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1148
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1148
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a
m
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s
in
in
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K
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Hy
b
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Mix
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q
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Halb
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Po
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E
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Nu
clea
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d
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1.
I
NT
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D
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f
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m
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s
s
tu
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in
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d
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ad
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ab
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to
b
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m
o
d
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th
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tr
an
s
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t
d
y
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am
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f
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m
p
lex
s
y
s
tem
s
ac
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v
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s
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.
T
h
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two
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d
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am
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at
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im
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ltan
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ly
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s
d
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a
m
ics
an
d
d
is
cr
ete
-
ev
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t
d
y
n
a
m
ics
[
1
]
–
[
3
]
.
Sy
s
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s
ex
h
ib
itin
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in
ter
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b
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T
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s
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b
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m
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u
s
in
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au
to
m
ata
[
4
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o
r
Petr
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[
5
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,
wh
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aly
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aim
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I
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&
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N:
2088
-
8
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Hyb
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co
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mixe
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…
(
Ta
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is
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)
1149
d
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T
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[
6
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–
[
8
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an
d
s
tab
ilit
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[
9
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,
[
1
0
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.
Nu
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2
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an
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1
4
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T
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1
5
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[
1
6
]
p
r
o
p
o
s
ed
a
n
o
v
el
o
b
s
er
v
er
b
ased
o
n
lin
ea
r
h
y
b
r
id
m
o
d
els,
an
d
n
u
m
er
o
u
s
ap
p
licatio
n
s
[
1
7
]
,
[
1
8
]
h
a
v
e
in
v
esti
g
ated
e
x
ten
d
i
n
g
id
en
tific
atio
n
tech
n
iq
u
es
f
r
o
m
lin
ea
r
s
y
s
tem
s
to
h
y
b
r
id
d
y
n
am
ical
s
y
s
tem
s
.
Fin
ally
,
s
to
ch
asti
c
h
y
b
r
id
s
y
s
tem
s
h
av
e
b
ee
n
u
s
ed
wh
e
n
u
n
c
er
tain
ty
p
ar
am
ete
r
s
ar
e
p
r
esen
t in
th
e
m
o
d
el
[
1
9
]
.
T
h
is
s
tu
d
y
p
r
esen
ts
a
m
o
d
elin
g
an
d
s
im
u
latio
n
ap
p
r
o
ac
h
f
o
r
d
ev
elo
p
in
g
a
m
o
d
el
p
r
ed
icti
v
e
co
n
tr
o
l
(
MPC
)
law
ad
ap
ted
to
a
s
p
ec
i
f
ic
k
in
d
o
f
h
y
b
r
id
d
y
n
am
ical
s
y
s
tem
s
.
T
h
e
ML
D
m
o
d
elin
g
f
r
am
ewo
r
k
e
n
ab
les
th
e
in
teg
r
atio
n
o
f
m
u
lti
-
m
o
d
el
p
r
ed
ictiv
e
co
n
tr
o
l te
ch
n
iq
u
es a
n
d
p
r
o
v
id
es th
e
m
ath
em
atica
l
f
o
u
n
d
atio
n
f
o
r
th
e
p
r
o
p
o
s
ed
m
o
d
elin
g
a
p
p
r
o
ac
h
.
T
h
e
m
ai
n
o
b
jectiv
e
is
to
as
s
ess
th
e
ex
ten
t
to
wh
ich
th
e
s
e
f
o
r
m
alis
m
s
an
d
m
eth
o
d
s
ca
n
ad
d
r
ess
th
e
ch
allen
g
es
ass
o
ciate
d
wi
th
h
y
b
r
i
d
s
y
s
tem
m
o
d
elin
g
,
p
ar
ticu
la
r
ly
in
ter
m
s
o
f
th
e
f
id
elity
o
f
d
y
n
am
ic
b
eh
av
i
o
r
r
ep
r
esen
tatio
n
,
d
esig
n
co
m
p
le
x
ity
,
an
d
c
o
m
p
u
tatio
n
al
b
u
r
d
en
.
T
h
is
p
ap
er
is
o
r
g
an
ized
in
to
d
i
f
f
er
en
t sectio
n
s
as f
o
llo
ws:
T
h
e
s
ec
o
n
d
s
ec
tio
n
d
escr
ib
es th
e
m
o
d
elin
g
m
eth
o
d
b
ased
o
n
th
e
m
ix
ed
d
y
n
am
ic
lo
g
ic
(
MD
L
)
f
r
am
e
wo
r
k
.
Nex
t,
th
e
m
u
lti
-
m
o
d
el
ML
D
ap
p
r
o
ac
h
is
d
ev
elo
p
e
d
in
s
ec
tio
n
3
,
f
o
llo
w
ed
b
y
s
ec
tio
n
4
,
wh
ich
p
r
esen
t
s
th
e
h
y
b
r
id
p
r
ed
ictiv
e
c
o
n
tr
o
l
(
HM
PC
)
s
tr
ateg
y
,
wh
ich
r
elies
o
n
th
e
m
u
lti
-
MD
L
m
o
d
el
an
d
d
escr
ib
es
th
e
m
ath
em
atica
l
tr
an
s
f
o
r
m
atio
n
o
f
th
e
co
n
tr
o
l
lo
w
cr
iter
ia
in
to
a
m
i
x
ed
-
in
te
g
er
q
u
ad
r
atic
o
p
tim
izatio
n
(
MI
QP)
.
Sectio
n
5
d
escr
ib
es
th
e
e
x
p
er
im
en
tal
s
etu
p
,
co
m
p
o
s
ed
o
f
th
r
ee
in
ter
co
n
n
e
cted
s
p
h
er
ical
tan
k
s
.
Fin
ally
,
s
ec
tio
n
6
co
n
clu
d
es
th
e
wo
r
k
with
r
em
ar
k
s
an
d
f
u
tu
r
e
p
er
s
p
ec
tiv
es.
2.
M
UL
T
I
P
L
E
M
O
D
E
L
M
L
D
SYST
E
M
S
T
h
e
m
u
ltip
le
-
ML
D
m
o
d
elin
g
f
r
am
ewo
r
k
is
b
ased
o
n
th
e
p
r
i
n
cip
le
o
f
tr
an
s
f
o
r
m
in
g
l
o
g
ical
r
elatio
n
s
,
d
is
cr
ete
d
y
n
am
ics,
an
d
lo
g
ic
al
s
u
b
ject
to
co
n
s
tr
ain
ts
in
t
o
lin
ea
r
m
ix
ed
in
eq
u
alities
.
T
h
e
in
teg
r
atio
n
o
f
in
eq
u
alities
in
a
co
n
tin
u
o
u
s
-
tim
e
d
y
n
am
ic
will
b
e
m
o
d
eled
b
y
lin
ea
r
d
if
f
er
en
ce
eq
u
atio
n
s
.
T
h
e
m
ix
ed
lo
g
ical
d
y
n
am
ic
m
o
d
el
d
e
v
elo
p
ed
f
o
r
ea
c
h
s
u
b
s
y
s
tem
is
d
escr
i
b
ed
b
y
a
s
tate
s
p
ac
e
an
d
in
eq
u
ality
c
o
n
s
tr
ain
ts
eq
u
atio
n
s
[
1
1
]
,
[
2
0
]
.
{
+
1
=
+
1
+
2
+
3
=
+
1
+
2
+
3
2
+
3
≤
1
+
4
+
5
(
1
)
W
h
er
e
,
{
}
=
1
…
3
,
,
{
}
=
1
…
3
,
{
}
=
1
…
5
(
=
1
…
)
ar
e
m
atr
ices
th
at
d
e
s
cr
ib
e
th
e
d
y
n
am
ics
tr
an
s
ien
t
b
eh
a
v
io
r
o
f
th
e
s
y
s
tem
with
k
n
o
w
n
d
im
e
n
s
io
n
s
.
T
h
e
v
ar
iab
les
x
r
ep
r
esen
t
s
th
e
lo
g
ical
a
n
d
co
n
tin
u
o
u
s
s
tates,
y
th
e
co
n
tin
u
o
u
s
an
d
lo
g
ical
o
u
tp
u
ts
,
an
d
[
]
th
e
co
n
tin
u
o
u
s
an
d
lo
g
i
ca
l
in
p
u
ts
.
∈
{
0
,
1
}
an
d
ar
e
au
x
iliar
y
lo
g
ical
an
d
co
n
tin
u
o
u
s
v
ar
iab
les,
r
esp
ec
ti
v
ely
.
I
n
d
ex
d
en
o
te
t
h
e
lo
o
k
u
p
o
f
th
e
m
o
d
el
at
th
e
s
elec
ted
ar
ea
,
co
n
s
is
ts
o
f
b
in
ar
y
au
x
iliar
y
v
a
r
iab
les
th
at
ar
e
n
o
t
p
ar
t
o
f
∆
,
ℓ
an
d
∈
ℛ
with
≤
an
d
∈
ℛ
×
{
0
,
1
}
ℓ
,
wh
er
e,
≤
an
d
ℓ
≤
ℓ
.
T
h
er
ef
o
r
e,
ea
ch
s
im
p
lifie
d
ML
D
m
o
d
el
is
ass
o
ciate
d
wi
th
a
s
et
o
f
co
n
s
tr
ain
ts
d
ef
in
e
d
b
y
∆
.
T
h
e
au
x
iliar
y
v
ar
iab
les
will
b
e
i
n
tr
o
d
u
ce
d
d
u
r
i
n
g
t
h
e
tr
an
s
f
o
r
m
atio
n
o
f
p
r
o
p
o
s
itio
n
a
l
lo
g
ic
in
t
o
lin
ea
r
in
eq
u
alities
.
3.
M
O
DE
L
I
NG
O
F
A
SPH
E
RI
CAL T
ANK
B
E
NCH
M
ARK
USI
NG
A
H
YB
R
I
D
F
RA
M
E
WO
RK
T
h
e
b
en
c
h
m
ar
k
d
e
p
icted
in
Fi
g
u
r
e
1
is
co
m
p
le
x
,
ch
ar
ac
ter
iz
ed
b
y
s
tr
o
n
g
n
o
n
lin
ea
r
ity
a
n
d
s
ig
n
if
ican
t
co
u
p
lin
g
am
o
n
g
th
e
p
r
o
ce
s
s
'
s
d
if
f
er
en
t
s
tates.
I
t
h
as
b
ee
n
m
o
d
eled
u
s
in
g
th
e
ML
D
f
r
am
ewo
r
k
.
T
h
e
co
r
r
esp
o
n
d
in
g
m
ath
em
atica
l
ex
p
r
ess
io
n
s
wer
e
d
er
iv
ed
u
s
in
g
s
tan
d
ar
d
tech
n
iq
u
es
d
escr
ib
ed
in
[
2
0
]
,
[
2
1
]
,
in
co
r
p
o
r
atin
g
c
o
n
tin
u
o
u
s
an
d
b
in
ar
y
a
u
x
iliar
y
v
ar
iab
les in
tr
o
d
u
ce
d
d
u
r
i
n
g
th
e
m
o
d
elin
g
s
tag
e.
T
h
e
d
if
f
e
r
en
tial
eq
u
atio
n
s
ar
e
d
is
cr
etize
d
u
s
in
g
th
e
f
o
r
war
d
d
if
f
er
e
n
ce
ap
p
r
o
x
im
atio
n
,
wh
er
e
ℎ
̇
(
)
is
r
ep
lace
d
b
y
(
ℎ
+
1
−
ℎ
)
⁄
,
with
d
ef
in
in
g
t
h
e
s
am
p
lin
g
tim
e.
W
e
d
ef
i
n
e:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
3
,
J
u
n
e
20
2
6
:
1
1
4
8
-
1
1
5
8
1150
{
=
[
ℎ
1
ℎ
2
ℎ
3
]
=
[
1
2
]
=
[
1
2
13
23
]
=
[
01
02
03
]
=
[
13
23
01
02
03
1
2
]
(
2
)
W
e
ca
n
wr
ite
th
e
r
esu
ltin
g
ex
p
r
ess
io
n
as
(
3
)
.
{
ℎ
1
+
1
=
ℎ
1
+
1
(
1
−
1
1
−
13
13
−
1
1
)
ℎ
2
+
1
=
ℎ
2
+
1
(
2
−
1
2
−
23
23
−
2
2
)
ℎ
3
+
1
=
ℎ
3
+
1
(
1
1
+
13
13
+
1
2
+
23
23
−
3
3
)
=
(
3
)
Ho
wev
er
,
th
e
elem
en
ts
o
f
th
e
m
atr
ices
,
with
=
1
,
…
5
)
in
clu
d
e
th
e
co
n
s
tr
ain
ts
,
as
wel
l
as
th
e
in
eq
u
aliti
e
s
ar
is
in
g
f
r
o
m
th
e
lo
g
ical
s
tatem
en
ts
o
f
th
e
th
r
ee
-
tan
k
s
y
s
tem
.
An
o
r
g
an
ized
s
et
o
f
tr
a
n
s
f
o
r
m
atio
n
r
u
les
m
u
s
t
b
e
a
p
p
lied
in
o
r
d
e
r
to
f
o
r
m
u
late
a
h
y
b
r
id
s
y
s
tem
in
s
id
e
th
e
ML
D
f
r
am
ewo
r
k
.
T
h
e
f
o
llo
win
g
elem
en
ts
ar
e
p
r
esen
t in
th
e
f
in
al
m
o
d
el:
−
T
h
r
ee
(
0
3
)
s
tates (
th
r
ee
(
3
)
co
n
tin
u
o
u
s
)
−
Six
(
0
6
)
in
p
u
t v
a
r
iab
les (
two
(
2
)
co
n
tin
u
o
u
s
,
f
o
u
r
(
4
)
b
in
ar
y
)
−
T
h
r
ee
(
0
3
)
o
u
tp
u
t
v
ar
iab
les (
th
r
ee
(
0
3
)
co
n
tin
u
o
u
s
,
ze
r
o
(
0
)
b
in
ar
y
)
−
Sev
en
(
0
7
)
co
n
ti
n
u
o
u
s
v
ar
iab
l
es o
f
th
e
au
x
iliar
y
k
in
d
−
T
h
r
ee
(
0
3
)
b
in
ar
y
v
ar
iab
les o
f
th
e
au
x
iliar
y
k
in
d
−
Fo
r
ty
-
f
o
u
r
4
4
m
ix
ed
-
in
teg
er
lin
ea
r
in
eq
u
alities
T
h
e
m
o
d
el
i
n
(
3
)
is
m
ad
e
u
p
o
f
th
r
ee
s
tate
v
ar
iab
les,
s
ix
in
p
u
ts
,
an
d
th
r
ee
o
u
tp
u
ts
,
alo
n
g
with
au
x
iliar
y
v
ar
iab
les
-
th
r
ee
lo
g
ical
an
d
s
ev
en
co
n
tin
u
o
u
s
,
an
d
f
o
r
ty
-
f
o
u
r
m
ix
ed
in
teg
er
lin
ea
r
in
e
q
u
ality
co
n
s
tr
ain
ts
.
Fig
u
r
e
1
.
T
h
r
ee
-
tan
k
s
p
h
er
ical
s
y
s
tem
(
Gu
r
s
k
i)
4.
M
UL
T
I
P
L
E
-
M
O
D
E
L
P
R
E
DICT
I
V
E
CO
NT
RO
L
DE
SI
G
N
F
O
R
H
YB
RID SY
ST
E
M
S
Nu
m
er
o
u
s
s
tu
d
ies
[
1
1
]
–
[
1
3
]
,
[
2
0
]
p
r
esen
t
MPC
as
a
f
r
am
e
wo
r
k
f
o
r
h
y
b
r
id
d
y
n
am
ical
s
y
s
tem
s
th
at
u
tili
ze
an
ML
D
r
ep
r
esen
tatio
n
co
m
b
in
ed
with
a
m
ix
ed
q
u
ad
r
atic
o
p
tim
izatio
n
s
o
lv
er
.
T
h
e
MPC
co
n
tr
o
l
Q
2
P
u
mp
2
FT
-
02
CV
-
02
V
1
V
2
h
0
V
23
V
13
T
1
T
2
h
1
h
2
h
m
a
x
T
3
h
3
Q
1
P
u
mp
1
FT
-
01
CV
-
01
V
N3
V
L2
V
L1
Q
L1
Q
N3
Q
L2
E
v
acu
atio
n
o
f
leak
a
g
e li
q
u
id
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:
2088
-
8
7
0
8
Hyb
r
id
s
ystem
s
mo
d
ellin
g
a
n
d
co
n
tr
o
l u
s
in
g
m
u
ltip
le
mixe
d
lo
g
ica
l
…
(
Ta
h
a
r
B
en
a
is
s
a
)
1151
ap
p
r
o
ac
h
u
s
es
a
m
o
d
el
to
p
r
e
d
ict
th
e
f
u
tu
r
e
tr
an
s
ien
t
o
u
tp
u
t
at
a
s
p
ec
if
ied
p
r
e
d
ictio
n
tim
e
h
o
r
izo
n
,
b
ase
d
o
n
cu
r
r
e
n
t
o
b
s
er
v
atio
n
s
o
r
m
e
asu
r
em
en
ts
[
2
2
]
.
At
ea
ch
s
am
p
le
in
ter
v
al,
th
e
p
r
ed
ictio
n
en
ab
les
th
e
co
n
tr
o
ller
to
d
eter
m
in
e
f
u
tu
r
e
co
n
tr
o
l
in
p
u
ts
b
y
m
in
im
izi
n
g
a
r
ele
v
an
t
co
s
t
f
u
n
ctio
n
wh
ile
ad
h
e
r
in
g
to
co
n
s
tr
ain
ts
.
T
h
e
id
ea
l seq
u
en
ce
is
in
itially
in
p
u
t to
th
e
p
lan
t a
t th
e
s
u
b
s
eq
u
en
t
tim
e
s
am
p
lin
g
s
tep
,
af
ter
wh
i
ch
th
e
o
p
tim
izatio
n
cr
iter
io
n
is
r
ep
ea
ted
u
s
in
g
r
ev
is
ed
p
r
o
ce
s
s
m
ea
s
u
r
em
en
ts
to
d
eliv
er
th
e
n
ec
ess
ar
y
f
ee
d
b
ac
k
co
n
tr
o
l
ac
tio
n
in
r
ea
l tim
e.
T
h
e
ML
D
m
o
d
el
is
u
s
ed
b
y
m
u
ltip
le
MPC
p
r
ed
ictiv
e
co
n
tr
o
l
s
tr
ateg
ies
to
s
y
n
th
esize
a
h
y
b
r
id
co
n
tr
o
ller
.
Fo
r
th
is
,
th
e
in
d
e
x
k
d
en
o
te
th
e
p
r
esen
t
tim
e,
(
)
th
e
cu
r
r
en
t
s
tate
-
s
p
ac
e,
(
,
)
an
eq
u
ili
b
r
iu
m
s
tate
o
r
r
ef
er
e
n
ce
v
al
u
e
to
r
ea
ch
,
+
th
e
f
in
al
tim
e
p
r
e
d
ictio
n
,
we
aim
to
co
m
p
u
te
t
h
e
s
eq
u
e
n
ce
o
f
f
u
tu
r
e
co
n
tr
o
l
i
n
p
u
ts
+
−
1
=
{
(
)
,
…
(
+
−
1
)
}
g
o
f
r
o
m
th
e
s
t
ate
(
)
to
b
y
m
in
im
izin
g
th
e
cr
iter
io
n
d
ef
in
ed
as
(
4
)
:
{
+
−
1
+
−
1
+
−
1
}
(
)
=
∑
(
‖
+
/
−
‖
5
2
+
‖
+
/
−
‖
2
2
−
1
=
0
+
‖
+
/
−
‖
3
2
+
‖
+
/
−
‖
4
2
)
+
∑
‖
+
/
−
‖
1
2
−
1
=
0
(
4
)
W
h
er
e
‖
‖
2
=
,
,
=
1
,
…
5
d
ef
in
e
weig
h
tin
g
m
atr
ices a
n
d
=
≥
0
f
o
r
=1
,
4.
N
d
en
o
tes
th
e
p
r
ed
ictio
n
tim
e
h
o
r
izo
n
f
o
r
t
h
e
o
u
tp
u
t,
w
h
er
ea
s
an
d
d
en
o
te
th
e
v
alu
es
o
f
th
e
au
x
iliar
y
v
ar
iab
les
r
elate
d
to
th
e
s
etp
o
in
t,
d
eter
m
in
e
d
b
y
s
o
lv
in
g
an
MI
QP
p
r
o
b
lem
s
u
b
ject
to
in
e
q
u
ality
co
n
s
tr
ain
ts
.
T
h
e
o
p
tim
al
s
o
lu
ti
o
n
is
ex
p
r
ess
ed
b
y
{
+
−
1
(
)
}
=
0
,
…
−
1
an
d
ca
n
b
e
co
m
p
u
te
d
at
ea
ch
s
am
p
lin
g
tim
e.
Nev
er
th
eless
,
s
o
lely
th
e
in
itial
in
p
u
t
u
(
k
)
o
f
th
is
s
eq
u
e
n
ce
is
im
p
lem
en
ted
in
th
e
s
y
s
t
em
.
T
h
e
id
ea
l
in
p
u
t
co
n
tr
o
l
[
(
+
1
)
,
…
(
+
−
1
)
]
is
th
er
ea
f
ter
d
is
r
eg
ar
d
ed
,
a
n
d
th
e
e
n
tire
o
p
tim
izatio
n
p
r
o
g
r
a
m
is
r
e
p
ea
ted
at
ea
ch
in
s
tan
t
(
k+1
)
.
T
h
e
we
ig
h
tin
g
m
atr
ix
Q
1
,
Q
2
,
Q
4
an
d
Q
5
ar
e
cr
u
cial
an
d
p
ar
ticu
lar
l
y
im
p
o
r
tan
t
,
s
in
ce
th
ey
p
r
o
v
id
e
th
e
tr
a
d
e
-
o
f
f
b
et
wee
n
th
e
ex
er
tio
n
o
f
co
n
tr
o
l
a
ctio
n
s
an
d
th
e
ac
cu
r
ac
y
o
f
f
o
l
lo
win
g
th
e
s
etp
o
in
t
tr
ac
k
in
g
.
5.
H
YB
RID
M
O
DE
L
P
R
E
DIC
T
I
V
E
CO
NT
RO
L
(
H
M
P
C)
T
h
e
m
ath
em
atica
l
r
elatio
n
s
h
i
p
o
f
th
e
o
p
tim
izatio
n
cr
iter
io
n
o
n
th
e
o
u
tp
u
t
v
ar
iab
les,
ex
p
r
ess
ed
b
y
(
4
)
,
is
r
ef
o
r
m
u
lated
as
a
MI
QP
p
r
o
b
lem
.
T
h
e
q
u
ad
r
atic
cr
it
er
io
n
f
u
n
ctio
n
p
en
alize
s
d
ev
ia
tio
n
s
er
r
o
r
b
etwe
en
th
e
r
ef
er
en
ce
tr
ajec
to
r
ies an
d
t
h
e
p
r
ed
ictiv
e
m
o
d
el.
T
h
is
cr
iter
io
n
ca
n
b
e
f
o
r
m
u
lated
as
(
5
)
:
{
(
,
)
=
min
1
2
+
{
=
≤
}
(
5
)
w
h
er
e
th
e
o
p
tim
izatio
n
v
ec
to
r
is
d
ef
in
ed
as:
=
[
+
−
1
+
−
1
+
−
1
]
T
h
e
ex
p
r
ess
io
n
f
o
r
th
e
m
atr
ix
H
an
d
th
e
v
ec
to
r
f
is
g
iv
en
b
y
th
e
f
o
llo
win
g
r
elatio
n
[
1
1
]
:
{
=
=
[
4
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
1
0
0
0
2
0
0
0
3
]
w
h
er
e
is
a
m
atr
ix
with
d
iag
o
n
al
elem
en
t,
an
d
d
ef
in
es
th
e
b
in
ar
y
c
o
n
tr
o
lled
an
d
au
x
iliar
y
n
u
m
b
e
r
o
f
v
ar
ia
b
les,
r
esp
ec
tiv
ely
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
3
,
J
u
n
e
20
2
6
:
1
1
4
8
-
1
1
5
8
1152
=
[
−
.
.
.
.
0
−
4
−
M
M
O
O
−
4
−
2
.
.
.
.
.
−
4
−
]
=
[
1
2
3
]
H
er
e
,
=
1
,
2
,
3
.
=
[
(
4
(
)
+
5
)
(
4
(
)
+
5
)
⋯
(
4
−
1
(
)
+
5
)
]
=
[
0
⋯
0
⋱
⋮
⋮
−
1
⋱
⋮
⋮
−
2
]
=
[
⋯
0
⋯
0
⋮
⋮
−
2
⋱
⋯
⋮
⋮
]
,
∈
{
1
,
2
,
3
}
=
[
1
2
3
1
2
3
×
]
H
er
e
,
=
∗
(
+
+
)
=
[
(
(
)
−
)
(
2
(
)
−
)
⋯
(
(
)
−
)
(
(
)
−
)
(
(
)
−
)
⋯
(
−
1
(
)
−
)
−
,
−
⋯
−
⏟
,
−
,
−
⋯
−
⏟
,
−
,
−
⋯
−
⏟
]
T
h
e
v
alu
e
o
f
=
∗
(
+
)
d
eter
m
in
es
th
e
n
u
m
b
er
o
f
lo
g
ical
v
ar
iab
les
with
in
th
e
o
p
tim
izatio
n
p
r
o
b
lem
,
wh
er
e
th
e
v
ar
ia
b
les
an
d
d
en
o
te
th
e
n
u
m
b
er
o
f
b
in
ar
y
co
n
tr
o
l
an
d
au
x
iliar
y
v
ar
iab
les,
r
esp
ec
tiv
ely
.
C
o
n
v
e
r
s
ely
,
th
e
v
ar
iab
le
=
+
d
escr
ib
es
th
e
co
n
ti
n
u
o
u
s
a
n
d
b
in
ar
y
n
u
m
b
er
co
n
tr
o
l
v
ar
iab
les.
W
h
er
e
is
th
e
c
o
n
s
tr
ain
t
m
atr
ix
,
is
th
e
co
n
s
tr
ain
t
co
n
s
tan
t
v
ec
to
r
,
is
th
e
lin
ea
r
co
s
t,
an
d
d
ef
in
es th
e
Hess
ian
m
atr
ix
o
f
th
e
q
u
a
d
r
atic
cr
iter
io
n
p
r
o
b
lem
.
T
h
is
co
n
tr
o
l
v
ec
to
r
c
o
m
p
r
is
e
s
b
o
th
lo
g
ical
a
n
d
c
o
n
tin
u
o
u
s
co
m
p
o
n
e
n
ts
.
T
h
e
MI
QP
al
g
o
r
ith
m
is
em
p
lo
y
ed
to
s
o
lv
e
t
h
e
m
u
lti
-
m
o
d
el
h
y
b
r
id
p
r
e
d
ictiv
e
co
n
t
r
o
l
p
r
o
b
lem
.
At
ea
c
h
s
am
p
li
n
g
tim
e,
th
e
MI
QP
p
r
o
b
lem
h
as b
ee
n
ca
lc
u
lated
with
th
e
aim
o
f
d
eter
m
in
in
g
th
e
o
p
tim
al
co
n
tr
o
l seq
u
en
ce
:
+
−
1
=
{
(
)
,
…
(
+
−
1
)
}
I
n
ac
co
r
d
an
ce
with
th
e
r
ec
ed
i
n
g
tim
e
h
o
r
izo
n
co
n
ce
p
t,
o
n
l
y
th
e
f
i
r
s
t
co
n
tr
o
l
in
p
u
t
is
ap
p
lied
to
th
e
s
y
s
tem
,
wh
ile
th
e
r
em
ain
in
g
in
p
u
ts
ar
e
d
is
ca
r
d
ed
.
T
h
e
n
ew
co
n
tr
o
l a
t
(
k
+1
)
is
th
en
r
ep
ea
ted
at
t
h
e
n
ex
t tim
e
s
tep
.
6.
M
I
Q
P
-
B
A
SE
D
O
P
T
I
M
I
Z
A
T
I
O
N
CO
N
T
RO
L
A
L
G
O
RI
T
H
M
T
h
e
alg
o
r
ith
m
o
f
m
ix
e
d
in
teg
er
q
u
ad
r
atic
p
r
o
g
r
am
m
in
g
ty
p
ically
r
elies
o
n
en
u
m
er
atio
n
t
ec
h
n
iq
u
es,
in
wh
ich
all
p
o
s
s
ib
le
s
o
lu
tio
n
s
ar
e
s
y
s
tem
atica
l
ly
ex
p
lo
r
ed
an
d
ev
alu
ated
to
id
en
tif
y
th
e
o
n
e
th
at
m
in
im
izes
th
e
o
b
jectiv
e
f
u
n
ctio
n
.
T
h
is
m
eth
o
d
is
co
m
m
o
n
ly
ca
r
r
ied
-
o
u
t
u
s
in
g
a
r
ec
u
r
r
e
n
t
b
r
an
ch
-
an
d
-
b
o
u
n
d
alg
o
r
ith
m
[
2
3
]
–
[
2
5
]
.
T
h
e
co
n
tr
o
l sch
em
e
is
d
ep
icted
in
Fig
u
r
e
2
.
I
n
th
e
C
PLE
X
s
o
lv
er
,
th
e
cty
p
e
ar
g
u
m
en
t
m
u
s
t
b
e
d
ef
in
ed
with
in
th
e
C
PLE
X
MI
QP
f
u
n
ctio
n
t
o
s
p
ec
if
y
th
e
n
atu
r
e
o
f
ea
c
h
v
a
r
iab
le
in
th
e
o
p
tim
izatio
n
v
ec
to
r
.
T
h
e
co
r
r
esp
o
n
d
in
g
e
x
p
r
ess
io
n
is
g
iv
e
n
as:
T
h
e
=
[
[
]
1
,
[
]
1
,
[
]
1
]
v
alu
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is
a
s
tr
in
g
co
m
p
o
s
ed
o
f
ch
ar
ac
ter
s
B
,
I
,
C
,
S,N
,
r
e
p
r
esen
tin
g
lo
g
ical,
in
teg
er
,
co
n
tin
u
o
u
s
,
s
e
m
i
-
co
n
tin
u
o
u
s
,
an
d
s
em
i
-
in
teg
er
v
ar
iab
les,
r
esp
ec
tiv
ely
.
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:
2088
-
8
7
0
8
Hyb
r
id
s
ystem
s
mo
d
ellin
g
a
n
d
co
n
tr
o
l u
s
in
g
m
u
ltip
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mixe
d
lo
g
ica
l
…
(
Ta
h
a
r
B
en
a
is
s
a
)
1153
Fig
u
r
e
2
.
E
x
ec
u
tio
n
o
f
HM
PC
co
n
tr
o
l stra
teg
y
7.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
f
o
cu
s
es
o
n
ev
al
u
atin
g
th
e
co
n
tr
o
l
v
ec
to
r
p
er
f
o
r
m
an
ce
d
u
r
in
g
b
o
th
tr
an
s
ien
t
a
n
d
s
tead
y
-
s
tate
p
h
ases
,
u
n
d
er
v
ar
ia
b
le
s
tep
ch
an
g
es
in
th
e
s
etp
o
in
ts
o
f
th
e
th
r
ee
wate
r
lev
els.
T
h
e
s
im
u
latio
n
r
esu
lts
p
r
esen
ted
in
Fig
u
r
e
3
d
em
o
n
s
tr
ate
th
e
s
y
s
tem
’
s
tr
ajec
to
r
y
tr
ac
k
in
g
ca
p
ab
ilit
ies.
T
h
e
liq
u
id
lev
els
[
h
1
h
2
h
3
]
ar
e
co
n
tr
o
lled
to
f
o
llo
w
a
s
e
q
u
en
ce
o
f
s
etp
o
in
t
tr
a
n
s
itio
n
s
:
in
itially
f
r
o
m
[
0
0
0
]
to
[
8
0
5
0
2
5
]
%,
th
e
n
to
[
8
0
5
0
2
5
]
%
to
[
5
0
7
5
5
0
]
%,
f
o
llo
wed
b
y
[
5
0
7
5
5
0
]
%
to
[
8
0
6
2
.
5
0
6
2
.
5
0
]
%
an
d
f
in
ally
to
[
6
2
.
5
0
7
5
5
0
]
%.
T
h
is
s
eq
u
en
ce
o
f
f
illi
n
g
an
d
e
m
p
ty
in
g
o
p
er
atio
n
s
ef
f
ec
tiv
el
y
en
g
ag
es
th
e
v
ar
io
u
s
o
p
e
r
atin
g
m
o
d
es
o
f
th
e
tan
k
s
y
s
tem
.
T
h
e
p
r
ed
ictiv
e
c
o
n
t
r
o
l
s
tr
ateg
y
d
em
o
n
s
tr
ates
ex
ce
llen
t
p
er
f
o
r
m
a
n
ce
in
m
a
in
tain
in
g
ac
c
u
r
ate
tr
ajec
to
r
y
tr
ac
k
i
n
g
u
n
d
er
all
m
o
d
e
tr
an
s
itio
n
s
.
T
h
e
p
r
ed
ictiv
e
co
n
tr
o
l
s
tr
ateg
y
p
r
o
v
id
es
ac
cu
r
ate
tr
ajec
to
r
y
tr
ac
k
in
g
ac
r
o
s
s
all
o
p
er
atin
g
m
o
d
es.
Du
r
in
g
th
e
s
ec
o
n
d
m
o
d
e
—
co
r
r
esp
o
n
d
in
g
to
th
e
t
r
an
s
itio
n
f
r
o
m
[
8
0
5
0
2
5
]
%
to
[
5
0
7
5
5
0
]
%
—
it
is
o
b
s
er
v
ed
th
at
th
e
f
l
o
w
an
d
v
alv
es
ass
o
ciate
d
with
th
e
f
ir
s
t
tan
k
[
1
1
2
]
,
af
ter
r
ea
ch
in
g
s
tead
y
-
s
tate,
n
o
lo
n
g
er
p
a
r
ticip
ate
in
r
eg
u
latin
g
tan
k
s
T
2
an
d
T
3
.
C
o
n
tr
o
l
ef
f
o
r
ts
ar
e
in
s
tead
s
h
if
ted
to
f
lo
w
Q
2
,
with
f
r
eq
u
en
t
s
witch
in
g
o
f
its
co
r
r
esp
o
n
d
i
n
g
v
alv
e.
C
o
n
v
e
r
s
ely
,
th
e
tr
an
s
itio
n
f
r
o
m
[
8
0
6
2
.
5
0
6
2
.
5
0
]
%
to
[
6
2
.
5
0
7
5
5
0
]
%
p
lace
s
g
r
ea
ter
d
em
an
d
o
n
th
e
s
ec
o
n
d
tan
k
T
2
,
wh
ich
en
ter
s
a
f
illi
n
g
p
h
ase,
wh
ile
th
e
f
ir
s
t ta
n
k
T
1
tr
an
s
itio
n
s
to
a
d
u
m
p
i
n
g
p
h
ase.
T
h
is
d
y
n
a
m
ic
in
ter
ac
tio
n
r
esu
lts
in
o
s
cillatio
n
s
in
tan
k
s
T
2
an
d
T
3
d
u
r
in
g
th
e
s
tead
y
-
s
tate
p
h
ase,
ac
co
m
p
a
n
ied
b
y
a
n
o
ticea
b
le
s
tatic
er
r
o
r
in
th
e
wate
r
lev
el
h
2
.
I
n
th
is
co
n
tr
o
l
ca
s
e,
th
e
in
p
u
t
c
o
n
tr
o
l
i
s
ap
p
lied
u
s
in
g
th
e
co
n
tr
o
l
v
ec
t
o
r
in
clu
d
es
th
e
o
u
tlet
v
alv
e
o
f
tan
k
T
3
m
ain
tain
ed
co
m
p
letel
y
o
p
en
,
wh
er
ea
s
th
e
o
u
tlet v
alv
es o
f
ta
n
k
s
T
1
an
d
T
2
r
em
ain
en
tire
ly
clo
s
ed
in
Fig
u
r
e
4
.
T
h
e
h
y
b
r
id
m
o
d
el
p
r
e
d
ictiv
e
co
n
tr
o
l
(
MPC
)
s
tr
ateg
y
is
im
p
lem
en
ted
b
ased
o
n
m
u
ltip
le
ML
D
m
o
d
els.
T
h
e
s
im
u
latio
n
s
ce
n
ar
io
in
clu
d
es
th
r
ee
d
is
tin
ct
o
p
er
atin
g
m
o
d
es,
d
en
o
ted
M
1
,
M
2
an
d
M
3
,
ea
ch
co
n
s
tr
ain
ed
with
in
a
r
e
g
io
n
d
ef
in
ed
b
y
t
h
e
p
h
y
s
ical
lim
itatio
n
s
o
f
th
e
b
en
ch
m
ar
k
s
y
s
tem
.
Mo
d
e
M
1
o
p
er
ates
with
in
th
e
r
e
g
io
n
[
0
-
0
.
2
5
]
[0
-
0
.
2
5
]
[
0
.
0
-
0
.
1
0
]
m
3
;
m
o
d
e
M
2
co
r
r
esp
o
n
d
s
to
th
e
r
an
g
e
[
0
.
2
5
-
0
.
4
5
]
[
0
.
2
5
-
0
.
4
5
]
[
0
.
0
-
0
.
2
0
]
m
3
;
an
d
m
o
d
e
M
3
is
d
ef
in
ed
o
v
er
th
e
s
p
ac
e
[
0
.
4
5
-
0
.
5
5
]
[
0
.
4
5
-
0
.
5
5
]
[
0
.
2
-
0
.
3
0
]
m
3
.
T
h
e
s
im
u
latio
n
r
esu
lts
d
em
o
n
s
tr
ate
ef
f
ec
tiv
e
tr
ajec
to
r
y
tr
ac
k
in
g
ac
r
o
s
s
all
th
r
ee
o
p
er
atin
g
m
o
d
es,
alo
n
g
with
a
s
ig
n
if
ican
t
r
ed
u
ctio
n
in
t
h
e
co
m
p
u
tatio
n
t
im
e
r
eq
u
i
r
ed
to
r
u
n
th
e
alg
o
r
ith
m
to
r
etr
iev
e
th
e
o
p
tim
al
s
o
l
u
tio
n
to
th
e
M
I
QP
o
p
tim
izatio
n
p
r
o
b
lem
.
C
PLE
X
S
o
lv
e
r
MATLAB S
o
ftwa
r
e
App
ly
C
o
n
t
r
ol
ler
S
e
t
P
oin
t
Re
f
e
r
e
n
c
e
Wr
ite
L
i
n
e
a
r
Qu
a
d
r
a
t
i
c
Op
t
i
m
i
z
e
r
C
o
n
st
r
a
i
n
t
s
OP
C
I
n
t
e
r
f
ac
e
Wr
it
e
T
h
r
e
e
-
t
a
n
k
S
p
h
e
r
ical
S
ys
t
e
m
We
i
g
h
t
i
n
g
Fa
c
t
o
r
s
M
o
d
e
l
#1
M
o
d
e
l
#N
Pr
e
d
i
c
t
i
o
n
Ho
r
i
z
o
n
N
CO
NTR
O
LLER
O
P
C
I
nt
e
r
fa
c
e
fo
r
re
ad
W
at
e
r
l
e
v
e
l
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
3
,
J
u
n
e
20
2
6
:
1
1
4
8
-
1
1
5
8
1154
Fig
u
r
e
3
.
Mo
d
el
p
r
e
d
ictiv
e
co
n
tr
o
l o
f
liq
u
id
lev
els
ℎ
1
,
ℎ
2
an
d
ℎ
3
(
Pre
d
ictio
n
h
o
r
izo
n
=3
,
=6
0
0
0
,
=
=0
.
0
1
,
v
alv
e
3
(
=1
)
is
h
eld
o
p
en
with
Step
SetPo
in
t)
T
h
e
m
u
ltip
le
m
o
d
el
p
r
ed
ictiv
e
co
n
tr
o
l
ap
p
r
o
ac
h
is
tr
an
s
f
o
r
m
ed
in
to
a
lin
ea
r
p
r
o
g
r
am
m
i
n
g
p
r
o
b
lem
with
1
3
2
m
ix
ed
lin
ea
r
co
n
s
tr
ain
ts
o
n
a
p
r
ed
ictio
n
tim
e
h
o
r
izo
n
ch
o
s
en
to
b
e
eq
u
al
to
th
e
v
alu
e
=3
to
4
8
,
co
n
tin
u
o
u
s
an
d
b
in
ar
y
v
ar
iab
les.
T
h
e
in
p
u
t
co
n
tr
o
ller
is
ca
lcu
lated
b
y
th
e
MI
QP
alg
o
r
ith
m
with
C
PLE
X
s
o
lv
er
an
d
tr
an
s
m
itted
u
n
d
er
an
OPC
in
ter
f
ac
e
to
f
o
llo
w
th
e
wate
r
liq
u
id
lev
el
s
p
ec
if
icatio
n
s
ℎ
1
=4
5
cm
,
ℎ
2
=3
5
cm
,
a
n
d
ℎ
3
=1
0
cm
.
T
h
e
MP
C
co
n
tr
o
ller
is
r
ef
o
r
m
u
lated
as
a
lin
ea
r
p
r
o
g
r
am
m
in
g
p
r
o
b
lem
with
m
i
x
ed
-
in
teg
er
co
n
s
tr
ain
ts
o
v
er
a
p
r
ed
ictio
n
tim
e
h
o
r
izo
n
o
f
=3
,
in
v
o
lv
i
n
g
4
8
c
o
n
tin
u
o
u
s
an
d
b
in
ar
y
v
a
r
iab
les
s
u
b
ject
to
1
3
2
lin
ea
r
c
o
n
s
tr
a
in
ts
.
T
h
e
o
p
tim
al
co
n
tr
o
l
in
p
u
ts
ar
e
co
m
p
u
ted
u
s
in
g
th
e
MI
QP
f
o
r
m
u
latio
n
s
o
lv
ed
b
y
th
e
C
PLE
X
s
o
lv
er
,
an
d
im
p
lem
en
ted
i
n
r
ea
l
tim
e
v
ia
an
OPC
in
ter
f
ac
e
to
m
e
et
th
e
wate
r
liq
u
id
lev
el
s
etp
o
in
ts
:
ℎ
1
=4
5
cm
,
ℎ
2
=3
5
cm
an
d
ℎ
3
=1
0
cm
.
On
th
e
o
th
e
r
h
an
d
,
th
e
wate
r
lev
el
in
tan
k
T
1
s
h
o
ws
o
s
cillato
r
y
b
eh
av
io
r
,
attr
ib
u
t
ed
to
th
e
s
witch
in
g
ac
tio
n
s
o
f
v
alv
es
V
1
an
d
V
13
,
wh
ich
ar
e
task
ed
with
m
ain
tain
in
g
th
e
lev
el
ℎ
1
an
d
ℎ
2
an
d
ℎ
3
ar
o
u
n
d
th
eir
r
esp
ec
tiv
e
r
ef
er
en
ce
tr
ajec
to
r
ies.
I
n
th
e
o
p
tim
izatio
n
cr
iter
io
n
,
th
e
weig
h
tin
g
m
at
r
ix
is
ca
r
ef
u
lly
ch
o
s
en
to
p
en
a
lize
d
ev
iatio
n
s
b
etwe
en
m
ea
s
u
r
ed
wate
r
lev
els
an
d
th
eir
s
etp
o
i
n
ts
,
th
er
eb
y
im
p
r
o
v
in
g
tr
ac
k
i
n
g
p
e
r
f
o
r
m
an
ce
.
P
os
it
io
n
V
alv
e
V
1
P
os
it
io
n
V
alv
e
V
1
3
P
os
it
io
n
V
alv
e
V
2
P
os
it
io
n
V
alv
e
V
23
I
n
p
u
t
c
on
t
rol
m
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1
(
k
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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C
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p
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I
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N:
2088
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en
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1155
Fig
u
r
e
4
.
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ltip
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ed
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n
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o
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ar
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a
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licatio
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s
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ical
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k
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y
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at
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o
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u
s
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ess
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d
ef
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ess
o
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th
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o
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ed
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eth
o
d
o
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h
iev
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s
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le
an
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o
p
tim
ize
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er
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o
r
m
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ce
.
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y
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atin
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les
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ial
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atic
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o
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ain
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ir
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itio
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ased
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lex
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r
ac
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r
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wo
r
k
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t
th
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tr
o
l
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o
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s
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ap
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tech
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es,
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v
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ate
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o
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im
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lific
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eth
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r
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e
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io
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ay
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ib
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ted
h
y
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s
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ll a
s
th
e
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r
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tio
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ased
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P
os
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P
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it
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2
P
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n
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13
Pos
itio
n
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e
V
23
I
n
p
u
t
co
n
t
r
o
l
m
a
ss f
lo
w
Q
1
a
n
d
Q
2
(
k
g
/
s)
Wa
t
er
level
s
h
1
,
h
2
a
n
d
h
3
(
m
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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I
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1156
F
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DATA AV
AI
L
AB
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h
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th
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r
esp
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d
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g
au
th
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r
,
K.
H
.
,
u
p
o
n
ju
s
tifie
d
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
S
.
B
r
a
n
i
c
k
y
,
V
.
S
.
B
o
r
k
a
r
,
a
n
d
S
.
K
.
M
i
t
t
e
r
,
“
A
u
n
i
f
i
e
d
f
r
a
m
e
w
o
r
k
f
o
r
h
y
b
r
i
d
c
o
n
t
r
o
l
:
M
o
d
e
l
a
n
d
o
p
t
i
ma
l
c
o
n
t
r
o
l
t
h
e
o
r
y
,
”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
A
u
t
o
m
a
t
i
c
C
o
n
t
ro
l
,
v
o
l
.
4
3
,
n
o
.
1
,
p
p
.
3
1
–
4
5
,
1
9
9
8
,
d
o
i
:
1
0
.
1
1
0
9
/
9
.
6
5
4
8
8
5
.
[
2
]
T.
A
.
H
e
n
z
i
n
g
e
r
,
“
T
h
e
t
h
e
o
r
y
o
f
h
y
b
r
i
d
a
u
t
o
ma
t
a
,
”
i
n
Ve
r
i
f
i
c
a
t
i
o
n
o
f
D
i
g
i
t
a
l
a
n
d
H
y
b
r
i
d
S
y
s
t
e
m
s
,
v
o
l
.
1
7
0
,
M
.
K
.
I
n
a
n
a
n
d
R
.
P
.
K
u
r
sh
a
n
,
E
d
s.
N
A
TO
S
e
r
i
e
s,
2
0
0
0
,
p
p
.
2
6
5
–
2
9
2
.
[
3
]
P
.
E.
C
a
i
n
e
s,
A
n
i
n
t
ro
d
u
c
t
i
o
n
t
o
h
y
b
ri
d
d
y
n
a
m
i
c
a
l
sys
t
e
m
s
,
v
o
l
.
3
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o
.
3
.
S
p
r
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e
r
-
V
e
r
l
a
g
L
o
n
d
o
n
,
2
0
0
2
.
[
4
]
R
.
A
l
u
r
a
n
d
D
.
L.
D
i
l
l
,
“
A
t
h
e
o
r
y
o
f
t
i
m
e
d
a
u
t
o
m
a
t
a
,
”
T
h
e
o
re
t
i
c
a
l
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
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.
1
2
6
,
n
o
.
2
,
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p
.
1
8
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–
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3
5
,
1
9
9
4
,
d
o
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:
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.
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0
1
6
/
0
3
0
4
-
3
9
7
5
(
9
4
)
9
0
0
1
0
-
8.
[
5
]
S
.
A
.
R
e
v
e
l
i
o
t
i
s,
D
i
scr
e
t
e
,
c
o
n
t
i
n
u
o
u
s
a
n
d
h
y
b
r
i
d
p
e
t
ri
n
e
t
s
,
v
o
l
.
2
8
,
n
o
.
3
.
S
p
r
i
n
g
e
r
-
V
e
r
l
a
g
B
e
r
l
i
n
,
2
0
0
8
.
[
6
]
J.
L
y
g
e
r
o
s
,
“
Le
c
t
u
r
e
n
o
t
e
s o
n
h
y
b
r
i
d
sy
st
e
ms,
”
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
C
o
m
p
u
t
e
r
E
n
g
i
n
e
e
r
i
n
g
,
U
n
i
v
e
r
si
t
y
o
f
P
a
t
r
a
s,
G
r
e
e
c
e
,
2
0
0
4
.
[
7
]
H
.
Li
n
a
n
d
P
.
J.
A
n
t
sa
k
l
i
s,
“
H
y
b
r
i
d
d
y
n
a
mi
c
a
l
s
y
st
e
ms
:
A
n
i
n
t
r
o
d
u
c
t
i
o
n
t
o
c
o
n
t
r
o
l
a
n
d
v
e
r
i
f
i
c
a
t
i
o
n
,
”
F
o
u
n
d
a
t
i
o
n
s
a
n
d
T
re
n
d
s
i
n
S
y
s
t
e
m
s
a
n
d
C
o
n
t
r
o
l
,
v
o
l
.
1
,
n
o
.
1
,
p
p
.
1
–
1
7
2
,
2
0
1
4
,
d
o
i
:
1
0
.
1
5
6
1
/
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[
2
4
]
C
.
A
.
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l
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s,
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o
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l
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m
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u
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m
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[
2
5
]
R
.
F
l
e
t
c
h
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r
a
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d
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.
Le
y
f
f
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r
,
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u
m
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c
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l
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x
p
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h
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AM
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o
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AUTH
O
RS
Ta
h
a
r
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n
a
iss
a
wa
s
b
o
rn
in
Dje
lfa
,
Alg
e
ria,
o
n
F
e
b
r
u
a
ry
0
6
,
1
9
7
0
.
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re
c
e
iv
e
d
th
e
E
n
g
i
n
e
e
r
d
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g
re
e
in
e
lec
tro
tec
h
n
ics
i
n
1
9
9
5
(El
e
c
tri
c
a
l
m
a
c
h
in
e
o
p
ti
o
n
),
fr
o
m
ENS
ET
-
Lag
h
o
u
a
t,
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e
ria.
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ro
m
1
9
9
9
t
o
2
0
1
1
h
e
wa
s
a
wo
r
k
in
g
a
s
e
n
g
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n
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e
r
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t
th
e
Alg
e
rian
C
o
m
p
a
n
y
o
f
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e
c
tri
c
it
y
a
n
d
G
a
s
Distrib
u
ti
o
n
S
p
a
Dje
lfa,
Alg
e
ria.
th
e
M
a
g
ist
e
r
d
e
g
re
e
i
n
2
0
1
8
o
n
in
h
ig
h
v
o
lt
a
g
e
e
n
g
in
e
e
rin
g
fr
o
m
t
h
e
Un
i
v
e
rsity
o
f
S
c
ien
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s
a
n
d
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h
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lo
g
y
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n
M
o
h
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m
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d
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o
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ia
f
-
UST
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F
a
c
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l
ty
o
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lec
tri
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l
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rin
g
a
n
d
P
h
.
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d
e
g
re
e
s
in
e
lec
tri
c
p
o
we
r
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n
g
in
e
e
rin
g
fro
m
th
e
Un
i
v
e
rsity
o
f
Lag
h
o
u
a
t
,
Alg
e
ria.
Cu
rre
n
tl
y
w
o
rk
s
a
s
a
n
As
so
c
iate
P
ro
fe
ss
o
r
at
th
e
Un
iv
e
rsity
o
f
Dje
lfa,
Alg
e
ria.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
t
h
e
d
iag
n
o
sis
a
n
d
c
o
n
tro
l
o
f
DC
-
DC
c
o
n
v
e
rter
a
p
p
l
ied
in
e
n
e
rg
y
p
h
o
to
v
o
lt
a
ic
sy
ste
m
s,
a
n
d
c
o
n
tro
l
o
f
n
o
n
li
n
e
a
r
d
y
n
a
m
ic
sy
ste
m
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
b
e
n
_
a
issa
tah
a
r@y
a
h
o
o
.
f
r
.
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h
a
m
e
d
F
o
u
z
i
Be
la
z
r
e
g
is
a
Re
se
a
rc
h
As
so
c
iat
e
in
th
e
De
p
a
rtme
n
t
o
f
Au
to
m
a
ti
c
a
t
t
h
e
Nu
c
lea
r
Re
se
a
rc
h
Ce
n
tre
o
f
Biri
n
e
/Alg
e
ria.
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r
e
c
e
iv
e
d
th
e
E
n
g
in
e
e
r
d
e
g
re
e
in
a
u
to
m
a
ti
c
e
n
g
i
n
e
e
rin
g
fro
m
th
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P
o
ly
tec
h
n
ic
S
c
h
o
o
l
(ENP
)
o
f
A
lg
iers
in
1
9
9
5
.
F
r
o
m
1
9
9
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to
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in
c
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n
u
a
ry
1
9
9
6
,
h
e
h
a
s b
e
e
n
with
th
e
N
u
c
lea
r
Re
se
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rc
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n
tre
o
f
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n
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a
s
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Re
se
a
rc
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th
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M
o
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ll
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g
a
n
d
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imu
latio
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Lab
o
ra
to
r
y
a
t
th
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De
p
a
rtme
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t
o
f
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u
to
m
a
ti
c
.
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tl
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s
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i
p
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se
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rc
h
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n
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lea
r
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a
fe
ty
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p
a
rtme
n
t,
Nu
c
lea
r
Re
se
a
rc
h
Ce
n
tre
o
f
Alg
iers
,
Alg
e
ria.
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re
c
e
iv
e
d
a
M
.
S
c
.
d
e
g
re
e
in
a
d
v
a
n
c
e
d
a
u
to
m
a
ti
c
fro
m
th
e
Un
iv
e
rsity
o
f
Dje
lfa,
Alg
e
ria
in
2
0
1
6
a
n
d
th
e
D
o
c
to
ra
te
in
a
u
to
m
a
ti
c
c
o
n
tro
l
f
ro
m
th
e
Ec
o
le
Na
ti
o
n
a
le
P
o
ly
tec
h
n
i
q
u
e
,
Al
g
e
ria
in
2
0
2
0
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
re
a
l
ti
m
e
c
o
n
tro
l
a
n
d
m
o
n
it
o
rin
g
sy
ste
m
,
a
n
a
ly
sis
a
n
d
c
o
n
tro
l
o
f
n
o
n
li
n
e
a
r
d
y
n
a
m
ic
sy
ste
m
s
,
m
o
d
e
ll
i
n
g
,
c
o
n
tr
o
l
a
n
d
id
e
n
ti
fica
ti
o
n
o
f
h
y
b
rid
d
y
n
a
m
i
c
sy
ste
m
s,
a
n
d
m
o
d
e
ll
in
g
/sim
u
l
a
ti
o
n
o
f
t
h
e
rm
a
l
h
y
d
ra
u
l
ic
sy
ste
m
with
AP
ROS
s
o
ftwa
re
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
f.
b
e
laz
re
g
@c
rn
a
.
d
z
.
K
h
a
led
H
a
lb
a
o
u
i
wa
s
b
o
rn
i
n
Dje
lfa
,
Alg
e
ria,
o
n
F
e
b
ru
a
ry
2
7
,
1
9
7
1
.
He
re
c
e
iv
e
d
th
e
En
g
i
n
e
e
r
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
i
n
e
e
rin
g
in
1
9
9
5
(El
e
c
tri
c
a
l
m
a
c
h
in
e
o
p
t
io
n
),
fr
o
m
ENS
ET
-
Lag
h
o
u
a
t,
Alg
e
ria,
t
h
e
M
a
g
ister
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fr
o
m
Dr.
Ya
h
ia
F
a
re
s
Un
iv
e
rsity
o
f
M
é
d
é
a
,
Al
g
e
ria
i
n
2
0
0
6
a
n
d
t
h
e
D
o
c
to
ra
t
in
Au
t
o
m
a
ti
c
Co
n
tro
l
fr
o
m
t
h
e
Eco
le
Na
ti
o
n
a
le
P
o
ly
tec
h
n
i
q
u
e
,
Al
g
e
ria i
n
2
0
1
2
.
F
r
o
m
1
9
9
5
t
o
2
0
0
0
h
e
w
a
s
a
wo
rk
i
n
g
a
s
En
g
in
e
e
r
a
t
th
e
De
p
a
rtme
n
t
o
f
In
str
u
m
e
n
tatio
n
a
n
d
Co
n
tro
l
o
f
t
h
e
De
v
e
l
o
p
m
e
n
t
o
f
E
n
e
rg
y
S
y
ste
m
s
Ce
n
tr
e
CDSE
Dje
lfa,
Alg
e
ria.
D
u
rin
g
2
0
0
1
–
2
0
0
7
,
h
e
h
a
s
b
e
e
n
a
R
e
se
a
rc
h
As
si
sta
n
t
a
t
P
o
we
r
El
e
c
tro
n
ics
La
b
o
ra
t
o
ry
o
f
a
N
u
c
lea
r
Re
se
a
rc
h
Ce
n
tre
o
f
Brin
e
C
RNB,
Ain
Ou
ss
e
ra
,
Al
g
e
ria.
He
wa
s
p
ro
m
o
ted
to
C
h
a
rg
e
o
f
Re
se
a
rc
h
in
2
0
0
7
,
Re
se
a
rc
h
F
e
ll
o
w
in
2
0
1
2
,
a
n
d
S
e
n
io
r
Re
se
a
rc
h
in
2
0
1
9
.
F
r
o
m
2
0
0
6
to
2
0
1
3
h
e
wa
s
an
As
so
c
iate
d
P
ro
fe
ss
o
r
in
th
e
Un
i
v
e
rsity
o
f
Dje
lfa,
Alg
e
ria.
He
p
ro
v
i
d
e
d
m
a
n
y
lec
tu
re
s
in
t
h
e
field
o
f
p
o
we
r
e
lec
tro
n
ics
a
n
d
n
u
c
lea
r
in
stru
m
e
n
tati
o
n
i
n
n
a
ti
o
n
a
l
a
n
d
re
g
io
n
a
l
trai
n
in
g
c
o
u
rse
o
rg
a
n
iz
e
d
b
y
I
n
tern
a
ti
o
n
a
l
Ato
m
ic
En
e
rg
y
Ag
e
n
c
y
(IAEA)
a
n
d
th
e
Ato
m
ic
En
e
rg
y
,
Co
m
m
issio
n
o
f
Alg
e
ria.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
h
y
b
ri
d
sy
ste
m
s,
m
o
to
r
d
riv
e
s,
c
o
m
p
u
ter
-
b
a
se
d
c
o
n
tr
o
l
sy
ste
m
s,
c
o
n
tro
l
th
e
o
r
y
a
p
p
li
c
a
ti
o
n
s a
n
d
p
o
we
r
e
lec
tro
n
ic
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
k
h
.
h
a
l
b
a
o
u
i@c
r
n
b
.
d
z
.
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