I
nte
rna
t
io
na
l J
o
urna
l o
f
P
o
wer
E
lect
ro
nics
a
nd
Driv
e
S
y
s
t
em
s
(
I
J
P
E
DS)
Vo
l.
1
6
,
No
.
1
,
Ma
r
ch
2
0
2
5
,
p
p
.
2
1
2
~
2
2
4
I
SS
N:
2
0
8
8
-
8
6
9
4
,
DOI
: 1
0
.
1
1
5
9
1
/ijp
ed
s
.
v
1
6
.i
1
.
p
p
2
1
2
-
22
4
212
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
p
e
d
s
.
ia
esco
r
e.
co
m
Co
mpa
ring
multi
-
co
ntrol a
lg
o
rith
ms
f
o
r comp
le
x
n
o
nlinea
r
sy
stem:
An
embe
dded prog
ra
mm
a
ble log
ic control
a
pplica
tions
So
chim
a
Vincent
E
g
o
ig
we
1
,
Aso
g
wa
T
o
chuk
wu C
hijin
du
2
,
L
o
is
O
ny
ej
er
e
Nwo
bo
do
3
,
O
nu
ig
bo
Chik
a
M
a
rt
ha
4
,
F
r
a
nk
E
k
ene
O
zio
k
o
2
,
O
z
o
r
G
o
dwin
O
do
zo
3
,
E
bere
Uzo
k
a
Chid
i
5
1
D
e
p
a
r
t
me
n
t
o
f
M
e
c
h
a
t
r
o
n
i
c
s E
n
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
o
f
En
g
i
n
e
e
r
i
n
g
,
U
n
i
v
e
r
s
i
t
y
o
f
N
i
g
e
r
i
a
N
su
k
k
a
,
E
n
u
g
u
,
N
i
g
e
r
i
a
2
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
F
a
c
u
l
t
y
o
f
A
p
p
l
i
e
d
a
n
d
P
h
y
si
c
a
l
S
c
i
e
n
c
e
,
E
n
u
g
u
S
t
a
t
e
U
n
i
v
e
r
si
t
y
o
f
S
c
i
e
n
c
e
a
n
d
Te
c
h
n
o
l
o
g
y
,
En
u
g
u
,
N
i
g
e
r
i
a
3
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
En
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
o
f
En
g
i
n
e
e
r
i
n
g
,
En
u
g
u
S
t
a
t
e
U
n
i
v
e
r
si
t
y
o
f
S
c
i
e
n
c
e
a
n
d
Te
c
h
n
o
l
o
g
y
,
E
n
u
g
u
,
N
i
g
e
r
i
a
4
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
El
e
c
t
r
o
n
i
c
s
En
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
o
f
E
n
g
i
n
e
e
r
i
n
g
,
En
u
g
u
S
t
a
t
e
U
n
i
v
e
r
s
i
t
y
o
f
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
En
u
g
u
,
N
i
g
e
r
i
a
5
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
El
e
c
t
r
o
n
i
c
s
En
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
o
f
E
n
g
i
n
e
e
r
i
n
g
,
U
n
i
v
e
r
si
t
y
o
f
N
i
g
e
r
i
a
N
s
u
k
k
a
,
E
n
u
g
u
,
N
i
g
e
r
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ap
r
3
,
2
0
2
4
R
ev
is
ed
Au
g
1
4
,
2
0
2
4
Acc
ep
ted
Au
g
2
9
,
2
0
2
4
Th
is
p
a
p
e
r
e
x
a
m
in
e
s
th
e
imp
a
c
t
o
f
m
u
lt
ip
le
c
o
n
tro
l
a
lg
o
ri
th
m
s
,
su
c
h
a
s
g
e
n
e
ti
c
a
lg
o
ri
th
m
(G
A),
a
rti
ficia
l
n
e
u
ra
l
n
e
two
r
k
(AN
N),
a
n
d
p
r
o
p
o
rti
o
n
a
l
in
teg
ra
l
d
e
ri
v
a
ti
v
e
(P
ID),
o
n
p
ro
g
ra
m
m
a
b
le
lo
g
ic
c
o
n
tr
o
ll
e
r
(P
LC)
p
e
rfo
rm
a
n
c
e
d
u
rin
g
a
n
o
n
li
n
e
a
r
th
e
rm
o
d
y
n
a
m
ic
p
r
o
c
e
ss
.
Th
e
AN
N
wa
s
train
e
d
wi
th
d
a
ta
t
h
a
t
m
o
d
e
le
d
t
h
e
t
h
e
rm
o
d
y
n
a
m
ic
p
r
o
c
e
ss
a
n
d
t
h
e
n
g
e
n
e
ra
ted
th
e
c
o
n
tr
o
l
a
lg
o
rit
h
m
.
G
A
w
a
s
imp
ro
v
e
d
b
y
a
p
p
l
y
in
g
t
h
e
c
o
u
n
ter
-
p
re
m
a
tu
re
a
lg
o
rit
h
m
(CP
A)
to
a
d
d
re
ss
issu
e
s
o
f
p
re
-
m
a
tu
re
c
o
n
v
e
rg
e
n
c
e
,
wh
il
e
th
e
P
ID p
re
se
n
ts
th
e
c
u
rre
n
t
a
lg
o
ri
th
m
u
se
d
to
o
p
ti
m
ize
th
e
P
LC
in
t
h
e
e
x
isti
n
g
tes
tb
e
d
.
E
x
p
e
rime
n
tal
e
v
a
lu
a
ti
o
n
o
f
t
h
e
se
m
o
d
e
ls
a
g
a
in
st
th
e
p
ro
c
e
ss
se
t
-
p
o
i
n
ts
sh
o
we
d
t
h
a
t
a
ll
t
h
e
a
lg
o
rit
h
m
s
we
re
a
b
le
to
re
jec
t
d
istu
r
b
a
n
c
e
a
n
d
f
o
ll
o
w
th
e
re
fe
re
n
c
e
se
t
p
o
i
n
ts
u
n
d
e
r
d
iffere
n
t
ste
p
c
h
a
n
g
e
s,
b
u
t
e
a
c
h
a
l
g
o
rit
h
m
e
x
p
e
rien
c
e
d
d
iffere
n
t
in
ter
n
a
l
b
e
h
a
v
i
o
rs
w
h
il
e
try
i
n
g
t
o
re
jec
t
d
istu
rb
a
n
c
e
.
Las
tl
y
,
t
h
e
re
su
lt
sh
o
we
d
t
h
a
t
wh
il
e
t
h
e
imp
ro
v
e
d
G
A wa
s
b
e
tt
e
r
th
a
n
t
h
e
P
ID,
wit
h
a
re
c
o
rd
e
d
slig
h
t
o
v
e
rsh
o
o
t
d
u
e
to
t
h
e
u
n
c
e
rtain
ti
e
s
o
f
t
h
e
t
h
e
r
m
o
d
y
n
a
m
i
c
p
r
o
c
e
s
s
,
t
h
e
A
NN
a
c
h
i
e
v
e
d
b
e
t
t
e
r
c
o
n
t
r
o
l
p
e
r
f
o
r
m
a
n
c
e
i
n
t
e
r
m
s
o
f
s
y
s
te
m
s
ta
b
i
l
i
t
y
t
h
a
n
t
h
e
o
t
h
e
r
c
o
u
n
t
e
r
p
a
r
t
a
l
g
o
r
i
t
h
m
s
.
K
ey
w
o
r
d
s
:
ANN
C
o
n
tr
o
l sy
s
tem
GA
PID
T
h
er
m
o
d
y
n
am
ic
s
et
-
p
o
in
ts
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r
th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Aso
g
wa
T
o
ch
u
k
w
u
C
h
ijin
d
u
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
Scie
n
ce
,
Facu
lty
o
f
Ap
p
lied
a
n
d
P
h
y
s
ical
Scien
ce
E
n
u
g
u
Stat
e
Un
iv
er
s
ity
o
f
Sci
en
ce
an
d
T
ec
h
n
o
l
o
g
y
Ag
b
an
i,
E
n
u
g
u
State,
Nig
er
ia
E
m
ail:
to
ch
u
k
wu
.
aso
g
wa@es
u
t.e
d
u
.
n
g
1.
I
NT
RO
D
UCT
I
O
N
All o
v
er
th
e
wo
r
ld
,
p
r
o
g
r
am
m
ab
le
lo
g
ic
co
n
tr
o
ller
s
(
PLC
s
)
h
av
e
d
o
m
in
ated
p
r
o
ce
s
s
d
esig
n
an
d
b
asic
p
r
o
ce
s
s
co
n
tr
o
l
s
y
s
tem
s
[
1
]
.
T
h
e
id
ea
is
to
m
in
im
ize
t
h
e
r
is
k
o
f
ac
cid
en
ts
d
u
r
in
g
t
h
e
te
ch
n
ical
p
r
o
ce
s
s
,
as
r
esear
ch
[
2
]
r
ev
ea
led
th
at
th
e
r
e
is
n
o
p
lan
t
all
o
v
er
th
e
wo
r
l
d
th
at
is
1
0
0
%
r
is
k
-
f
r
ee
.
T
h
e
p
r
o
ce
s
s
d
esig
n
h
as
t
o
d
o
with
th
e
co
r
r
ec
t
s
p
ec
if
icatio
n
o
f
e
n
g
in
ee
r
in
g
c
o
m
p
o
n
en
t
s
s
u
ch
as
v
alv
es,
p
r
ess
u
r
e
tr
a
n
s
m
itter
s
,
ac
tu
ato
r
s
,
s
en
s
o
r
s
,
alar
m
s
,
etc.
in
lin
e
with
th
e
s
tan
d
ar
d
s
o
f
i
n
d
u
s
tr
ial
au
to
m
atio
n
[
3
]
,
wh
ile
th
e
p
r
o
ce
s
s
co
n
tr
o
l
s
y
s
tem
is
th
e
ap
p
licatio
n
o
f
PLCs
o
r
o
t
h
er
co
n
tr
o
l
s
y
s
tem
s
f
o
r
th
e
m
o
n
ito
r
in
g
a
n
d
ad
ju
s
tm
en
t
o
f
p
r
o
ce
s
s
in
p
u
ts
to
g
iv
e
th
e
d
esire
d
o
u
tp
u
t [
4
]
an
d
[
5
]
.
R
ec
en
tly
,
PLCs
h
av
e
g
ain
ed
m
o
r
e
atten
tio
n
d
u
e
t
o
r
ec
e
n
t a
d
v
an
ce
m
e
n
ts
in
th
eir
f
ea
tu
r
es,
s
u
ch
as
wir
ele
s
s
co
n
tr
o
l
ac
ce
s
s
,
lar
g
er
m
e
m
o
r
y
,
b
etter
p
r
o
ce
s
s
in
g
s
p
ee
d
,
an
d
p
r
o
g
r
am
m
in
g
f
lex
ib
ilit
y
[
6
]
.
I
n
ad
d
itio
n
,
it
h
as
b
ee
n
ap
p
lied
f
o
r
r
ea
l
-
tim
e
co
n
tr
o
l
o
p
er
atio
n
s
,
wh
ich
ac
co
r
d
in
g
to
Ulag
wu
-
E
ch
ef
u
et
a
l.
[
7
]
,
ar
e
in
g
r
ea
t d
em
an
d
in
to
d
ay
’
s
in
d
u
s
tr
ial
s
ettin
g
s
.
Ho
wev
er
,
wh
ile
th
e
P
L
C
h
as
co
n
tin
u
ed
to
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
C
o
mp
a
r
in
g
mu
lti
-
co
n
tr
o
l a
lg
o
r
ith
ms fo
r
co
mp
lex
n
o
n
lin
ea
r
s
ystem
…
(
S
o
ch
ima
V
in
ce
n
t E
g
o
ig
w
e
)
213
of
f
er
p
r
o
m
is
in
g
s
o
l
u
tio
n
s
to
o
p
tim
ize
in
d
u
s
tr
ial
au
to
m
atio
n
,
th
er
e
is
s
till
a
n
ee
d
f
o
r
it
to
o
f
f
er
o
p
tim
al
c
o
n
tr
o
l,
esp
ec
ially
in
co
m
p
lex
n
o
n
lin
ea
r
s
itu
atio
n
s
[
8
]
.
Pro
ce
s
s
co
n
tr
o
l
h
as
b
ec
o
m
e
h
eter
o
g
en
e
o
u
s
in
n
atu
r
e
,
with
m
u
ltip
le
p
ar
am
eter
s
,
tim
e
-
in
v
ar
ian
t
c
o
n
s
tr
ain
ts
,
s
et
-
p
o
i
n
ts
,
m
u
lti
-
lo
g
ic
s
eq
u
en
ce
s
,
an
d
all
r
eq
u
ir
in
g
ap
p
r
o
x
im
atio
n
in
a
s
h
o
r
t tim
e
[
9
]
,
th
u
s
p
r
esen
tin
g
co
m
p
lex
c
o
n
tr
o
l iss
u
es f
o
r
th
e
co
n
v
en
tio
n
al
PLC an
d
h
en
ce
p
r
esen
tin
g
th
e
n
ee
d
f
o
r
a
d
v
an
c
ed
co
n
tr
o
l sy
s
tem
(
AC
S).
Air
ik
k
a
[
1
0
]
d
ef
in
es
AC
S
as
th
e
a
p
p
licatio
n
o
f
class
ical
co
n
tr
o
l
tec
h
n
iq
u
es
with
th
e
ab
ilit
y
to
p
er
f
o
r
m
co
m
p
lex
c
o
m
p
u
tati
o
n
s
f
r
o
m
p
r
o
ce
s
s
m
o
d
elin
g
,
p
ar
am
eter
esti
m
atio
n
,
p
er
f
o
r
m
an
ce
cr
iter
i
o
n
o
p
tim
izatio
n
,
m
u
ltiv
ar
iab
le
,
an
d
b
ac
k
-
p
r
o
p
ag
atio
n
-
b
ased
co
n
tr
o
l
ch
ar
ac
ter
is
tics
in
to
th
e
b
a
s
ic
p
r
o
ce
s
s
co
n
tr
o
l
s
y
s
tem
to
en
h
a
n
ce
p
er
f
o
r
m
a
n
ce
.
I
n
th
e
co
n
te
x
t
o
f
PLC,
th
ese
AC
S
ca
n
b
e
ap
p
lied
to
o
p
tim
ize
t
h
e
p
er
f
o
r
m
an
ce
t
h
r
o
u
g
h
au
to
m
a
tic
p
ar
am
eter
tu
n
in
g
[
1
1
]
,
wh
ich
ca
n
b
e
d
o
n
e
u
s
in
g
e
x
ter
n
al
co
m
p
u
tin
g
m
ac
h
in
es
(
E
C
M)
o
r
th
e
ap
p
licatio
n
o
f
ad
v
an
ce
d
p
r
o
ce
s
s
co
n
tr
o
l
alg
o
r
ith
m
s
(
APC
A)
[
1
2
]
.
W
h
ile
th
ese
two
m
eth
o
d
s
ca
n
im
p
r
o
v
e
PLC,
T
ar
n
awsk
i
et
a
l
.
[
1
2
]
i
d
en
tif
ied
APC
A
as
o
f
f
er
in
g
b
etter
r
esu
lts
f
o
r
s
af
ety
in
teg
r
ity
,
q
u
ality
ass
u
r
an
ce
,
an
d
ec
o
n
o
m
y
wh
e
n
co
m
p
ar
ed
t
o
E
C
M.
Ma
n
y
wo
r
k
s
o
f
liter
atu
r
e
o
n
APC
A
h
av
e
b
ee
n
p
r
esen
ted
,
r
ec
o
m
m
en
d
i
n
g
v
a
r
io
u
s
APC
A
tech
n
iq
u
es
to
im
p
r
o
v
e
co
n
s
tr
ain
t
a
p
p
r
o
x
i
m
atio
n
f
o
r
n
o
n
lin
e
ar
s
y
s
tem
s
.
Fo
r
in
s
tan
ce
,
a
s
tu
d
y
[
1
3
]
a
p
p
lied
th
e
Z
ieg
ler
Nich
o
las
tu
n
in
g
tec
h
n
iq
u
e
o
r
co
n
s
tr
ain
t
ap
p
r
o
x
im
atio
n
o
f
a
n
o
n
lin
ea
r
s
y
s
tem
,
wh
ile
a
s
tu
d
y
[1
4
]
co
m
p
ar
ed
th
e
Z
ieg
ler
Nich
o
las,
in
ter
n
al
m
o
d
el
c
o
n
tr
o
l
(
I
MC),
a
n
d
S
h
am
s
-
I
MC
tech
n
iq
u
es,
r
esp
ec
tiv
ely
,
an
d
r
ep
o
r
ted
Sh
am
s
-
I
MC a
s
m
o
r
e
co
n
s
is
ten
t th
an
th
e
o
th
er
s
.
Ho
wev
er
,
a
s
tu
d
y
[
1
5
]
r
ev
ea
led
th
e
PID
ca
n
n
o
t b
e
r
eliab
le
f
o
r
th
e
co
n
tr
o
l
o
f
m
u
ltip
le
v
a
r
iab
l
es,
wh
ich
ar
e
tim
e
-
in
v
ar
ian
t
,
an
d
s
u
g
g
ested
an
a
d
ap
tiv
e
s
o
l
u
tio
n
in
a
b
o
u
n
d
ed
least
s
q
u
ar
e
o
p
tim
izer
s
o
lv
er
[
1
6
]
to
a
d
d
r
ess
in
teg
r
atio
n
is
s
u
es
s
u
ch
as
co
m
p
atib
ilit
y
an
d
f
u
n
ctio
n
o
v
er
h
ea
d
.
Stu
d
y
[
1
7
]
a
p
p
lied
f
u
zz
y
lo
g
ic
f
o
r
im
p
r
o
v
ed
s
er
v
o
m
o
to
r
co
n
tr
o
l,
wh
i
le
[
1
8
]
im
p
r
o
v
e
d
f
u
zz
y
lo
g
ic
with
T
ak
ag
i
-
Su
g
e
o
n
o
an
d
ap
p
lied
it
to
o
p
tim
ize
th
e
S7
-
3
0
0
/4
0
0
PLC
s
y
s
tem
.
I
n
th
e
s
am
e
v
e
in
,
th
e
s
tu
d
y
[
1
9
]
ap
p
lied
n
o
r
m
aliza
tio
n
ac
ce
le
r
atio
n
-
b
ased
f
u
zz
y
i
n
f
er
en
ce
e
n
g
in
e
ad
j
u
s
tm
en
t
to
c
o
n
tr
o
l
t
h
e
s
ca
lin
g
in
p
u
t
an
d
o
u
tp
u
t
co
ef
f
icien
ts
o
f
t
h
e
PL
C
,
wh
ile
th
e
s
tu
d
y
[
2
0
]
i
m
p
r
o
v
ed
th
e
f
u
zz
y
co
n
tr
o
l
s
y
s
tem
u
s
in
g
a
p
a
r
ticle
s
war
m
alg
o
r
ith
m
an
d
ac
h
iev
e
d
a
b
etter
co
n
tr
o
l so
lu
tio
n
wh
e
n
co
m
p
a
r
ed
with
th
e
r
esu
lts
o
b
tain
ed
in
[
1
9
]
.
T
h
e
d
ata
-
d
r
iv
e
n
a
p
p
r
o
a
ch
(
DD
A)
[
2
1
]
was
a
ls
o
u
s
e
d
f
o
r
t
h
e
o
p
ti
m
iz
ati
o
n
o
f
PLC
p
e
r
f
o
r
m
a
n
c
e.
DD
A
ca
n
b
e
class
i
f
i
e
d
in
to
tw
o
a
p
p
r
o
ac
h
es
,
wh
ic
h
a
r
e
s
ta
tis
ti
ca
l
a
n
d
a
r
ti
f
i
cial
i
n
t
ell
ig
e
n
ce
(
AI
)
.
T
h
e
s
t
atis
tic
al
ap
p
r
o
ac
h
u
s
e
d
a
m
at
h
em
atic
all
y
i
n
s
p
i
r
e
d
h
e
u
r
is
ti
c
m
o
d
el
t
o
s
o
l
v
e
th
e
o
p
ti
m
i
z
ati
o
n
p
r
o
b
l
em
s
o
f
t
h
e
p
la
n
t
,
w
h
il
e
th
e
AI
e
m
p
lo
y
ed
s
m
a
r
t
o
p
ti
m
i
za
ti
o
n
a
p
p
r
o
ac
h
es
a
n
d
m
a
c
h
i
n
e
le
ar
n
i
n
g
(
ML
)
al
g
o
r
i
th
m
s
t
o
lea
r
n
t
h
e
b
e
h
av
io
r
o
f
t
h
e
p
l
an
t
a
n
d
p
e
r
f
o
r
m
c
o
n
tr
o
l
o
p
e
r
at
io
n
s
.
L
ite
r
at
u
r
e
h
as
f
o
c
u
s
e
d
r
e
ce
n
tl
y
o
n
A
I
.
a
p
p
r
o
a
ch
f
o
r
o
p
t
im
i
za
ti
o
n
o
f
PL
C
s
,
u
s
i
n
g
m
o
s
t
ly
M
L
a
lg
o
r
it
h
m
s
.
F
o
r
e
x
am
p
l
e,
B
ay
esi
a
n
o
p
ti
m
iz
ati
o
n
w
as
u
s
e
d
b
y
M
o
h
a
m
e
d
e
t
a
l
.
[
2
2
]
to
t
u
n
e
t
h
e
p
a
r
am
ete
r
s
o
f
t
h
e
ca
s
c
ad
e
co
n
t
r
o
ll
er
a
n
d
ac
h
ie
v
e
r
o
b
u
s
t
n
ess
t
o
d
is
tu
r
b
a
n
c
e
a
n
d
o
p
t
im
al
t
r
ac
k
i
n
g
p
e
r
f
o
r
m
a
n
c
e,
w
h
il
e
B
h
ar
g
a
v
[
2
3
]
a
p
p
li
e
d
a
b
ac
k
-
pr
o
p
a
g
at
io
n
-
b
ase
d
n
eu
r
al
n
etw
o
r
k
f
o
r
e
r
r
o
r
d
et
ec
t
io
n
,
f
au
lt
to
l
er
a
n
ce
,
a
n
d
o
p
t
im
iza
ti
o
n
o
f
PLC
.
W
h
ile
t
h
ese
s
t
u
d
ies
r
e
c
o
r
d
ed
s
i
g
n
i
f
i
ca
n
t
c
o
n
t
r
o
l
s
u
cc
ess
,
t
h
e
y
w
er
e
n
o
t
test
e
d
c
o
n
s
i
d
e
r
i
n
g
v
e
r
y
co
m
p
l
ex
n
o
n
l
in
ea
r
c
h
e
m
ic
al
p
r
o
c
ess
es
wi
th
m
u
lti
p
l
e
co
n
t
r
o
l
c
o
n
s
tr
a
in
ts
,
w
h
i
ch
l
ea
v
es
a
g
ap
.
I
n
[
2
4
]
,
a
p
r
e
d
ic
ti
v
e
co
n
t
r
o
l
al
g
o
r
it
h
m
d
ev
el
o
p
e
d
wit
h
a
m
o
d
el
p
r
e
d
ic
ti
v
e
c
o
n
t
r
o
lle
r
(
MPC
)
w
as
u
s
e
d
t
o
o
p
ti
m
iz
e
th
e
f
u
n
ct
io
n
o
f
SC
L
5
0
0
-
P
L
C
.
T
h
e
MPC
w
as
im
p
r
o
v
e
d
wit
h
Nes
te
r
o
v
’
s
f
o
r
est
g
r
a
d
ie
n
t
[
2
5
]
a
n
d
th
en
em
b
e
d
d
e
d
i
n
t
o
t
h
e
PLC
u
s
i
n
g
s
t
r
u
ct
u
r
e
d
t
est
p
r
o
g
r
a
m
m
in
g
an
d
t
este
d
ex
p
er
i
m
e
n
t
all
y
o
n
m
u
lti
p
l
e
c
o
n
n
ec
t
e
d
tan
k
s
y
s
t
em
s
.
T
h
e
MPC
was
c
o
m
p
ar
ed
wit
h
t
h
e
P
I
D,
a
n
d
t
h
e
r
es
u
l
ts
s
h
o
w
e
d
t
h
at
t
h
e
MPC
h
as
b
ette
r
co
n
s
t
r
ai
n
t
ap
p
r
o
x
i
m
a
ti
o
n
f
ea
t
u
r
es
.
I
n
t
h
e
s
t
u
d
y
[
2
6
]
,
a
g
r
a
d
ie
n
t
al
g
o
r
it
h
m
was
a
p
p
lie
d
t
o
o
p
tim
ize
MPC
a
n
d
th
en
in
t
eg
r
ate
d
i
n
t
o
F
est
o
-
p
r
o
g
r
am
m
a
b
le
l
o
g
i
c
c
o
n
tr
o
l
le
r
s
(
P
L
C
)
.
A
n
e
x
p
e
r
i
m
e
n
t
al
r
esu
lt
wa
s
p
e
r
f
o
r
m
ed
o
n
a
n
o
n
li
n
ea
r
p
r
o
c
ess
.
T
h
e
r
es
u
l
ts
we
r
e
c
o
m
p
a
r
e
d
a
g
ai
n
s
t
s
t
an
d
ar
d
PLC,
an
d
it
was
o
b
s
e
r
v
e
d
t
h
at
t
h
e
i
m
p
r
o
v
e
d
MPC
-
b
ase
d
PLC
wa
s
b
et
te
r
.
D
esp
i
te
t
h
e
s
u
cc
ess
,
it
is
s
til
l
n
o
t
cl
ea
r
w
h
et
h
e
r
th
e
s
y
s
t
em
is
e
f
f
e
cti
v
e
w
h
e
n
test
e
d
in
a
c
o
m
p
l
e
x
n
o
n
li
n
e
ar
s
y
s
te
m
wit
h
m
u
l
ti
p
le
c
o
n
s
t
r
ai
n
ts
.
I
n
a
n
o
th
e
r
a
p
p
r
o
a
c
h
,
Z
h
a
o
e
t
a
l
.
[
2
7
]
a
d
o
p
t
t
h
e
Ko
o
p
m
a
n
s
u
b
s
p
ac
e
m
o
d
e
l
a
n
d
a
m
u
lti
-
p
a
r
a
m
et
er
q
u
a
d
r
ati
c
p
r
o
g
r
am
m
i
n
g
a
p
p
r
o
a
ch
to
s
o
l
v
e
t
h
e
c
o
n
s
t
r
a
in
ts
o
p
t
i
m
iz
ati
o
n
p
r
o
b
le
m
i
n
a
c
h
il
le
d
wate
r
p
l
an
t
c
o
n
tr
o
l
.
I
n
ad
d
i
ti
o
n
,
p
ie
ce
wis
e
-
a
f
f
in
e
c
o
n
t
r
o
l
laws
a
n
d
ac
ti
v
e
c
o
n
s
t
r
ai
n
ts
s
e
ts
we
r
e
d
et
er
m
i
n
e
d
u
s
i
n
g
d
at
a
-
d
r
i
v
e
n
p
a
r
ti
ti
o
n
o
f
d
is
t
u
r
b
a
n
c
e
s
p
ac
e
t
o
r
ed
u
c
e
p
o
w
er
co
n
s
u
m
p
t
i
o
n
i
n
t
h
e
ch
ille
r
p
la
n
t
,
w
h
il
e
a
ch
ie
v
i
n
g
o
p
ti
m
a
l
o
p
e
r
at
io
n
ir
r
es
p
e
cti
v
e
o
f
c
o
n
s
tr
a
in
ts
v
i
o
la
ti
o
n
s
,
w
h
i
le
A
r
t
u
r
o
et
a
l
.
[
2
8
]
ap
p
l
ie
d
a
r
t
if
i
cial
n
e
u
r
al
n
e
two
r
k
(
ANN
)
t
o
i
m
p
r
o
v
e
th
e
p
e
r
f
o
r
m
a
n
c
e
o
f
A
lle
n
-
B
r
ad
le
y
PLC
o
p
e
r
at
io
n
s
d
u
r
in
g
w
ate
r
l
e
v
el
c
o
n
t
r
o
l
.
T
h
e
s
tu
d
y
tr
a
in
e
d
a
f
e
e
d
-
f
o
r
wa
r
d
n
e
u
r
al
n
et
wo
r
k
al
g
o
r
it
h
m
wi
th
d
a
ta
f
r
o
m
t
h
e
p
la
n
t
t
o
g
e
n
e
r
at
e
a
c
o
n
t
r
o
l
m
o
d
el
,
wh
ic
h
was
in
te
g
r
ate
d
i
n
t
o
th
e
PLC
u
s
in
g
R
S
L
o
g
ix
5
0
0
0
.
T
h
e
p
e
r
f
o
r
m
a
n
c
e
s
h
o
we
d
t
h
e
ANN
w
as
ab
l
e
to
i
m
p
r
o
v
e
t
h
e
co
n
s
t
r
a
in
t
ap
p
r
o
x
im
ati
o
n
ef
f
i
c
ien
c
y
o
f
P
L
C
wh
en
co
m
p
a
r
e
d
wit
h
t
r
a
d
it
io
n
al
PLC.
ML
-
i
n
s
p
i
r
e
d
d
is
c
r
et
e
-
tim
e
co
n
t
r
o
ll
er
w
as
p
r
o
p
o
s
e
d
i
n
[
2
9
]
,
u
s
i
n
g
P
I
D
a
n
d
n
e
u
r
al
n
etw
o
r
k
s
t
o
d
e
v
e
lo
p
a
n
a
d
v
a
n
c
ed
co
n
t
r
o
l
al
g
o
r
it
h
m
f
o
r
th
e
ap
p
r
o
x
im
ati
o
n
s
o
f
s
i
n
g
le
i
n
p
u
t a
n
d
o
u
tp
u
t
d
is
cr
ete
-
t
im
e
n
o
n
li
n
ea
r
s
y
s
te
m
s
.
I
n
th
e
s
t
u
d
y
,
t
h
e
n
eu
r
a
l n
etw
o
r
k
was
t
r
ai
n
e
d
wit
h
th
e
d
ata
f
r
o
m
t
h
e
p
la
n
t
.
T
h
e
e
r
r
o
r
b
et
wee
n
th
e
in
p
u
t
a
n
d
o
u
t
p
u
t
was
m
i
n
i
m
iz
e
d
u
s
i
n
g
ad
ap
tat
io
n
r
u
l
es
o
f
th
e
P
I
D
,
wi
th
t
h
r
ee
n
e
u
r
o
n
s
u
s
ed
as
t
h
e
P
-
I
-
D
i
n
p
u
ts
.
T
h
e
m
o
d
el
g
en
er
ated
a
f
ter
e
v
alu
atio
n
an
d
ju
s
tify
in
g
th
e
s
u
cc
ess
was
r
ec
o
m
m
en
d
ed
f
o
r
n
o
n
lin
ea
r
co
n
tr
o
l
s
y
s
tem
s
.
I
n
th
e
s
am
e
v
ein
,
L
ee
an
d
J
an
g
[
3
0
]
tr
ain
ed
1
0
0
0
d
ata
p
o
in
ts
f
o
r
th
e
m
ass
s
p
r
in
g
d
am
p
er
s
y
s
tem
(
MSDS)
u
s
in
g
a
n
eu
r
al
n
etwo
r
k
an
d
l
o
n
g
s
h
o
r
t
-
ter
m
m
em
o
r
y
(
L
STM
)
.
T
h
e
m
o
d
el
s
wer
e
r
esp
ec
tiv
ely
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
6
,
No
.
1
,
Ma
r
c
h
20
2
5
:
212
-
224
214
ap
p
lied
f
o
r
th
e
s
elf
-
tu
n
in
g
o
f
PID
an
d
c
o
n
tr
o
l
o
f
MSDS.
T
h
e
r
esu
lt
s
h
o
we
d
th
at
b
o
th
m
o
d
els
ac
h
iev
ed
g
o
o
d
p
er
f
o
r
m
an
ce
,
b
u
t
th
e
L
STM
was
r
ec
o
m
m
en
d
e
d
d
u
e
to
its
p
r
ed
ictiv
e
ch
a
r
ac
ter
is
tics
.
I
n
[
3
1
]
,
DDA
was
u
s
ed
f
o
r
co
n
tr
o
l
p
er
f
o
r
m
an
ce
ass
es
s
m
en
t
o
f
PID
p
e
r
f
o
r
m
an
ce
.
C
o
m
p
ar
ativ
e
ML
alg
o
r
it
h
m
s
s
u
ch
as
d
ec
is
io
n
tr
ee
,
ex
tr
a
tr
ee
s
,
Ad
ab
o
ast,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM)
,
am
o
n
g
o
th
e
r
s
,
wer
e
tr
ain
ed
with
d
ata
co
llected
f
r
o
m
s
ig
n
al
-
b
ased
clo
s
ed
-
lo
o
p
ed
p
r
o
ce
s
s
s
y
s
tem
s
.
T
h
e
r
esu
lt
s
h
o
wed
th
at
th
e
SVM
ac
h
iev
ed
b
etter
p
er
f
o
r
m
an
ce
ef
f
icien
cy
af
ter
c
o
m
p
ar
ati
v
e
an
aly
s
is
with
o
th
er
m
o
d
els.
[
3
2
]
u
s
ed
b
lack
b
o
x
m
u
lti
o
b
j
ec
tiv
e
o
p
tim
izatio
n
(
B
B
MA
)
an
d
r
ein
f
o
r
ce
m
en
t le
ar
n
in
g
(
R
L
)
to
tu
n
e
PID
.
T
h
e
R
L
was u
s
ed
to
m
in
im
ize
m
u
lti
-
s
tep
co
n
v
er
g
en
ce
an
d
f
ac
ilit
ate
th
e
tu
n
in
g
o
f
th
e
PID
,
wh
ile
th
e
B
B
MA
d
ev
e
lo
p
ed
with
p
ar
ticle
s
war
m
(P
S
)
[
3
3
]
a
n
d
g
en
etic
alg
o
r
ith
m
(
GA)
[
3
4
]
was
u
s
ed
to
tu
n
e
th
e
PID
,
r
esp
ec
tiv
ely
,
an
d
co
m
p
ar
ativ
ely
a
n
aly
ze
d
t
h
r
o
u
g
h
s
im
u
latio
n
ex
p
er
im
en
ts
.
T
h
e
r
esu
lt sh
o
we
d
th
at
th
e
R
L
ac
h
i
ev
e
d
f
aster
s
elf
-
tu
n
e
wh
e
n
co
m
p
ar
ed
to
th
e
r
est.
Ov
er
all,
th
e
liter
atu
r
e
h
as
s
h
o
wn
th
at
s
ev
er
al
ap
p
r
o
ac
h
es
h
av
e
b
ee
n
ap
p
lied
o
v
er
th
e
y
e
ar
s
f
o
r
th
e
o
p
tim
izatio
n
o
f
PLC
an
d
h
a
v
e
all
h
ad
s
ig
n
if
ican
t
s
u
cc
e
s
s
in
th
e
ap
p
r
o
x
im
atio
n
o
f
n
o
n
lin
ea
r
s
y
s
tem
s
;
h
o
wev
er
,
it
is
s
till
n
o
t
clea
r
w
h
ich
alg
o
r
ith
m
ac
h
ie
v
ed
th
e
b
est
p
er
f
o
r
m
an
ce
.
Seco
n
d
ly
,
m
ajo
r
ity
o
f
th
e
r
esu
lts
wer
e
n
o
t
test
ed
co
n
s
id
er
in
g
co
m
p
lex
n
o
n
lin
e
ar
p
r
o
ce
s
s
w
ith
m
u
ltip
le
co
n
s
tr
ain
ts
r
eq
u
i
r
in
g
a
p
p
r
o
x
im
atio
n
with
in
a
s
h
o
r
t
tim
e,
wh
ile
s
o
m
e
o
f
th
e
r
esu
lts
,
d
esp
ite
th
eir
s
u
cc
ess
,
r
eq
u
ir
e
v
alid
atio
n
th
r
o
u
g
h
th
e
r
ea
l
-
wo
r
l
d
test
b
ed
m
eth
o
d
.
B
ased
o
n
th
e
s
e
g
ap
s
,
th
e
f
o
llo
win
g
co
n
t
r
ib
u
tio
n
will
b
e
m
ad
e
in
th
is
p
a
p
er
.
B
ased
o
n
th
ese
g
ap
s
,
th
e
f
o
llo
win
g
c
o
n
tr
ib
u
tio
n
will
b
e
m
ad
e
in
th
is
p
ap
er
:
i)
A
m
ath
em
atica
l
f
o
r
m
u
latio
n
o
f
th
e
n
o
n
lin
ea
r
p
r
o
b
lem
in
a
th
er
m
o
d
y
n
am
ic
p
r
o
ce
s
s
will
b
e
p
r
esen
ted
;
ii)
T
h
r
ee
n
o
tab
le
c
o
n
tr
o
l
alg
o
r
ith
m
s
(
ANN,
PID
an
d
GA)
will
b
e
d
ev
elo
p
e
d
u
s
in
g
an
d
in
te
g
r
ated
to
o
p
tim
ize
p
lc
r
esp
ec
tiv
ely
.
T
h
e
ef
f
ec
tiv
e
n
ess
o
f
ea
c
h
alg
o
r
ith
m
will
b
e
ac
ce
s
s
ed
e
x
p
er
im
en
tal
ly
u
n
d
e
r
th
e
co
n
s
id
er
ed
n
o
n
lin
ea
r
p
r
o
b
lem
;
iii)
An
im
p
r
o
v
ed
g
a
will
b
e
ap
p
lied
to
ad
d
r
ess
is
s
u
es
o
f
p
r
e
-
m
atu
r
e
co
n
v
er
g
e
n
ce
wh
ich
h
as
c
o
n
tin
u
o
u
s
ly
h
in
d
e
r
ed
s
u
cc
ess
p
er
f
o
r
m
an
ce
o
f
g
a
u
s
in
g
co
u
n
ter
p
r
em
atu
r
e
alg
o
r
ith
m
(
C
PA)
;
an
d
iv
)
R
ec
o
m
m
en
d
atio
n
will
b
e
m
ad
e
o
f
en
g
in
ee
r
s
o
n
th
e
ch
o
ice
o
f
th
e
b
est co
n
tr
o
l a
lg
o
r
ith
m
f
o
r
ap
p
r
o
x
im
atio
n
o
f
co
m
p
le
x
n
o
n
lin
ea
r
c
o
n
s
tr
ain
ts
in
tech
n
i
ca
l p
r
o
ce
s
s
.
2.
M
E
T
H
O
D
T
h
e
m
eth
o
d
o
lo
g
y
u
s
ed
f
o
r
th
e
s
tu
d
y
b
eg
an
with
th
e
m
ath
em
atica
l
m
o
d
elin
g
o
f
a
n
o
n
lin
ea
r
th
er
m
o
d
y
n
am
ic
p
r
o
ce
s
s
o
f
two
co
n
n
ec
ted
r
ea
ct
o
r
tan
k
s
d
u
r
in
g
a
n
ir
r
ev
er
s
ib
le
ex
o
th
er
m
ic
r
ea
ctio
n
.
T
o
im
p
r
o
v
e
th
e
PLC
ap
p
lied
f
o
r
th
e
s
y
s
tem
ap
p
r
o
x
im
atio
n
,
th
r
ee
co
n
tr
o
l
alg
o
r
ith
m
s
wh
ic
h
a
r
e
PID
,
ANN
a
n
d
GA
wer
e
d
ev
elo
p
ed
a
n
d
ea
ch
in
teg
r
ated
s
ep
ar
ately
o
n
th
e
PLC.
T
h
e
GA
was
al
s
o
im
p
r
o
v
ed
with
C
PA
to
ad
d
r
ess
is
s
u
es
o
f
p
r
e
-
m
atu
r
e
co
v
ar
ia
n
ce
an
d
im
p
r
o
v
e
th
e
ap
p
r
o
x
im
atio
n
p
r
o
ce
s
s
.
T
h
e
th
r
ee
m
o
d
els
wer
e
in
teg
r
ated
in
to
PLC
an
d
th
en
ex
p
er
im
en
tally
v
alid
ated
u
n
d
er
n
o
n
lin
ea
r
co
n
d
itio
n
s
.
R
es
u
lts
o
b
tain
ed
f
r
o
m
ea
ch
test
ar
e
co
m
p
ar
ativ
e
an
aly
ze
d
to
id
en
tify
th
e
m
o
s
t
s
u
itab
le
co
n
tr
o
l
s
o
lu
tio
n
to
o
p
tim
ize
PLC
an
d
m
ain
tain
s
tab
ilit
y
o
f
th
e
th
e
r
m
o
d
y
n
a
m
ic
p
r
o
ce
s
s
in
r
ea
l tim
e.
2
.
1
.
T
he
no
nli
nea
r
t
herm
o
dy
na
m
ic
pro
ce
s
s
A
co
m
p
lex
ch
em
ical
p
r
o
ce
s
s
was
d
escr
ib
ed
b
y
Li
[
3
5
]
as
a
d
y
n
am
ic
b
eh
a
v
io
r
o
f
two
co
n
n
ec
ted
r
ea
cto
r
tan
k
d
u
r
in
g
an
ir
r
ev
er
s
ib
le
ex
o
th
er
m
ic
r
ea
ctio
n
,
wh
ic
h
is
co
n
tr
o
lled
with
wate
r
co
o
lan
t.
T
h
e
f
lo
w
r
ate
f
o
r
b
o
th
r
ea
ct
o
r
s
ar
e
g
i
v
en
as
1
an
d
2
wh
ile
tem
p
er
atu
r
es
o
f
th
e
two
r
ea
cto
r
s
ar
e
1
an
d
2
.
T
h
e
ch
em
ical
p
r
o
ce
s
s
is
m
o
d
eled
with
th
e
a
s
s
u
m
p
tio
n
ac
co
r
d
i
n
g
to
Li
[
3
5
]
th
at
1
=
2
=
,
1
=
2
=
,
=
2
=
an
d
1
=
+
as
th
e
d
if
f
er
en
tial
e
q
u
atio
n
wh
ich
p
r
esen
ts
th
e
r
ate
o
f
co
n
ce
n
tr
atio
n
in
(
1
)
an
d
(
2
)
r
esp
ec
tiv
ely
f
o
r
t
h
e
t
wo
r
ea
ct
o
r
s
an
d
tem
p
e
r
atu
r
es
ch
an
g
es
in
(
3
)
a
n
d
(
4
)
an
d
t
h
e
v
o
l
u
m
e
tr
ic
f
lo
w
r
ate
o
f
th
e
ch
em
ical
p
r
o
ce
s
s
p
r
esen
ted
i
n
th
e
(
5
)
a
n
d
(
6
)
r
esp
ec
tiv
el
y
.
1
=
0
0
−
+
1
+
2
−
1
−
/
1
(
1
)
2
=
+
1
−
+
2
–
2
−
/
2
(
2
)
1
=
−
+
1
+
2
−
1
−
/
1
−
(
1
−
1
)
(
3
)
2
=
1
−
+
1
+
2
−
2
−
/
2
−
(
2
−
2
)
(
4
)
10
=
1
(
1
−
1
)
−
(
1
−
1
)
(
5
)
20
=
2
(
2
−
2
)
−
(
2
−
2
)
(
6
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
C
o
mp
a
r
in
g
mu
lti
-
co
n
tr
o
l a
lg
o
r
ith
ms fo
r
co
mp
lex
n
o
n
lin
ea
r
s
ystem
…
(
S
o
ch
ima
V
in
ce
n
t E
g
o
ig
w
e
)
215
F
r
o
m
t
h
e
m
o
d
e
l
o
f
t
h
e
t
h
e
r
m
o
d
y
n
a
m
i
c
b
e
h
a
v
i
o
r
c
o
n
s
i
d
e
r
i
n
g
t
h
e
t
h
r
e
e
k
e
y
a
t
t
r
i
b
u
t
es
w
h
i
c
h
a
r
e
t
e
m
p
e
r
a
t
u
r
e
,
c
o
n
c
e
n
t
r
a
ti
o
n
,
a
n
d
v
o
l
u
m
e
o
f
m
i
x
t
u
r
e
i
n
t
h
e
r
e
a
c
t
o
r
s
,
t
h
e
i
d
ea
s
a
r
e
t
o
c
o
n
t
r
o
l
,
1
2
t
h
r
o
u
g
h
t
h
e
v
a
r
i
a
t
i
o
n
o
f
,
10
a
n
d
20
.
T
h
e
v
a
r
i
a
t
i
o
n
b
e
tw
e
e
n
t
h
e
in
p
u
t
t
e
m
p
e
r
a
t
u
r
e
an
d
t
h
e
c
o
n
t
r
o
l
l
e
d
t
e
m
p
e
r
a
t
u
r
e
v
a
l
u
es
i
s
t
h
e
e
r
r
o
r
a
s
−
.
L
e
t
t
h
e
v
a
r
ia
t
i
o
n
b
e
tw
e
e
n
th
e
i
n
p
u
t
a
n
d
c
o
n
t
r
o
l
co
n
ce
n
tr
atio
n
s
b
e
g
iv
en
a
s
11
2
−
2
,
12
2
,
ℎ
ℎ
21
=
2
−
2
,
22
=
2
−
2
,
31
=
1
−
1
,
32
=
1
−
1
.
T
h
e
c
h
a
n
g
e
i
n
t
h
e
t
w
o
r
e
a
c
t
o
r
s
i
n
(
1
)
-
(
6
)
c
a
n
b
e
p
r
e
s
e
n
t
e
d
a
s
i
n
(
7
)
.
11
=
11
12
,
12
=
12
1
,
1
=
11
21
=
21
22
,
21
+
31
.
22
=
22
2
+
22
(
7
)
2
=
21
W
h
er
e
21
=
31
32
,
31
+
,
32
.
32
=
32
3
+
32
;
2
=
;
11
=
1
,
12
=
1
;
21
=
,
22
=
2
;
31
=
,
32
=
;
=
,
∅
=
+
,
=
−
an
d
1
=
+
2
0
−
4
;
2
=
20
−
20
;
3
=
10
−
10
;
1
=
+
(
12
+
+
(
11
+
2
)
+
(
11
+
2
)
−
(
(
21
+
2
)
)
⁄
∅
21
=
+
1
+
+
(
21
+
2
)
−
;
(
(
11
+
2
)
−
(
(
21
+
2
)
)
⁄
−
(
21
+
2
−
2
)
∅
22
=
2
(
20
−
22
−
2
)
+
(
21
+
2
−
22
−
2
)
∅
31
=
−
+
(
31
+
1
)
−
1
−
(
(
21
+
1
)
)
⁄
−
(
21
+
2
)
-
(
31
+
1
−
1
)
∅
32
=
1
(
10
−
32
−
1
)
+
(
31
+
1
−
32
−
1
)
1
=
+
1
+
2
−
1
−
(
1
)
)
⁄
;
2
=
+
1
+
2
−
2
−
(
2
)
)
⁄
;
3
=
+
1
+
2
−
1
−
(
1
)
)
⁄
−
(
2
−
2
)
;
4
=
+
1
−
+
+
–
(
1
)
)
⁄
∗
2
−
2
2
2
−
(
2
)
)
⁄
3
T
h
e
(
1
)
to
(
7
)
wer
e
p
r
esen
te
d
with
th
e
o
b
jectiv
e
o
f
co
v
er
in
g
th
e
s
y
s
tem
o
u
tp
u
t
to
ze
r
o
.
T
h
is
was
ac
h
iev
ed
u
s
in
g
th
e
u
n
ce
r
tain
p
ar
am
eter
s
in
(
4
)
an
d
(
5
)
to
d
ev
elo
p
co
n
t
r
o
l
alg
o
r
ith
m
s
th
at
w
ill
b
e
p
r
o
g
r
am
m
e
d
in
th
e
PLC
to
co
n
tr
o
l
th
e
co
m
p
lex
r
ea
cto
r
s
.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
is
to
u
s
e
th
e
f
lo
w
r
ate
(
)
o
f
co
o
lan
t
as
in
p
u
t
to
s
tab
ilit
y
o
f
th
e
r
ea
cto
r
as
th
e
co
n
tr
o
lled
co
n
ce
n
tr
atio
n
in
(
8
)
;
co
n
tr
o
lled
tem
p
e
r
at
u
r
e
in
(
9
)
an
d
th
e
co
n
tr
o
l
tem
p
er
at
u
r
e
ch
an
g
e
o
f
th
e
co
o
lan
t
as
a
r
esu
lt
o
f
th
er
m
o
d
y
n
am
ics
with
in
th
e
r
e
ac
to
r
an
d
th
en
th
e
d
if
f
er
en
ce
b
etwe
en
th
e
c
o
o
lan
t a
n
d
its
in
itial tem
p
er
atu
r
e
p
r
esen
ted
in
th
e
(
10
)
.
(
)
/
=
/
∗
(
0
−
)
−
∗
−
(
8
)
(
)
/
=
/
∗
(
0
−
)
−
/
(
_
)
∗
−
−
/
(
)
∗
(
−
)
(
9
)
(
)
/
=
/
∗
(
0
−
)
+
/
(
∗
∗
)
∗
(
−
)
(
1
0
)
2
.
2
.
B
a
s
ics o
f
t
he
P
L
C
T
h
e
PLC
o
p
e
r
ated
b
ased
o
n
th
e
cy
clic
s
ca
n
n
in
g
m
eth
o
d
in
wh
ich
its
o
p
e
r
atin
g
s
y
s
tem
m
o
n
ito
r
s
th
e
tim
er
an
d
th
e
co
llected
d
ata
f
r
o
m
th
e
in
p
u
t
m
o
d
u
le
to
ch
e
ck
th
e
s
tatu
s
o
f
all
in
p
u
t
d
ev
i
ce
s
.
T
h
e
p
r
o
ce
s
s
o
r
u
s
ed
th
e
ap
p
licatio
n
s
o
f
twar
e
b
ased
o
n
t
h
e
wo
r
k
f
lo
w
o
f
t
h
e
AC
S
alg
o
r
ith
m
p
r
o
g
r
am
m
ed
u
s
in
g
th
e
la
d
d
er
lo
g
ic
m
eth
o
d
,
to
in
s
tr
u
ct
an
d
a
d
ju
s
t
th
e
PLC
co
n
tr
o
l p
ar
am
et
er
s
to
m
atch
th
e
d
esire
d
o
u
tp
u
t,
b
ased
o
n
in
ter
n
al
co
m
p
u
tatio
n
s
an
d
th
en
wr
ite
th
e
d
ata
in
to
th
e
o
u
t
p
u
t
m
o
d
u
le
,
an
d
th
e
s
ca
n
cy
cle
co
n
tin
u
es.
T
h
e
p
o
wer
s
u
p
p
l
y
en
s
u
r
es
th
e
r
e
g
u
lated
p
o
wer
lo
w
in
to
th
e
en
tire
s
y
s
tem
,
v
ia
t
h
e
co
n
v
er
s
io
n
o
f
t
h
e
in
c
o
m
in
g
alter
n
atin
g
c
u
r
r
e
n
t
in
to
d
ir
ec
t
c
u
r
r
e
n
t.
T
h
e
in
p
u
t
m
o
d
u
le
c
o
n
n
ec
ts
th
e
s
en
s
o
r
s
an
d
tr
a
n
s
m
itter
s
to
th
e
ce
n
tr
al
p
r
o
ce
s
s
in
g
w
h
ich
u
s
e
th
e
o
p
tim
izatio
n
al
g
o
r
ith
m
p
r
o
g
r
am
m
e
d
u
s
in
g
lad
d
er
l
o
g
ic,
s
tr
u
ctu
r
e
d
tex
t
,
o
r
f
u
n
cti
o
n
b
lo
c
k
m
eth
o
d
to
ad
j
u
s
t
th
e
PLC
co
n
tr
o
l
p
ar
am
eter
s
to
m
atch
th
e
d
esire
d
o
u
t
p
u
t
an
d
th
en
u
s
ed
to
co
n
tr
o
l
o
th
er
o
u
tp
u
t
d
ev
ices.
T
h
e
e
th
er
n
et
is
th
e
co
m
m
u
n
i
ca
tio
n
s
ec
tio
n
o
f
th
e
PLC
w
h
ich
is
u
s
ed
to
in
ter
f
ac
e
o
th
e
r
co
m
p
u
ter
s
f
o
r
th
e
m
o
n
ito
r
in
g
an
d
an
aly
s
is
o
f
th
e
tech
n
ical
p
r
o
ce
s
s
.
T
h
e
PLC p
r
o
g
r
am
m
in
g
s
p
ec
if
icatio
n
s
ar
e
in
T
ab
le
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
6
,
No
.
1
,
Ma
r
c
h
20
2
5
:
212
-
224
216
T
ab
le
1
.
T
h
e
PLC
s
p
ec
if
icatio
n
s
P
a
r
a
me
t
e
r
s
V
a
l
u
e
s
P
a
r
a
me
t
e
r
s
V
a
l
u
e
s
C
u
r
r
e
n
t
4
-
2
0
mA
I
n
p
u
t
p
o
r
t
3
P
r
o
g
r
a
m
mem
o
r
y
w
i
t
h
r
u
n
m
o
d
e
1
2
2
8
9
b
y
t
e
s
O
u
t
p
u
t
p
o
r
t
3
P
r
o
g
r
a
m
mem
o
r
y
w
i
t
h
o
u
t
r
u
n
m
o
d
e
1
6
3
8
4
b
y
t
e
s
C
o
mm
u
n
i
c
a
t
i
o
n
i
n
t
e
r
f
a
c
e
R
S
4
8
5
D
a
t
a
mem
o
r
y
1
0
2
4
1
b
y
t
e
s
P
o
w
e
r
s
u
p
p
l
y
2
2
0
-
24
V
/
D
C
B
a
c
k
u
p
mem
o
r
y
1
0
0
h
r
s
A
n
a
l
o
g
u
e
a
d
j
u
s
t
me
n
t
2
S
p
e
e
d
o
f
c
o
m
p
u
t
a
t
i
o
n
2
a
t
2
0
0
M
H
z
F
l
o
a
t
i
n
g
p
o
i
n
t
Y
e
s
2
.
3
.
Adv
a
nce
co
ntr
o
l a
lg
o
rit
h
m
I
n
t
h
is
s
e
cti
o
n
,
AI
-
in
s
p
i
r
e
d
co
n
t
r
o
l
al
g
o
r
it
h
m
s
a
r
e
p
r
o
p
o
s
ed
a
n
d
p
r
ese
n
t
e
d
t
o
o
p
tim
i
ze
c
o
n
tr
o
l
p
e
r
f
o
r
m
a
n
c
e
o
f
P
L
C
.
P
o
p
u
l
a
r
alg
o
r
it
h
m
s
s
u
c
h
as
p
r
o
p
o
r
ti
o
n
al
in
te
g
r
al
d
e
r
i
v
at
e,
g
e
n
e
tic
a
l
g
o
r
i
th
m
,
an
d
n
e
u
r
al
n
et
wo
r
k
al
g
o
r
it
h
m
s
ar
e
p
r
o
p
o
s
ed
r
es
p
e
cti
v
e
ly
t
o
f
ac
ilit
at
e
tu
n
in
g
o
f
t
h
e
P
L
C
co
n
t
r
o
l
s
y
s
te
m
.
T
h
is
p
e
r
f
o
r
m
a
n
c
e
will
b
e
c
o
m
p
a
r
a
ti
v
el
y
a
n
a
ly
ze
d
th
e
b
est s
ele
ct
ed
f
o
r
s
y
s
te
m
i
n
te
g
r
a
te
d
to
o
p
tim
iz
e
t
ec
h
n
ic
al
p
r
o
c
ess
es
.
2
.
3
.
1
.
G
enet
ic
a
lg
o
rit
hm
Gen
etic
alg
o
r
ith
m
(
GA)
is
a
r
a
n
d
o
m
s
ea
r
ch
u
s
ed
in
s
o
lv
in
g
c
o
m
p
lex
o
p
tim
izatio
n
p
r
o
b
l
e
m
s
[
3
6
]
lik
e
n
o
n
lin
ea
r
p
a
r
am
eter
ap
p
r
o
x
i
m
atio
n
in
ch
em
ical
p
r
o
ce
s
s
es
.
J
ay
ac
h
itra
an
d
Vin
o
d
h
a
[
3
7
]
a
d
d
ed
th
at
th
e
GA
em
p
lo
y
ed
th
e
r
u
les
o
f
p
r
o
b
a
b
i
lity
tr
an
s
itio
n
to
h
an
d
le
g
en
er
alize
d
p
o
p
u
latio
n
o
f
ch
r
o
m
o
s
o
m
es
wh
ich
ev
o
lv
ed
th
r
o
u
g
h
a
s
er
ies
o
f
iter
atio
n
s
g
en
er
atio
n
s
,
p
io
n
ee
r
ed
b
y
f
itn
ess
tes
ts
,
cr
o
s
s
o
v
er
,
an
d
m
u
ta
tio
n
.
GA
tak
es
f
o
u
r
s
im
p
le
s
tep
s
wh
ich
ar
e
th
e
p
o
p
u
latio
n
g
en
er
aliza
tio
n
,
f
itn
ess
s
elec
tio
n
,
cr
o
s
s
o
v
er
,
an
d
m
u
tatio
n
ap
p
r
o
ac
h
r
esp
ec
tiv
ely
to
ar
r
iv
e
at
th
e
o
p
tim
u
m
s
o
lu
tio
n
,
an
d
wh
en
th
e
r
esu
lt
d
o
es
n
o
t
co
n
v
er
g
e,
th
e
o
u
tp
u
t
is
f
ee
d
b
ac
k
f
o
r
a
n
o
th
er
f
itn
ess
test
.
Par
a
m
eter
s
u
s
ed
f
o
r
t
h
e
GA
u
p
d
ates
an
d
co
m
p
u
tatio
n
s
ar
e
i
n
T
ab
le
2
;
wh
ile
t
h
e
p
s
eu
d
o
co
d
e
is
in
A
lg
o
r
ith
m
1
.
T
h
e
GA
in
Alg
o
r
ith
m
1
,
p
r
esen
ts
th
e
tr
ad
itio
n
al
GA
[
3
8
]
f
o
r
th
e
o
p
tim
izatio
n
o
f
PL
C
,
h
o
wev
er
,
th
is
alg
o
r
ith
m
s
u
f
f
e
r
s
am
o
n
g
m
a
n
y
lim
itatio
n
s
th
e
is
s
u
es
o
f
p
r
e
-
m
atu
r
e
co
n
v
er
g
e
n
ce
.
T
h
is
u
s
u
ally
o
cc
u
r
s
wh
en
th
er
e
is
n
o
t
en
o
u
g
h
s
ea
r
ch
s
p
ac
e
f
o
r
th
e
alg
o
r
ith
m
to
e
x
p
l
o
r
e.
I
t
ca
n
also
h
ap
p
e
n
wh
en
th
er
e
is
n
o
t
en
o
u
g
h
d
iv
er
s
e
b
etwe
en
th
e
m
u
tatio
n
an
d
cr
o
s
s
o
v
er
o
p
er
atio
n
o
f
th
e
ch
r
o
m
o
s
o
m
es
o
r
if
th
e
s
ize
o
f
th
e
ch
r
o
m
o
s
o
m
es
is
v
er
y
s
m
all
[
3
9
]
.
T
o
a
d
d
r
ess
th
is
is
s
u
e,
th
e
s
tu
d
y
p
r
o
p
o
s
ed
a
n
o
v
el
c
o
u
n
ter
-
p
r
em
atu
r
e
alg
o
r
ith
m
.
T
ab
le
2
.
Par
am
eter
s
o
f
th
e
GA
P
a
r
a
me
t
e
r
V
a
l
u
e
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
P
o
p
u
l
a
t
i
o
n
s
i
z
e
8
0
0
0
C
r
o
ss
o
v
e
r
o
p
e
r
a
t
o
r
D
u
e
p
o
i
n
t
w
i
t
h
p
r
o
b
a
b
i
l
i
t
y
(
P
=
0
.
8
)
R
e
p
r
e
se
n
t
a
t
i
o
n
M
i
x
e
d
b
i
n
a
r
y
r
e
a
l
M
u
t
a
t
i
o
n
o
p
e
r
a
t
o
r
u
n
i
f
o
r
m
I
n
i
t
i
a
l
i
z
a
t
i
o
n
R
a
n
d
o
m
P
r
o
b
a
b
i
l
i
t
y
0
.
0
1
S
c
a
l
e
f
a
c
t
o
r
(
5
,
2
0
)
P
r
o
p
o
r
t
i
o
n
a
l
c
o
e
f
f
.
0,
10
x
ma
x
(
|
u
min
|
,
|
u
m
a
x
|)
Alg
o
r
ith
m
1
.
GA
p
s
eu
d
o
c
o
d
e
1)
Star
t
2)
I
n
itiate
th
e
r
an
d
o
m
p
o
p
u
latio
n
s
ize
o
f
th
e
v
ar
ia
b
les in
th
e
ex
o
th
er
m
ic
r
ea
ctio
n
=
8
0
0
0
3)
Set a
r
ef
er
en
ce
s
tan
d
ar
d
f
o
r
te
m
p
er
atu
r
e
a
n
d
c
o
n
ce
n
tr
atio
n
4)
Per
f
o
r
m
co
m
p
u
tatio
n
test
with
r
ef
er
en
ce
s
tan
d
ar
d
s
u
s
in
g
t
h
e
f
itn
ess
m
o
d
el
5)
Get
n
ew
o
f
f
s
p
r
in
g
6)
Gen
er
ate
n
ew
p
o
p
u
latio
n
7)
C
r
o
s
s
o
v
er
s
am
p
le
8)
Mu
tatio
n
9)
Do
u
n
til
10)
B
est o
f
f
s
p
r
in
g
is
d
eter
m
in
ed
11)
Gen
er
ate
b
est PLC co
n
tr
o
l f
u
n
ctio
n
s
12)
R
etu
r
n
13)
E
n
d
T
h
is
C
PA
is
tailo
r
ed
to
war
d
s
o
p
tim
izin
g
th
e
tr
ad
itio
n
al
GA
(
in
A
lg
o
r
ith
m
1
)
t
o
ad
d
r
e
s
s
is
s
u
es
o
f
p
r
e
-
m
atu
r
e
c
o
n
v
e
r
g
en
ce
ass
o
ciate
d
with
GA,
wh
ich
m
ig
h
t
i
m
p
ac
t
its
r
eliab
ilit
y
as
a
P
L
C
o
p
tim
izer
.
T
h
e
alg
o
r
ith
m
b
eg
in
s
b
y
o
p
tim
izin
g
th
e
p
o
p
u
latio
n
s
ize
o
f
th
e
ch
r
o
m
o
s
o
m
es
u
s
in
g
a
m
u
ltip
le
p
o
p
u
latio
n
alg
o
r
ith
m
,
as
r
ef
e
r
en
ce
d
i
n
[
4
0
]
.
I
n
itially
,
th
e
p
o
p
u
latio
n
s
ize
is
d
en
o
ted
as
P,
an
d
th
e
d
esire
d
in
cr
ea
s
e
in
p
o
p
u
latio
n
is
r
ep
r
esen
ted
as
Δ
P.
T
h
e
n
ew
p
o
p
u
latio
n
s
ize
is
d
eter
m
in
ed
b
y
a
d
d
in
g
Δ
P
to
th
e
in
itial
p
o
p
u
latio
n
,
r
esu
ltin
g
in
P+Δ
P.
Nex
t,
th
e
tech
n
iq
u
e
ad
ju
s
ts
th
e
cr
o
s
s
o
v
er
a
n
d
m
u
tatio
n
o
p
er
atio
n
s
u
s
in
g
a
p
r
o
b
a
b
ilit
y
f
u
n
ctio
n
th
at
g
e
n
e
r
ates
v
alu
es
b
etwe
en
0
an
d
1
.
T
h
e
o
u
tp
u
t
o
f
th
is
p
r
o
b
a
b
ilit
y
f
u
n
ctio
n
is
u
tili
ze
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
C
o
mp
a
r
in
g
mu
lti
-
co
n
tr
o
l a
lg
o
r
ith
ms fo
r
co
mp
lex
n
o
n
lin
ea
r
s
ystem
…
(
S
o
ch
ima
V
in
ce
n
t E
g
o
ig
w
e
)
217
to
ad
ap
t
th
e
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
r
ates,
e
n
ab
lin
g
th
e
co
n
tr
o
l
o
f
p
o
p
u
latio
n
d
iv
er
s
ity
.
T
o
s
elec
t
th
e
b
est
o
u
tco
m
e,
t
h
e
least
sq
u
ar
e
alg
o
r
ith
m
(
L
SA)
r
ef
e
r
en
ce
d
as [
4
1
]
was a
p
p
lied
.
L
S
A
e
v
a
l
u
a
te
s
t
h
e
p
r
o
b
a
b
i
l
it
y
f
u
n
c
t
i
o
n
'
s
o
u
t
p
u
t
a
n
d
i
d
e
n
t
i
f
i
es
t
h
e
b
e
s
t
o
u
t
c
o
m
e
,
d
e
s
i
g
n
at
e
d
a
s
N
.
T
h
is
b
e
s
t
o
u
t
c
o
m
e
is
r
e
c
o
m
m
e
n
d
ed
a
s
t
h
e
f
o
u
n
d
a
t
i
o
n
f
o
r
t
h
e
n
e
x
t
g
e
n
e
r
a
t
i
o
n
.
T
o
d
e
t
e
r
m
i
n
e
t
h
e
P
a
r
e
t
o
-
o
p
t
i
m
al
s
o
l
u
t
i
o
n
s
,
a
m
u
l
t
i
-
o
b
j
e
c
ti
v
e
e
v
o
l
u
t
i
o
n
a
l
g
o
r
i
t
h
m
r
e
f
e
r
e
n
c
e
d
a
s
[
4
2
]
w
a
s
a
d
o
p
t
e
d
t
o
f
a
c
i
l
it
a
te
t
h
e
d
i
s
c
o
v
e
r
y
o
f
s
o
l
u
t
i
o
n
s
t
h
a
t
s
i
m
u
l
t
a
n
e
o
u
s
l
y
o
p
t
i
m
i
z
e
m
u
l
ti
p
l
e
o
b
j
e
c
ti
v
e
s
w
h
i
l
e
m
a
i
n
t
a
i
n
i
n
g
d
i
v
e
r
s
i
t
y
.
Fu
r
t
h
e
r
m
o
r
e
,
a
l
o
c
a
l
s
e
a
r
c
h
o
p
e
r
a
t
o
r
w
a
s
u
s
e
d
t
o
r
e
f
i
n
e
t
h
e
b
es
t
o
u
t
c
o
m
e
o
b
t
a
i
n
e
d
t
h
u
s
f
a
r
.
T
h
r
o
u
g
h
f
i
n
e
-
tu
n
in
g
t
h
e
a
l
g
o
r
i
t
h
m
'
s
p
a
r
a
m
e
t
e
r
s
,
t
h
is
l
o
c
a
l
s
ea
r
c
h
o
p
e
r
a
t
i
o
n
a
i
m
s
t
o
e
n
h
a
n
c
e
t
h
e
q
u
a
l
i
t
y
o
f
t
h
e
s
o
l
u
t
i
o
n
.
L
a
s
t
l
y
,
t
h
e
r
e
f
i
n
e
d
b
e
s
t
o
u
t
c
o
m
e
s
e
r
v
e
s
a
s
a
b
a
s
i
s
f
o
r
g
e
n
e
r
a
t
i
n
g
n
e
w
o
f
f
s
p
r
i
n
g
i
n
t
h
e
s
u
b
s
e
q
u
e
n
t
g
e
n
e
r
a
t
i
o
n
,
t
h
e
r
e
b
y
c
o
n
t
i
n
u
i
n
g
t
h
e
o
p
t
i
m
i
z
a
ti
o
n
p
r
o
c
e
s
s
.
I
n
s
u
m
m
a
r
y
,
t
h
e
t
e
c
h
n
i
q
u
e
o
p
t
i
m
i
z
es
t
h
e
p
o
p
u
l
a
t
i
o
n
s
i
z
e
,
a
d
j
u
s
ts
c
r
o
s
s
o
v
e
r
a
n
d
m
u
t
a
t
i
o
n
r
a
t
e
s
u
s
i
n
g
a
p
r
o
b
a
b
i
l
i
t
y
f
u
n
c
t
i
o
n
,
s
e
l
e
ct
s
t
h
e
b
es
t
o
u
t
c
o
m
e
u
s
i
n
g
L
S
A
,
a
p
p
l
i
es
m
u
l
t
i
-
o
b
je
c
t
i
v
e
e
v
o
l
u
t
i
o
n
t
o
d
e
t
e
r
m
i
n
e
P
a
r
e
t
o
-
o
p
t
i
m
al
s
o
l
u
ti
o
n
s
,
r
e
f
i
n
es
t
h
e
b
es
t
o
u
t
c
o
m
e
th
r
o
u
g
h
a
l
o
c
a
l
s
e
a
r
c
h
o
p
e
r
at
o
r
,
a
n
d
g
e
n
e
r
a
t
es
n
ew
o
f
f
s
p
r
i
n
g
.
T
h
e
s
e
s
t
e
p
s
c
o
l
l
e
ct
iv
e
l
y
a
i
m
t
o
i
m
p
r
o
v
e
t
h
e
al
g
o
r
i
t
h
m
'
s
p
e
r
f
o
r
m
a
n
c
e
a
n
d
f
a
ci
l
ita
t
e
t
h
e
d
is
c
o
v
e
r
y
o
f
o
p
t
i
m
a
l
s
o
l
u
t
i
o
n
s
f
o
r
t
h
e
t
r
a
d
it
i
o
n
a
l
GA
i
n
A
l
g
o
r
it
h
m
1
.
T
h
e
p
r
o
p
o
s
e
d
C
P
A
w
as
p
r
es
e
n
t
ed
a
s
A
l
g
o
r
i
t
h
m
2
.
A
l
g
o
r
i
t
h
m
1
p
r
e
s
e
n
ts
t
h
e
t
r
a
d
i
t
i
o
n
a
l
GA
,
w
h
i
l
e
A
l
g
o
r
i
t
h
m
2
p
r
e
s
e
n
t
s
t
h
e
p
r
o
p
o
s
e
d
C
P
A
.
C
o
l
l
e
ct
i
v
e
l
y
o
t
h
e
r
a
l
g
o
r
i
t
h
m
s
w
e
r
e
i
n
t
e
g
r
a
t
e
d
as
a
n
i
m
p
r
o
v
e
d
G
A
f
o
r
t
h
e
o
p
t
i
m
i
z
a
t
i
o
n
P
L
C
f
o
r
e
n
h
a
n
c
e
d
c
o
n
t
r
o
l
o
f
n
o
n
l
i
n
e
a
r
i
n
c
o
n
t
i
n
u
o
u
s
s
ti
r
t
a
n
k
r
e
a
c
t
o
r
(
C
S
T
R
)
p
la
n
t
.
T
h
e
p
r
o
p
o
s
e
d
G
A
w
a
s
r
e
p
o
r
t
e
d
as
Al
g
o
r
i
t
h
m
3
.
2
.
3
.
2
.
Neura
l net
wo
rk
a
lg
o
ri
t
hm
T
o
s
o
lv
e
th
e
co
n
tr
o
l
s
y
s
tem
p
r
o
b
lem
o
f
C
STR,
f
ee
d
-
f
o
r
war
d
n
eu
r
al
n
etwo
r
k
(
FF
NN)
[
4
3
]
,
[
4
4
]
was
ap
p
lied
to
o
p
tim
ize
th
e
PLC.
T
h
e
n
eu
r
al
n
etwo
r
k
was
ad
o
p
ted
f
r
o
m
[
4
5
]
an
d
u
s
ed
to
co
n
tr
o
l
th
e
PLC.
T
h
e
n
eu
r
al
n
etwo
r
k
is
a
b
r
a
n
ch
o
f
ML
th
at
is
in
s
p
ir
e
d
b
y
th
e
b
eh
av
io
r
o
f
th
e
h
u
m
a
n
b
r
ain
.
T
h
e
n
eu
r
o
n
s
h
av
e
weig
h
ts
,
b
iases
,
an
d
ac
tiv
atio
n
f
u
n
ctio
n
s
.
T
h
e
n
e
u
r
o
n
s
wer
e
co
n
f
i
g
u
r
ed
co
n
s
id
er
in
g
t
h
e
n
u
m
b
er
o
f
co
n
tr
o
l
p
ar
am
eter
s
t
o
d
eter
m
in
e
t
h
e
i
n
p
u
t
an
d
f
o
r
m
o
f
t
h
e
n
etwo
r
k
.
T
h
e
ac
tiv
atio
n
f
u
n
ctio
n
was
u
s
ed
to
tr
i
g
g
er
th
e
n
eu
r
o
n
s
to
g
iv
e
o
u
tp
u
t
with
in
th
e
d
esire
d
r
an
g
e
b
ased
o
n
th
e
ac
tiv
atio
n
f
u
n
ctio
n
ty
p
e.
I
n
th
is
ca
s
e,
th
e
ty
p
e
co
n
s
id
er
ed
is
th
e
tan
g
en
t
h
y
p
er
b
o
lic
f
u
n
ctio
n
,
w
h
ic
h
p
r
o
d
u
ce
s
o
u
tp
u
t
f
ea
tu
r
es
with
in
th
e
r
an
g
e
o
f
-
1
an
d
1
an
d
is
co
n
n
ec
ted
at
th
e
h
id
d
en
lay
er
s
o
f
th
e
n
eu
r
o
n
s
,
an
d
th
en
th
e
p
u
r
elin
ac
tiv
atio
n
f
u
n
ctio
n
,
wh
ich
is
co
n
n
ec
ted
at
th
e
o
u
tp
u
t
o
f
th
e
n
eu
r
o
n
s
.
T
h
e
r
ea
s
o
n
f
o
r
th
e
m
u
ltip
le
ac
tiv
atio
n
f
u
n
ctio
n
s
is
to
en
s
u
r
e
v
ar
iatio
n
o
f
n
o
n
lin
ea
r
ities
,
wh
ich
h
elp
s
im
p
r
o
v
e
t
h
e
tr
ain
in
g
p
r
o
ce
s
s
.
T
h
e
n
eu
r
al
n
etwo
r
k
was
tr
ain
ed
with
d
ata
co
llected
f
r
o
m
t
h
e
C
STR
m
o
d
el
at
a
s
tead
y
s
tate
u
s
in
g
T
ab
l
e
3
.
T
h
e
d
ata
co
n
tain
C
STR
b
eh
av
io
r
p
ar
am
eter
s
s
u
ch
as
in
let
f
lo
w
r
ate
o
f
r
ea
ct
an
ts
A
an
d
B
,
co
n
ce
n
tr
atio
n
r
ate
o
f
p
r
o
d
u
cts
A
an
d
B
,
co
o
lan
t
tem
p
e
r
atu
r
e,
in
f
lo
w
tem
p
er
atu
r
e
,
an
d
co
o
la
n
t
f
lo
w
r
ate.
T
h
e
o
u
tp
u
t
tar
g
e
t
v
alu
e
is
co
n
ce
n
tr
atio
n
o
f
B
wh
ich
is
th
e
o
u
tlet.
T
h
e
tr
ain
in
g
p
r
o
ce
s
s
was d
o
n
e
with
g
r
ad
ien
t
d
escen
t
-
b
ased
tr
ain
in
g
alg
o
r
ith
m
[
4
6
]
.
Du
r
in
g
t
h
e
tr
ai
n
in
g
o
f
th
e
n
eu
r
al
n
etwo
r
k
with
p
ar
am
ete
r
s
i
n
T
ab
le
4
,
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
MSE
)
an
d
R
eg
r
ess
io
n
(
R
)
wer
e
r
esp
ec
tiv
ely
u
s
ed
to
m
ea
s
u
r
e
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
c
o
n
tr
o
l
laws.
T
h
e
MSE
was
u
s
ed
to
m
ea
s
u
r
e
th
e
e
r
r
o
r
th
at
o
cc
u
r
r
e
d
d
u
r
in
g
th
e
tr
ain
i
n
g
p
r
o
ce
s
s
,
with
th
e
tar
g
et
v
alu
e
o
f
ze
r
o
a
n
d
th
e
R
v
alu
e
o
f
1
.
T
h
e
p
er
f
o
r
m
an
ce
was
v
alid
at
ed
u
s
in
g
ten
f
o
ld
cr
o
s
s
-
v
alid
a
tio
n
tech
n
iq
u
e,
a
n
d
th
e
r
esu
lt
s
ar
e
p
r
esen
ted
in
T
ab
le
5
.
T
h
e
r
esu
lt
r
ep
o
r
ted
a
n
av
er
ag
e
MSE
o
f
0
.
0
3
0
3
3
e
-
1
0
an
d
an
R
o
f
0
.
9
7
6
1
4
.
T
h
e
im
p
licatio
n
s
o
f
th
e
tr
ain
in
g
r
esu
lt
s
h
o
wed
th
at
th
e
FF
NN
co
r
r
ec
tly
lear
n
ed
th
e
p
lan
t
f
ea
tu
r
es
an
d
was
also
ab
le
to
co
n
tr
o
l
d
y
n
am
ics co
r
r
ec
tly
.
T
h
e
o
u
tp
u
t p
r
o
d
u
ce
d
with
th
e
FF
NN
tr
ain
in
g
is
th
e
r
ef
e
r
en
ce
c
o
n
tr
o
l la
w
in
Alg
o
r
ith
m
4
.
2
.
3
.
3
.
P
I
D
co
ntr
o
l f
un
ct
io
n
T
h
e
PID
is
o
n
e
o
f
th
e
m
o
s
t
u
s
ed
co
n
tr
o
l
f
u
n
ctio
n
s
o
f
PLC
o
p
tim
izatio
n
.
T
h
e
PID
is
m
ad
e
u
p
o
f
th
e
in
teg
r
atio
n
o
f
t
h
r
ee
m
at
h
em
a
tical
f
u
n
ctio
n
s
wh
ic
h
ar
e
th
e
p
r
o
p
o
r
tio
n
al,
i
n
t
e
g
r
a
l
,
a
n
d
d
e
r
i
v
a
t
i
v
e
f
u
n
c
t
i
o
n
s
r
e
s
p
e
c
t
i
v
e
l
y
t
o
f
o
r
m
t
h
e
c
o
n
t
r
o
l
l
a
w
.
E
a
c
h
f
u
n
c
t
i
o
n
c
o
m
p
e
n
s
a
t
e
s
a
n
d
h
e
l
p
s
a
d
j
u
s
t
t
h
e
g
a
i
n
o
f
t
h
e
o
t
h
e
r
u
n
t
i
l
a
g
o
o
d
a
p
p
r
o
x
i
m
a
t
i
o
n
f
u
n
c
t
i
o
n
i
s
a
c
h
i
e
v
e
d
f
o
r
t
h
e
p
l
a
n
t
c
o
n
s
t
r
a
i
n
t
s
.
T
h
e
p
r
o
p
o
r
t
i
o
n
a
l
f
u
n
c
t
i
o
n
i
s
p
r
e
s
e
n
t
e
d
u
s
i
n
g
(
1
1
)
.
=
.
(
)
(
1
1
)
W
h
er
e
Kp
is
th
e
p
r
o
p
o
r
tio
n
al
g
ain
; th
e
in
teg
r
al
ter
m
is
p
r
ese
n
ted
(
1
2
)
.
=
∫
(
)
0
(
1
2
)
W
h
e
r
e
=
i
s
t
h
e
i
n
t
e
g
r
a
l
g
a
i
n
,
i
s
t
h
e
i
n
t
e
g
r
a
l
t
i
m
e
c
o
n
s
t
a
n
t
.
T
h
e
d
e
r
i
v
a
t
i
v
e
f
u
n
c
t
i
o
n
w
a
s
p
r
e
s
e
n
t
e
d
a
s
(
1
3
)
.
=
(
)
(
13)
W
h
er
e
=
is
th
e
d
er
iv
ativ
e
g
ain
.
T
h
e
r
elatio
n
s
h
ip
b
etwe
en
th
e
(
8
)
-
(
1
0
)
was
u
s
ed
to
d
ev
elo
p
th
e
PID
co
n
tr
o
ller
as in
(
1
4
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
6
,
No
.
1
,
Ma
r
c
h
20
2
5
:
212
-
224
218
=
(
1
+
1
+
.
2
)
=
(
1
+
1
+
)
(
1
4
)
Alg
o
r
ith
m
2
.
T
h
e
C
PA
p
s
eu
d
o
co
d
e
1)
Star
t
2)
Op
tim
ize
ch
r
o
m
o
s
o
m
es with
m
u
ltip
le
p
o
p
u
latio
n
alg
o
r
ith
m
s
3)
L
et
th
e
in
itial p
o
p
u
latio
n
s
ize
b
e
P
,
an
d
th
e
d
esire
d
in
c
r
ea
s
e
in
p
o
p
u
latio
n
s
ize
b
e
ΔP
4)
T
h
e
n
ew
p
o
p
u
latio
n
s
ize
is
d
eter
m
in
ed
as
P +
Δ
P
5)
Ad
ju
s
tin
g
cr
o
s
s
o
v
er
a
n
d
m
u
tatio
n
6)
T
h
e
alg
o
r
ith
m
ad
ju
s
ts
th
e
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
r
ates u
s
in
g
a
p
r
o
b
ab
ilit
y
f
u
n
ctio
n
b
etwe
en
0
an
d
1
7)
T
h
e
o
u
tp
u
t o
f
th
e
p
r
o
b
ab
ilit
y
f
u
n
ctio
n
is
u
s
ed
to
r
eg
u
late
th
e
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
o
p
er
at
io
n
s
8)
T
h
is
ad
ju
s
tm
en
t a
im
s
to
in
f
lu
e
n
ce
th
e
p
o
p
u
latio
n
d
iv
er
s
ity
9)
Selectin
g
th
e
b
est o
u
tco
m
e
with
L
SA
as (
n
)
10)
Dete
r
m
in
e
th
e
p
ar
eto
-
o
p
tim
a
l
s
o
lu
tio
n
s
with
m
u
lti
-
o
b
jectiv
e
ev
o
lu
tio
n
alg
o
r
ith
m
wh
ile
m
ain
tain
in
g
d
iv
er
s
ity
11)
R
ef
in
in
g
th
e
b
est o
u
tc
o
m
e
with
lo
ca
l sear
ch
o
p
er
ato
r
12)
Fin
e
tu
n
e
th
e
alg
o
r
ith
m
f
o
r
n
e
w
o
f
f
s
p
r
in
g
g
en
e
r
atio
n
13)
R
ec
o
m
m
en
d
th
e
o
f
f
s
p
r
in
g
14)
R
etu
r
n
A
lg
o
r
ith
m
3
.
Pro
p
o
s
ed
GA
1)
Star
t th
e
co
n
tr
o
l a
lg
o
r
ith
m
f
o
r
th
e
C
STR
2)
Op
tim
ize
th
e
co
n
tr
o
l
p
ar
am
ete
r
s
u
s
in
g
a
C
PA in
alg
o
r
ith
m
2
3)
Set th
e
in
itial p
o
p
u
latio
n
s
ize
as P,
an
d
d
e
ter
m
in
e
th
e
d
esire
d
in
cr
ea
s
e
in
p
o
p
u
latio
n
s
ize
as Δ
P
4)
C
alcu
late
th
e
n
ew
p
o
p
u
latio
n
s
ize
as P +
Δ
P
5)
Ad
ju
s
t
th
e
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
r
ates
with
in
th
e
GA
t
o
en
h
an
ce
th
e
ex
p
lo
r
atio
n
an
d
ex
p
lo
itatio
n
ca
p
ab
ilit
ies o
f
th
e
alg
o
r
ith
m
6)
Use
a
p
r
o
b
ab
ilit
y
f
u
n
ctio
n
b
et
wee
n
0
an
d
1
to
r
eg
u
late
th
e
c
r
o
s
s
o
v
er
a
n
d
m
u
tatio
n
o
p
er
atio
n
s
,
aim
in
g
t
o
in
f
lu
en
ce
th
e
p
o
p
u
latio
n
d
i
v
er
s
ity
an
d
im
p
r
o
v
e
th
e
q
u
ality
o
f
th
e
s
o
lu
tio
n
s
7)
Select
th
e
b
est o
u
tco
m
e
u
s
in
g
th
e
L
SA a
n
d
d
esig
n
ate
it a
s
N
8)
Utilize
a
m
u
lti
-
o
b
jectiv
e
ev
o
lu
tio
n
alg
o
r
ith
m
to
d
eter
m
in
e
th
e
Par
eto
-
o
p
tim
al
s
o
lu
tio
n
s
wh
ile
m
ain
tain
in
g
d
i
v
er
s
ity
am
o
n
g
t
h
e
s
o
lu
tio
n
s
9)
E
m
p
lo
y
a
lo
ca
l
s
ea
r
ch
o
p
er
ato
r
to
r
ef
in
e
th
e
b
est
o
u
tco
m
e
o
b
tain
ed
s
o
f
ar
,
aim
in
g
to
f
u
r
t
h
er
im
p
r
o
v
e
its
q
u
ality
an
d
co
n
v
er
g
en
ce
p
r
o
p
er
ties
10)
Fin
e
-
tu
n
e
th
e
alg
o
r
ith
m
'
s
p
ar
am
eter
s
an
d
co
n
tr
o
l settin
g
s
to
en
h
an
ce
th
e
g
en
er
ati
o
n
o
f
n
ew
o
f
f
s
p
r
in
g
11)
R
e
c
o
m
m
e
n
d
t
h
e
o
f
f
s
p
r
i
n
g
,
w
h
i
c
h
r
e
p
r
e
s
e
n
t
s
t
h
e
n
e
x
t
g
e
n
e
r
a
t
i
o
n
o
f
c
o
n
t
r
o
l
a
c
t
i
o
n
s
o
r
s
e
t
-
p
o
i
n
t
s
f
o
r
t
h
e
C
S
T
R
12)
R
etu
r
n
to
co
n
tin
u
e
th
e
iter
atio
n
s
o
f
th
e
GA,
iter
atin
g
th
r
o
u
g
h
s
tep
s
2
-
1
1
to
f
u
r
th
er
o
p
tim
ize
th
e
co
n
tr
o
l
o
f
th
e
C
STR
Alg
o
r
ith
m
4
.
FF
NN
co
n
tr
o
l f
u
n
ctio
n
1)
Star
t
2)
L
o
ad
C
STR d
ata
at
s
tead
y
s
tate
3)
Sp
lit in
to
tr
ain
in
g
an
d
test
(
8
0
:
2
0
)
4)
Sy
s
tem
id
en
tific
atio
n
as n
o
n
li
n
ea
r
au
to
r
eg
r
ess
iv
e
m
o
v
in
g
a
v
er
ag
e
5)
C
o
n
f
ig
u
r
e
n
eu
r
al
n
etw
o
r
k
a
r
c
h
itectu
r
e
6)
Activ
ate
n
eu
r
o
n
s
with
tan
h
f
u
n
ctio
n
at
th
e
in
p
u
t la
y
e
r
7)
Star
t g
r
ad
ien
t d
escen
t a
lg
o
r
ith
m
8)
Set M
SE
tar
g
et
≈
0
9)
Star
t tr
ain
in
g
n
eu
r
o
n
s
10)
Activ
ate
n
eu
r
o
n
s
with
p
u
r
elin
ac
tiv
atio
n
f
u
n
cti
o
n
at
th
e
o
u
tp
u
t la
y
er
11)
I
f
MSE
≈
0
12)
Sto
p
tr
ain
in
g
13)
Gen
er
ate
r
ef
er
e
n
ce
n
eu
r
o
co
n
t
r
o
l f
u
n
ctio
n
14)
E
ls
e
15)
Ad
ju
s
t n
eu
r
o
n
s
16)
Do
u
n
til
17)
MSE
≈
0
18)
Ap
p
ly
s
tep
(
1
2
)
19)
Sto
p
tr
ain
in
g
20)
E
n
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
C
o
mp
a
r
in
g
mu
lti
-
co
n
tr
o
l a
lg
o
r
ith
ms fo
r
co
mp
lex
n
o
n
lin
ea
r
s
ystem
…
(
S
o
ch
ima
V
in
ce
n
t E
g
o
ig
w
e
)
219
T
ab
le
3
.
Stead
y
s
tate
p
ar
a
m
ete
r
s
o
f
th
e
C
STR
P
a
r
a
me
t
e
r
s
U
n
i
t
V
a
l
u
e
P
a
r
a
me
t
e
r
s
U
n
i
t
V
a
l
u
e
V
o
l
u
me
t
r
i
c
f
l
o
w
r
a
t
e
m
3
/h
1
.
0
0
0
0
0
B
o
l
t
z
ma
n
n
’
s
i
d
e
a
l
g
a
s c
o
n
st
a
n
t
k
c
a
l
/
k
g
m
o
l
1
.
9
8
5
9
0
R
e
a
c
t
o
r
V
o
l
u
me
m
3
1
.
0
0
0
0
0
R
e
a
c
t
i
o
n
h
e
a
t
k
c
a
l
/
k
g
m
o
l
-
5
9
6
0
Pre
-
e
x
p
o
n
e
n
t
i
a
l
n
o
n
-
t
h
e
r
mal
f
a
c
t
o
r
1
/
h
3
.
5
5
6
2
e
+
0
8
C
a
p
a
c
i
t
y
o
f
h
e
a
t
d
e
n
s
i
t
y
m
3
k
4
7
0
.
3
0
A
c
t
i
v
a
t
i
o
n
e
n
e
r
g
y
k
c
a
l
/
k
g
m
o
l
1
1
8
5
1
.
4
H
e
a
t
t
r
a
n
sf
e
r
k
c
a
l
/
k
*
h
1
4
5
.
1
0
1
S
e
t
p
o
i
n
t
(
T
a
n
d
C
)
K
a
n
d
m
o
l
/
m
3
3
1
1
a
n
d
1
1
B
o
l
t
z
ma
n
n
’
s
i
d
e
a
l
g
a
s c
o
n
st
a
n
t
k
c
a
l
/
k
g
m
o
l
1
.
9
8
5
9
0
T
ab
le
4
.
FF
NN
tr
ain
in
g
p
a
r
am
eter
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
H
i
d
d
e
n
l
a
y
e
r
7
Tr
a
i
n
i
n
g
sam
p
l
e
s
8
0
0
0
D
e
l
a
y
o
u
t
p
u
t
2
M
a
x
.
i
n
t
e
r
v
a
l
(
s)
20
I
n
t
e
r
v
a
l
(
s)
0
.
2
M
a
x
.
p
l
a
n
t
i
n
p
u
t
3
M
a
x
.
o
u
t
p
u
t
3
M
i
n
.
i
n
t
e
r
v
a
l
(
s)
5
D
e
l
a
y
i
n
p
u
t
2
M
i
n
.
p
l
a
n
t
i
n
p
u
t
0
M
i
n
.
o
u
t
p
u
t
3
Tr
a
i
n
i
n
g
e
p
o
c
h
s
2
0
0
T
ab
le
5
.
T
r
ai
n
in
g
a
n
d
v
ali
d
S
/
N
M
S
E
R
e
g
r
e
ssi
o
n
1
0
.
0
0
2
8
4
5
e
-
10
0
.
9
7
2
9
2
0
.
0
0
5
4
2
3
e
-
10
0
.
9
7
5
2
3
0
.
0
0
4
5
3
5
e
-
10
0
.
9
8
3
2
4
0
.
0
2
4
1
6
5
e
-
10
0
.
9
5
3
9
5
0
.
0
4
8
3
4
5
e
-
10
0
.
9
8
0
9
6
0
.
0
3
0
2
4
5
e
-
10
0
.
9
8
1
7
7
0
.
0
4
5
3
2
e
-
10
0
.
9
8
1
1
8
0
.
0
5
2
8
7
e
-
10
0
.
9
8
3
7
9
0
.
0
3
4
1
2
e
-
10
0
.
9
7
4
9
10
0
.
0
5
5
4
2
e
-
10
0
.
9
7
3
9
A
v
g
0
.
0
3
0
3
3
e
-
10
0
.
9
7
6
1
4
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
m
o
d
els
o
f
th
e
C
STR
an
d
th
e
th
r
ee
AC
S
alg
o
r
ith
m
s
u
s
ed
f
o
r
th
e
o
p
tim
izatio
n
o
f
th
e
PLC
wer
e
test
ed
in
an
ex
p
er
im
en
tal
te
s
t
m
ad
e
o
f
Siem
en
s
PLC,
l
ap
to
p
in
s
talled
with
Stu
d
o
5
0
0
s
o
f
twar
e,
h
u
m
a
n
m
ac
h
in
e
in
ter
f
ac
e
,
s
o
m
atic
m
an
ag
er
s
o
f
twar
e
.
T
h
e
p
a
r
am
et
er
s
in
T
ab
le
s
1
-
3
wer
e
u
s
ed
f
o
r
th
e
p
r
o
g
r
am
m
in
g
with
th
e
r
ef
er
en
ce
tem
p
er
atu
r
e
s
et
-
p
o
in
t
ch
an
g
es
f
r
o
m
3
1
1
-
313
(
)
an
d
co
n
ce
n
t
r
atio
n
at
1
0
-
1
0
.
3
(
/
3
)
.
T
h
e
p
e
r
f
o
r
m
an
ce
o
f
th
e
p
la
n
t
was
ch
an
g
ed
v
ia
th
e
in
tr
o
d
u
ctio
n
o
f
s
tep
ch
a
n
g
e
at
v
ar
io
u
s
in
s
tan
ce
s
o
f
th
e
tech
n
ical
p
r
o
ce
s
s
,
wh
ile
th
e
co
n
tr
o
l
alg
o
r
ith
m
s
wer
e
m
o
n
ito
r
ed
co
n
s
id
er
in
g
o
v
er
s
h
o
o
t
an
d
r
esp
o
n
s
e
tim
e
as
th
e
tr
y
to
ad
ap
t
an
d
f
o
llo
w
th
e
r
ef
er
en
ce
s
et
-
p
o
in
t
an
d
p
er
f
o
r
m
d
is
tu
r
b
a
n
ce
r
ejec
tio
n
.
T
h
e
b
atch
r
ea
c
to
r
p
r
esen
ts
th
e
d
y
n
am
ic
b
eh
a
v
io
r
of
th
e
two
co
n
n
ec
ted
tan
k
s
wh
o
s
e
co
n
ce
n
tr
atio
n
wer
e
m
o
d
elled
in
th
e
(
1
)
an
d
(
2
)
,
tem
p
er
at
u
r
e
d
y
n
am
ic
m
o
d
eled
in
(
3
)
an
d
(
4
)
,
an
d
th
en
v
o
lu
m
etr
ic
f
lo
w
r
ates
o
f
th
e
f
l
o
w
m
o
d
elled
in
th
e
(
5
)
an
d
(
6
)
.
T
o
c
o
n
tr
o
l
th
e
s
y
s
tem
,
th
e
v
ar
iatio
n
s
b
etwe
en
i
n
p
u
t
an
d
c
o
n
tr
o
lled
v
ar
iab
les
ar
e
d
ef
in
ed
as
er
r
o
r
s
(
1
,
12
,
21
,
22
,
31
,
32
)
.
T
h
ese
e
r
r
o
r
s
ar
e
r
elate
d
t
o
th
e
i
n
p
u
t
an
d
co
n
t
r
o
lled
co
n
ce
n
tr
atio
n
s
(
,
2
)
,
in
p
u
t
a
n
d
c
o
n
tr
o
lle
d
tem
p
e
r
at
u
r
es
(
,
,
2
,
2
,
1
,
1
,
1
,
1
)
.
T
h
e
e
x
p
er
im
en
tal
s
etu
p
u
s
ed
f
o
r
th
e
d
ata
m
o
n
ito
r
in
g
o
f
th
e
b
atch
r
ea
cto
r
was p
r
esen
ted
in
F
ig
u
r
e
1
.
Fig
u
r
e
1
.
T
h
e
ex
p
er
im
en
tal
s
etu
p
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
6
,
No
.
1
,
Ma
r
c
h
20
2
5
:
212
-
224
220
T
h
e
ex
p
e
r
im
en
tal
s
etu
p
was
u
s
ed
to
m
o
n
ito
r
th
e
t
h
er
m
o
d
y
n
am
ic
p
r
o
ce
s
s
o
f
t
h
e
b
atch
r
ea
c
to
r
p
lan
ts
.
T
h
e
o
b
jectiv
e
was
to
u
s
e
its
u
n
ce
r
tain
p
a
r
am
eter
s
as
in
(
4
)
a
s
in
p
u
t
to
ea
ch
o
f
th
e
co
n
tr
o
l
a
lg
o
r
ith
m
s
an
d
th
e
n
im
p
r
o
v
e
th
e
PLC
f
o
r
b
etter
co
n
tr
o
l
o
f
co
m
p
lex
r
ea
cto
r
s
.
T
ab
le
3
was
u
s
ed
f
o
r
th
e
test
in
g
p
ar
am
eter
s
,
in
two
d
if
f
er
en
t
test
s
,
wh
ile
th
e
r
esu
l
t
o
f
test
1
co
m
p
ar
ativ
e
r
esp
o
n
s
e
o
f
th
e
alg
o
r
ith
m
s
(
PID
,
I
m
p
r
o
v
e
d
GA,
ANN)
u
s
in
g
er
r
o
r
tem
p
er
atu
r
e
f
r
o
m
th
e
r
ea
cto
r
as
in
(
7
)
as
in
p
u
t
to
co
n
tr
o
l
th
e
p
lan
t
an
d
p
r
o
d
u
ce
th
e
s
tab
ilized
co
n
tr
o
ller
o
u
tp
u
t
r
esu
lt
in
Fig
u
r
e
2
wh
ic
h
was
p
r
o
d
u
ce
d
f
r
o
m
(
8
)
a
n
d
also
th
e
c
o
n
tr
o
lled
tem
p
er
atu
r
e
f
o
r
th
e
th
r
ee
alg
o
r
ith
m
s
as
m
o
d
elled
in
(
9
)
an
d
r
e
p
o
r
ted
in
Fig
u
r
e
3
.
T
h
ese
co
n
tr
o
l
o
u
tco
m
es
wer
e
ac
h
iev
ed
f
r
o
m
th
e
in
jecte
d
co
o
lan
t in
(
1
0
)
wh
ich
also
p
r
o
d
u
c
e
th
e
r
esu
lt in
Fig
u
r
e
4
.
Fig
u
r
es
2
-
4
p
r
esen
t
th
e
r
esu
lt
o
f
th
e
p
lan
t
test
with
th
e
th
r
ee
AC
S
d
ev
elo
p
ed
to
o
p
tim
ize
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
PLC.
Fig
u
r
e
2
s
h
o
ws
th
e
co
n
tr
o
l c
o
n
ce
n
t
r
atio
n
o
f
th
e
p
lan
t w
h
ich
was a
ch
ie
v
ed
d
u
e
to
th
e
tem
p
er
atu
r
e
c
o
n
tr
o
l
r
esp
o
n
s
e
i
n
Fig
u
r
e
3
,
u
s
in
g
th
e
c
o
o
lan
t
i
n
Fig
u
r
e
4
.
T
h
e
r
esu
lt
s
h
o
wed
th
at
th
e
th
r
ee
AC
S
all
f
o
llo
wed
th
e
r
ef
er
e
n
ce
s
et
-
p
o
in
t
to
c
o
n
tr
o
l
th
e
v
ar
iatio
n
i
n
co
n
ce
n
tr
atio
n
i
n
(
1
)
an
d
te
m
p
er
atu
r
e
v
ar
iatio
n
in
(
2
)
.
T
h
e
PID
f
u
n
ctio
n
s
ea
c
h
ap
p
r
o
x
im
ated
t
h
e
c
o
n
tr
o
l
p
a
r
am
eter
s
an
d
s
u
m
u
p
th
e
th
r
e
e
co
m
p
u
ted
o
u
tp
u
ts
as
th
e
co
n
tr
o
l
f
u
n
ctio
n
as
m
o
d
eled
in
(
1
4
)
t
o
a
p
p
r
o
x
im
ate
t
h
e
p
lan
t.
T
h
e
im
p
r
o
v
e
d
GA
i
n
alg
o
r
ith
m
(
3
)
o
n
t
h
e
o
th
er
h
an
d
co
llects
th
e
p
o
p
u
la
tio
n
s
ize
o
f
th
e
p
lan
t
u
s
in
g
th
e
C
PA
a
lg
o
r
ith
m
to
o
p
tim
ize
th
e
p
o
p
u
latio
n
an
d
ad
d
r
ess
p
r
e
-
m
atu
r
e
co
n
v
er
g
e
n
ce
p
r
o
b
lem
,
th
e
n
ap
p
l
y
f
itn
e
s
s
test
to
g
en
er
ate
n
ew
s
am
p
l
es
wh
ich
co
n
v
er
g
e
an
d
co
n
tr
o
l
th
e
p
lan
ts
af
ter
s
er
ies o
f
m
u
tatio
n
a
n
d
cr
o
s
s
o
v
er
.
Fig
u
r
e
2
.
C
o
n
tr
o
lled
co
n
ce
n
tr
a
tio
n
Fig
u
r
e
3
.
C
o
n
tr
o
lled
tem
p
e
r
atu
r
e
Fig
u
r
e
4
.
C
o
o
lan
t
tem
p
er
atu
r
e
Fro
m
th
e
r
esu
lt,
it
was
o
b
s
er
v
ed
th
at
th
e
PID
ex
p
er
ien
ce
s
o
v
er
s
h
o
t,
w
h
ile
th
at
o
f
th
e
GA
was
s
lig
h
t.
T
h
e
r
ea
s
o
n
f
o
r
th
e
o
v
er
s
h
o
t
in
th
e
GA
d
esp
ite
th
e
o
p
tim
izatio
n
with
t
h
e
C
PA
alg
o
r
ith
m
was
d
u
e
to
th
e
u
n
ce
r
tain
ch
a
r
ac
ter
is
tics
o
f
th
e
th
er
m
o
d
y
n
am
ic
p
r
o
ce
s
s
wh
ich
ch
an
g
es
with
tim
e
an
d
m
ay
n
o
t
b
e
ca
p
t
u
r
ed
b
y
th
e
GA.
Fu
r
th
e
r
m
o
r
e
,
th
e
ANN
was
ab
le
to
co
n
tr
o
l
th
e
o
v
e
r
s
h
o
o
t
a
n
d
ac
h
iev
ed
a
b
etter
s
tead
y
s
tate
with
th
e
p
lan
t.
Simi
lar
ly
,
at
th
e
p
o
in
t o
f
s
tep
ch
an
g
e
o
f
th
e
v
ar
io
u
s
in
s
tan
ce
s
,
th
e
PID
an
d
G.
A
o
v
er
s
h
o
o
ts
(
s
ee
T
ab
le
6
f
o
r
o
v
er
s
h
o
o
t
p
e
r
ce
n
tag
e
)
,
w
h
ile
tr
y
in
g
to
r
ejec
t
d
is
tu
r
b
an
ce
,
also
th
e
ANN
p
er
f
ec
tly
f
o
llo
ws
th
e
r
ef
e
r
en
ce
s
et
-
p
o
in
t
an
d
c
o
n
tr
o
ls
th
e
p
lan
t
with
a
lim
ited
o
v
er
s
h
o
o
t
o
f
1
.
1
2
%.
An
o
th
er
test
2
was
p
er
f
o
r
m
ed
,
s
ettin
g
th
e
in
itialize
tem
p
er
atu
r
e
an
d
co
n
ce
n
tr
atio
n
o
f
th
e
p
l
an
t
at
3
1
0
.
5
-
3
1
3
.
5
(
)
an
d
co
n
ce
n
tr
atio
n
at
10
-
1
0
.
2
5
(
k
gmol
/
m
3
)
,
wh
ile
th
e
tem
p
er
atu
r
e
in
s
tan
ce
s
wer
e
v
ar
y
in
g
at
v
ar
io
u
s
s
tep
s
o
f
th
e
tech
n
ica
l
p
r
o
ce
s
s
,
to
g
iv
e
r
o
o
m
f
o
r
th
e
ev
alu
atio
n
o
f
t
h
e
AC
S
alg
o
r
ith
m
u
s
ed
to
o
p
tim
ize
th
e
PID
.
T
h
e
r
esu
lts
wer
e
p
r
esen
ted
in
Fig
u
r
es 5
-
7
,
wh
ile
m
o
r
e
an
al
y
s
is
was p
r
esen
ted
in
T
ab
le
7
.
Fro
m
th
e
r
esu
lt
o
f
th
e
test
r
e
s
u
lt,
it
was
o
b
s
er
v
ed
th
at
th
e
v
ar
iatio
n
o
f
tem
p
er
atu
r
e
,
in
t
h
e
v
ar
i
o
u
s
in
s
tan
ce
s
af
f
ec
ts
th
e
co
n
ce
n
t
r
atio
n
o
f
th
e
p
lan
t,
wh
ile
th
e
PID
,
GA
,
an
d
ANN
alg
o
r
ith
m
s
tr
y
to
r
ejec
t
d
is
tu
r
b
an
ce
o
n
th
e
p
lan
t.
T
h
e
s
tead
y
s
tate
was
ac
h
ie
v
ed
v
ia
th
e
in
jectio
n
o
f
th
e
co
o
lan
t
in
t
o
th
e
r
ea
ct
o
r
.
Fr
o
m
th
e
o
u
tco
m
e,
it wa
s
o
b
s
er
v
e
d
t
h
at
th
e
co
n
tr
o
l a
lg
o
r
ith
m
s
f
o
ll
o
wed
a
s
im
ilar
tr
en
d
in
th
e
f
ir
s
t te
s
t,
wi
th
th
e
PID
an
d
G.
A
ex
p
er
ien
cin
g
o
v
e
r
s
h
o
o
t,
wh
ile
ANN
o
v
er
s
h
o
o
t
w
as
m
in
im
al
as
in
T
ab
le
6
,
als
o
is
th
e
co
m
p
a
r
ativ
e
r
esp
o
n
s
e
o
f
test
2
in
T
ab
le
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
C
o
mp
a
r
in
g
mu
lti
-
co
n
tr
o
l a
lg
o
r
ith
ms fo
r
co
mp
lex
n
o
n
lin
ea
r
s
ystem
…
(
S
o
ch
ima
V
in
ce
n
t E
g
o
ig
w
e
)
221
T
ab
les
6
a
n
d
7
p
r
esen
t
th
e
c
o
m
p
ar
ativ
e
an
aly
s
is
o
f
th
e
co
n
tr
o
l
alg
o
r
ith
m
s
test
ed
o
n
th
e
n
o
n
lin
ea
r
p
lan
t.
T
h
e
r
esu
lt
s
h
o
wed
th
at
t
h
e
FF
NN
-
PLC
ac
h
iev
ed
a
b
ett
er
co
n
tr
o
l
r
esp
o
n
s
e
c
o
n
s
id
er
in
g
th
e
o
v
e
r
s
h
o
t
a
n
d
r
esp
o
n
s
e
tim
e
to
d
is
tu
r
b
an
ce
r
ejec
tio
n
wh
en
co
m
p
a
r
ed
with
th
e
GA
an
d
PID
co
u
n
ter
p
ar
ts
.
T
h
e
r
ea
s
o
n
was
d
u
e
to
t
h
e
in
tellig
en
ce
o
f
th
e
n
eu
r
o
n
s
wh
ich
u
n
d
er
s
tan
d
th
e
p
lan
t
b
e
h
av
io
r
an
d
u
s
e
th
e
r
e
f
er
en
ce
to
tr
ac
k
th
e
s
et
p
o
in
ts
.
T
h
e
o
v
er
s
h
o
t
an
d
d
elay
e
x
p
er
ien
ce
d
b
y
th
e
GA
was
d
u
e
to
th
e
tie
it
tak
es
to
co
llect
th
e
ch
r
o
m
o
s
o
m
es,
p
er
f
o
r
m
f
itn
ess
,
an
d
m
u
tatio
n
u
n
til
th
e
d
esire
d
co
n
tr
o
l
r
esp
o
n
s
e
is
ex
p
e
r
ien
ce
d
.
T
h
ese
r
esu
lts
in
d
elay
s
in
th
e
p
lan
t,
lik
ewise
th
e
ca
s
e
o
f
th
e
PID
wh
er
e
its
in
d
iv
id
u
al
P
-
I
-
D
m
ath
em
ati
ca
l
f
u
n
ctio
n
s
act
on
th
e
co
n
s
tr
ain
ts
to
r
ejec
t d
is
tu
r
b
an
ce
an
d
co
n
tr
o
l th
e
p
la
n
t.
Fig
u
r
e
5
.
C
o
n
tr
o
lled
tem
p
e
r
atu
r
e
Fig
u
r
e
6
.
C
o
n
tr
o
lled
co
n
ce
n
tr
a
tio
n
Fig
u
r
e
7
.
C
o
o
lan
t
tem
p
er
atu
r
e
T
ab
le
6
.
T
est 1
c
o
m
p
ar
ativ
e
r
e
s
p
o
n
s
e
C
o
n
t
r
o
l
l
a
w
s
O
v
e
r
sh
o
o
t
(
%)
S
e
t
t
l
i
n
g
t
i
m
e
(
sam
p
l
e
s)
P
I
D
-
P
LC
3
1
.
2
5
2
3
.
1
3
GA
-
P
LC
1
2
.
1
5
3
5
.
0
0
F
F
N
N
-
P
LC
1
.
1
2
8
.
7
5
T
ab
le
7
.
T
est co
m
p
ar
ativ
e
r
es
p
o
n
s
e
C
o
n
t
r
o
l
l
a
w
s
O
v
e
r
sh
o
o
t
(
%)
S
e
t
t
l
i
n
g
t
i
me
(
sam
p
l
e
s)
P
I
D
-
P
LC
3
5
.
1
7
2
7
.
0
0
GA
-
P
LC
2
2
.
3
1
4
1
.
0
0
F
F
N
N
-
P
LC
3
.
0
0
1
0
.
3
0
-
Data
av
ailab
ilit
y
T
h
e
d
ata
u
s
ed
f
o
r
th
is
wo
r
k
is
av
ailab
le
at
k
ag
g
le.
co
m
/d
atasets
/ed
d
ar
d
d
/co
n
tin
u
o
u
s
-
s
tirr
ed
-
tan
k
-
r
ea
cto
r
-
d
o
m
ain
-
a
d
ap
tatio
n
.
4.
CO
NCLU
SI
O
N
T
h
is
r
esear
ch
h
as
s
u
cc
ess
f
u
lly
ev
alu
ated
th
e
im
p
ac
t
o
f
v
ar
io
u
s
co
n
tr
o
l
alg
o
r
ith
m
s
o
n
th
e
PLC
an
d
test
ed
d
u
r
in
g
c
o
m
p
lex
tec
h
n
i
ca
l
p
r
o
ce
s
s
es
,
wh
er
e
m
u
ltip
le
co
n
s
tr
ain
ts
ar
e
co
n
tr
o
lled
.
F
r
o
m
th
e
r
e
v
iew
o
f
liter
atu
r
es,
it
was
o
b
s
er
v
ed
th
at
m
an
y
wo
r
k
s
h
a
v
e
b
ee
n
p
r
e
s
en
ted
wh
ich
o
p
tim
ized
PLC
p
er
f
o
r
m
an
ce
d
u
r
in
g
co
n
tr
o
l
o
f
n
o
n
lin
ea
r
s
y
s
tem
,
h
o
wev
er
th
is
p
ap
er
f
o
c
u
s
ed
o
n
ex
ten
d
in
g
th
is
PLC
f
u
n
ctio
n
ality
to
m
o
r
e
co
m
p
lex
n
o
n
lin
ea
r
s
y
s
tem
s
,
co
n
s
id
er
in
g
G.
A,
PID
,
an
d
A
NN
r
esp
ec
tiv
ely
as
t
h
e
c
o
n
tr
o
l
alg
o
r
ith
m
s
test
ed
s
ep
ar
ately
o
n
a
co
m
p
le
x
th
e
r
m
o
d
y
n
am
ic
p
r
o
ce
s
s
.
Fro
m
th
e
r
esu
lt,
it
was
o
b
s
er
v
e
d
th
at
all
th
r
ee
alg
o
r
ith
m
s
tr
ied
to
f
o
llo
w
th
e
r
ef
e
r
en
ce
s
et
-
p
o
in
ts
an
d
co
n
tr
o
l
th
e
p
la
n
t;
h
o
wev
e
r
,
th
eir
b
e
h
av
io
r
d
u
r
in
g
th
is
p
r
o
ce
s
s
v
ar
ies
co
n
s
id
er
in
g
s
ettlin
g
tim
e
an
d
o
v
e
r
s
h
o
o
t.
T
h
e
PID
ex
p
er
ien
ce
s
o
v
er
s
h
o
o
t
a
n
d
h
en
ce
n
o
t
r
ec
o
m
m
en
d
ed
f
o
r
th
e
co
n
tr
o
l
o
f
m
u
lti
-
v
a
r
ian
t
d
y
n
am
ic
s
y
s
tem
s
,
th
e
im
p
r
o
v
ed
GA
r
ec
o
r
d
ed
g
o
o
d
c
o
n
tr
o
l
p
er
f
o
r
m
an
ce
wit
h
lim
ited
o
v
er
s
h
o
o
t
b
u
t
s
u
f
f
er
s
d
elay
tr
ain
in
g
tim
e
T
h
e
ANN
ac
h
iev
ed
b
etter
r
esp
o
n
s
e
to
d
is
tu
r
b
an
ce
id
en
tific
atio
n
a
n
d
r
ejec
tio
n
w
h
en
c
o
m
p
ar
e
d
to
th
e
PID
an
d
th
e
im
p
r
o
v
ed
GA.
Ov
e
r
all,
it
ca
n
b
e
d
ed
u
ce
d
th
at
o
p
tim
izin
g
PLC it n
eu
r
al
n
etwo
r
k
co
n
tr
o
l a
lg
o
r
ith
m
will p
r
o
v
id
e
th
e
n
ee
d
ed
ad
a
p
tiv
e
co
n
tr
o
l f
u
n
ctio
n
ality
f
o
r
th
e
ap
p
r
o
x
im
atio
n
o
f
c
o
m
p
lex
n
o
n
l
in
ea
r
s
y
s
tem
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.