
P
.
K
a
l
i
a
f
e
t
i
s
a
n
d
T.
C
o
st
o
p
o
u
l
o
s,
“
M
o
d
e
l
l
i
n
g
a
n
d
si
mu
l
a
t
i
o
n
o
f
a
n
a
x
i
a
l
p
i
s
t
o
n
v
a
r
i
a
b
l
e
d
i
s
p
l
a
c
e
me
n
t
p
u
mp
w
i
t
h
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
,
”
Me
c
h
a
n
i
sm
a
n
d
M
a
c
h
i
n
e
T
h
e
o
r
y
,
v
o
l
.
3
0
,
n
o
.
4
,
p
p
.
5
9
9
–
6
1
2
,
M
a
y
1
9
9
5
,
d
o
i
:
1
0
.
1
0
1
6
/
0
0
9
4
-
1
1
4
X
(
9
4
)
0
0
0
5
7
-
R.
[
5
]
N
.
D
.
M
a
n
r
i
n
g
a
n
d
R
.
E.
J
o
h
n
so
n
,
“
M
o
d
e
l
i
n
g
a
n
d
d
e
s
i
g
n
i
n
g
a
v
a
r
i
a
b
l
e
-
d
i
s
p
l
a
c
e
me
n
t
o
p
e
n
-
l
o
o
p
p
u
m
p
,
”
J
o
u
rn
a
l
o
f
D
y
n
a
m
i
c
S
y
s
t
e
m
s,
Me
a
s
u
rem
e
n
t
,
a
n
d
C
o
n
t
r
o
l
,
v
o
l
.
1
1
8
,
n
o
.
2
,
p
p
.
2
6
7
–
2
7
1
,
Ju
n
.
1
9
9
6
,
d
o
i
:
1
0
.
1
1
1
5
/
1
.
2
8
0
2
3
1
3
.
[
6
]
D
.
L
o
v
r
e
c
a
n
d
E.
D
e
t
i
č
e
k
,
“
I
mp
r
o
v
e
m
e
n
t
o
f
t
h
e
s
t
a
t
i
c
a
l
b
e
h
a
v
i
o
u
r
o
f
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
l
e
d
a
x
i
a
l
p
i
s
t
o
n
p
u
mp
s,”
S
t
r
o
j
n
i
s
k
i
Ve
st
n
i
k
/
J
o
u
r
n
a
l
o
f
M
e
c
h
a
n
i
c
a
l
En
g
i
n
e
e
ri
n
g
,
v
o
l
.
5
5
,
n
o
.
1
2
,
p
p
.
7
6
6
–
7
7
4
,
2
0
0
9
.
[
7
]
N
.
D
.
M
a
n
r
i
n
g
a
n
d
V
.
S
.
M
e
h
t
a
,
“
P
h
y
si
c
a
l
l
i
m
i
t
a
t
i
o
n
s
f
o
r
t
h
e
b
a
n
d
w
i
d
t
h
f
r
e
q
u
e
n
c
y
o
f
a
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
l
e
d
,
a
x
i
a
l
-
p
i
s
t
o
n
p
u
mp
,
”
J
o
u
rn
a
l
o
f
D
y
n
a
m
i
c
S
y
s
t
e
m
s,
M
e
a
s
u
remen
t
a
n
d
C
o
n
t
r
o
l
,
T
ra
n
s
a
c
t
i
o
n
s
o
f
t
h
e
AS
ME
,
v
o
l
.
1
3
3
,
n
o
.
6
,
p
.
0
6
1
0
0
5
,
2
0
1
1
,
d
o
i
:
1
0
.
1
1
1
5
/
1
.
4
0
0
4
0
5
6
.
[
8
]
W
.
K
e
mm
e
t
m
ü
l
l
e
r
,
F
.
F
u
c
h
sh
u
m
e
r
,
a
n
d
A
.
K
u
g
i
,
“
N
o
n
l
i
n
e
a
r
p
r
e
ss
u
r
e
c
o
n
t
r
o
l
o
f
s
e
l
f
-
s
u
p
p
l
i
e
d
v
a
r
i
a
b
l
e
d
i
sp
l
a
c
e
men
t
a
x
i
a
l
p
i
s
t
o
n
p
u
m
p
s
,
”
C
o
n
t
ro
l
E
n
g
i
n
e
e
ri
n
g
Pr
a
c
t
i
c
e
,
v
o
l
.
1
8
,
n
o
.
1
,
p
p
.
8
4
–
9
3
,
2
0
1
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
o
n
e
n
g
p
r
a
c
.
2
0
0
9
.
0
9
.
0
0
6
.
[
9
]
L.
C
h
e
n
,
S
.
Y
e
,
Z
.
C
h
a
n
g
,
X
.
G
o
u
,
a
n
d
K
.
S
u
n
,
“
S
i
m
u
l
a
t
i
o
n
r
e
s
e
a
r
c
h
o
n
t
h
e
r
e
v
o
l
u
t
i
o
n
-
p
r
e
ssu
r
e
p
e
r
f
o
r
ma
n
c
e
o
f
a
n
a
e
r
o
n
a
u
t
i
c
a
l
h
y
d
r
a
u
l
i
c
a
x
i
a
l
p
i
s
t
o
n
p
u
mp
,
”
i
n
2
0
1
6
I
EEE
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
A
i
rcr
a
f
t
U
t
i
l
i
t
y
S
y
s
t
e
m
s
(
A
U
S
)
,
O
c
t
.
2
0
1
6
,
p
p
.
1
2
4
7
–
1
2
5
1
,
d
o
i
:
1
0
.
1
1
0
9
/
A
U
S
.
2
0
1
6
.
7
7
4
8
2
3
0
.
[
1
0
]
L.
K
u
mar
a
n
d
N
.
P
.
M
a
n
d
a
l
,
“
P
r
e
ss
u
r
e
c
o
n
t
r
o
l
o
f
v
a
r
i
a
b
l
e
d
i
s
p
l
a
c
e
me
n
t
r
a
d
i
a
l
p
i
st
o
n
p
u
m
p
w
i
t
h
P
I
D
c
o
n
t
r
o
l
l
e
r
,
”
Ma
t
e
r
i
a
l
s
T
o
d
a
y
:
Pro
c
e
e
d
i
n
g
s
,
v
o
l
.
4
5
,
n
o
.
6
,
p
p
.
5
1
5
8
–
5
1
6
5
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
m
a
t
p
r
.
2
0
2
1
.
0
1
.
6
9
2
.
[
1
1
]
H
o
n
g
l
i
u
D
u
a
n
d
N
.
D
.
M
a
n
r
i
n
g
,
“
A
s
i
n
g
l
e
-
a
c
t
u
a
t
o
r
c
o
n
t
r
o
l
d
e
si
g
n
f
o
r
h
y
d
r
a
u
l
i
c
v
a
r
i
a
b
l
e
d
i
s
p
l
a
c
e
me
n
t
p
u
m
p
s,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
2
0
0
1
Am
e
r
i
c
a
n
C
o
n
t
r
o
l
C
o
n
f
e
re
n
c
e
.
(
C
a
t
.
N
o
.
0
1
C
H
3
7
1
4
8
)
,
2
0
0
1
,
v
o
l
.
6
,
p
p
.
4
4
8
4
–
4
4
8
9
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
.
2
0
0
1
.
9
4
5
6
8
5
.
[
1
2
]
P
.
T.
D
e
a
n
a
n
d
R
.
C
.
F
a
l
e
s,
“
M
o
d
e
r
n
c
o
n
t
r
o
l
d
e
si
g
n
f
o
r
a
v
a
r
i
a
b
l
e
d
i
s
p
l
a
c
e
m
e
n
t
h
y
d
r
a
u
l
i
c
p
u
m
p
,
”
i
n
2
0
0
7
Am
e
ri
c
a
n
C
o
n
t
r
o
l
C
o
n
f
e
re
n
c
e
,
J
u
l
.
2
0
0
7
,
p
p
.
3
5
3
5
–
3
5
4
0
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
.
2
0
0
7
.
4
2
8
2
8
2
6
.
[
1
3
]
O
.
G
a
d
,
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l
,
2
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3
.
[
2
6
]
S
.
Q
i
a
n
,
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.
Z
h
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[
2
7
]
Y
.
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g
,
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a
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a
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H
y
d
r
a
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c
s &
P
n
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m
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s
,
v
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4
7
,
n
o
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3
,
p
p
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9
–
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,
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3
,
[
O
n
l
i
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e
]
.
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v
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:
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[
2
8
]
W
.
Ji
a
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a
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.
,
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st
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[
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9
]
K
.
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[
3
0
]
S.
-
H
.
K
i
m,
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1
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p
p
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3
9
–
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3
.
[
3
1
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L.
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.
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a
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c
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M
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2
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.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Viv
e
k
Ve
r
m
a
is
a
p
a
rt
-
ti
m
e
re
se
a
rc
h
sc
h
o
lar
a
t
th
e
De
p
a
rtme
n
t
o
f
M
e
c
h
a
n
ica
l
En
g
i
n
e
e
rin
g
a
t
Am
it
y
S
c
h
o
o
l
o
f
En
g
i
n
e
e
rin
g
a
n
d
Tec
h
n
o
l
o
g
y
,
A
m
it
y
Un
i
v
e
rsity
,
L
u
c
k
n
o
w.
He
h
o
l
d
s
B.
E.
i
n
In
d
u
str
ial
E
n
g
i
n
e
e
rin
g
fro
m
IIT
Ro
o
rk
e
e
(f
o
rm
e
rly
Un
iv
e
rsity
o
f
Ro
o
rk
e
e
),
In
d
ia
a
n
d
M
.
Tec
h
.
i
n
P
r
o
d
u
c
ti
o
n
En
g
i
n
e
e
rin
g
fro
m
M
NN
IT,
Allah
a
b
a
d
,
In
d
ia.
C
u
rre
n
tl
y
h
e
is
wo
rk
i
n
g
a
s
As
sista
n
t
P
r
o
fe
ss
o
r
a
t
De
p
a
rtme
n
t
o
f
M
e
c
h
a
n
ica
l
E
n
g
i
n
e
e
rin
g
,
ASE
T,
Am
it
y
Un
iv
e
rsity
,
Lu
c
k
n
o
w,
h
a
s
v
a
st
e
x
p
e
rien
c
e
o
f
tea
c
h
in
g
a
b
o
u
t
2
0
y
e
a
rs.
He
u
se
d
to
h
o
ld
se
v
e
ra
l
a
d
m
i
n
istrativ
e
p
o
sts
a
t
th
e
De
p
a
rtme
n
t
a
n
d
Un
iv
e
rsity
lev
e
ls.
He
is
a
m
e
m
b
e
r
o
f
se
v
e
ra
l
p
ro
fe
ss
io
n
a
l
b
o
d
ies
su
c
h
a
s
S
AE
,
IET
(UK
),
a
n
d
IAENG
.
He
h
a
s
su
p
e
rv
ise
d
1
0
m
a
ste
rs
a
n
d
m
o
re
th
a
n
5
0
u
n
d
e
r
g
ra
d
u
a
te
st
u
d
e
n
ts.
He
h
a
s
o
rg
a
n
ize
d
se
v
e
ra
l
F
DP
c
o
n
su
lt
a
n
c
y
p
r
o
jec
ts
a
s
we
ll
.
He
h
a
s
re
se
a
r
c
h
in
tere
st
in
m
a
th
e
m
a
ti
c
a
l
m
o
d
e
ll
in
g
o
f
m
e
c
h
a
n
ica
l
sy
ste
m
s
a
n
d
c
o
m
p
u
tati
o
n
a
l
fl
u
i
d
d
y
n
a
m
ics
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
v
v
e
rm
a
@lk
o
.
a
m
it
y
.
e
d
u
.
Dr
.
S
a
c
h
in
K
u
m
a
r
a
P
h
.
D.
i
n
El
e
c
tro
n
ics
,
M
.
Tec
h
.
a
n
d
B.
E
i
n
El
e
c
tro
n
ics
a
nd
Co
m
m
u
n
ica
ti
o
n
,
p
re
se
n
tl
y
with
Am
it
y
Un
iv
e
rsity
,
Lu
c
k
n
o
w
Ca
m
p
u
s.
He
h
a
s
a
lmo
st
2
0
y
e
a
rs
o
f
a
c
a
d
e
m
ic
a
n
d
re
se
a
rc
h
e
x
p
e
r
ien
c
e
.
His
re
se
a
rc
h
i
n
tere
st
i
n
c
l
u
d
e
s
a
p
p
li
c
a
ti
o
n
s
o
f
b
i
o
-
m
e
d
ica
l
sig
n
a
l
p
r
o
c
e
ss
in
g
,
m
a
c
h
in
e
lea
rn
in
g
,
a
rti
ficia
l
i
n
telli
g
e
n
c
e
a
n
d
a
p
p
li
c
a
ti
o
n
s
o
f
wire
les
s
se
n
so
r
n
e
two
rk
s.
He
is
a
n
a
c
ti
v
e
m
e
m
b
e
r
o
f
n
u
m
b
e
r
o
f
p
ro
fe
ss
io
n
a
l
b
o
d
ies
IEE
E,
IET
E,
IAENG
,
IS
C
a
n
d
IET
(U
K),
h
e
h
a
s
p
u
b
li
sh
e
d
m
o
re
th
a
n
8
0
re
se
a
rc
h
p
a
p
e
rs,
b
o
o
k
c
h
a
p
ters
,
a
n
d
a
rti
c
les
in
a
n
u
m
b
e
r
re
p
u
te
d
J
o
u
r
n
a
ls
i
n
d
e
x
e
d
in
S
COPU
S
a
n
d
S
CI
a
n
d
c
o
n
tri
b
u
ted
2
b
o
o
k
s
with
i
n
ter
n
a
ti
o
n
a
l
p
u
b
li
sh
e
rs.
He
is
a
n
a
c
ti
v
e
m
e
m
b
e
r
o
f
e
d
i
to
rial
b
o
a
rd
/re
v
iew
e
r
in
v
a
ri
o
u
s
re
p
u
te
d
jo
u
rn
a
ls
.
He
h
a
s
b
e
e
n
i
n
stru
m
e
n
t
a
l
in
o
r
g
a
n
izin
g
n
u
m
b
e
r
o
f
in
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s,
h
a
s
g
i
v
e
n
in
v
it
e
d
talk
s,
a
n
d
c
h
a
ire
d
v
a
rio
u
s
tec
h
n
ica
l
se
ss
io
n
s
i
n
n
a
ti
o
n
a
l
a
s
we
ll
a
s
in
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s
of
re
p
u
te.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sk
u
m
a
r3
@lk
o
.
a
m
it
y
.
e
d
u
.
Dr
.
Apu
r
v
a
Ana
n
d
c
u
rre
n
tl
y
h
o
l
d
s
th
e
p
o
siti
o
n
o
f
P
ro
fe
ss
o
r
a
n
d
Dire
c
to
r
a
t
M
a
h
a
ra
n
a
P
ra
tap
En
g
i
n
e
e
rin
g
Co
ll
e
g
e
,
Ka
n
p
u
r,
sh
o
wc
a
sin
g
a
c
a
re
e
r
sp
a
n
n
in
g
o
v
e
r
two
d
y
n
a
m
ic d
e
c
a
d
e
s.
In
h
is p
re
v
i
o
u
s
ro
le,
he
se
rv
e
d
a
s th
e
P
r
o
fe
ss
o
r
a
n
d
De
a
n
a
t
BBD Un
iv
e
rsit
y
in
L
u
c
k
n
o
w
fro
m
2
0
1
7
t
o
2
0
2
3
.
His
a
c
a
d
e
m
ic
jo
u
r
n
e
y
i
n
c
lu
d
e
s
k
e
y
ro
les
a
t
re
n
o
wn
e
d
in
stit
u
ti
o
n
s,
n
o
tab
l
y
ABES
E
n
g
i
n
e
e
rin
g
Co
l
leg
e
a
n
d
Am
it
y
Un
i
v
e
risty
,
wh
e
re
h
e
se
rv
e
d
a
s
P
ro
fe
ss
o
r
a
n
d
He
a
d
o
f
th
e
De
p
a
rtme
n
t.
Ho
ld
in
g
a
P
h
.
D.
i
n
M
e
c
h
a
n
ica
l
En
g
i
n
e
e
rin
g
a
n
d
M
a
ste
r'
s
in
M
e
c
h
a
n
ica
l
E
n
g
in
e
e
rin
g
a
n
d
a
Ba
c
h
e
lo
r'
s
in
I
n
d
u
str
ial
a
n
d
P
ro
d
u
c
ti
o
n
En
g
i
n
e
e
rin
g
.
He
sc
h
o
larly
imp
a
c
t
is ev
id
e
n
t
i
n
h
is
3
0
p
u
b
li
c
a
ti
o
n
s,
g
a
rn
e
rin
g
4
0
1
c
it
a
ti
o
n
s a
n
d
a
c
h
iev
in
g
a
n
imp
re
ss
iv
e
h
-
i
n
d
e
x
o
f
0
5
.
In
t
h
e
re
a
lm
o
f
g
l
o
b
a
l
c
o
ll
a
b
o
ra
ti
o
n
,
he
se
rv
e
d
a
s
P
ro
g
ra
m
Ch
a
ir
f
o
r
se
v
e
ra
l
i
n
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s,
h
is
c
o
n
tr
ib
u
ti
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