In
te
r
n
ation
a
l Jou
rn
al
o
f Po
we
r
Elec
tron
ic
s an
d
D
r
ive S
y
stem
(IJ
PED
S
)
V
o
l.
10, N
o.
1, Mar
ch 20
19,
p
p.
423~
4
3
2
IS
S
N
: 2088-
86
94,
D
O
I
:
10.11
59
1
/ij
ped
s
.
v10
.
i
1.pp
4
23-
43
2
423
Jou
rn
a
l
h
o
me
pa
ge
:
ht
tp:
//i
a
e
score
.
com
/
j
o
u
r
na
l
s
/
i
n
d
e
x
.
p
hp/IJ
PED
S
Maximum power control fo
r
photovoltaic system using
intellige
n
t strate
gies
Mo
ha
mmed
S
limi,
Ab
d
e
lk
rim Bo
uchet
a
, Bo
u
s
m
a
h
a
Bouchiba
Dep
a
rtm
e
n
t
o
f El
ectrical
En
g
i
n
eer
i
ng,
U
niv
e
rsit
y
of
T
ahri
M
o
h
am
m
e
d
BP4
17,
A
lgeria
Art
i
cl
e In
fo
ABSTRACT
A
r
tic
le hist
o
r
y
:
Re
ce
i
v
e
d
A
pr 20,
2
0
1
8
Re
vise
d N
ov
5
, 2018
A
c
c
e
pte
d
D
ec 5,
201
8
Th
e
p
o
w
e
r
s
u
p
p
l
i
ed
b
y
ph
o
t
ovolt
a
ic
D
C–
DC
c
o
n
verter
i
s
a
f
fected
by
t
wo
f
acto
r
s
,
s
u
n
i
rradi
a
nce
a
n
d
tem
p
e
r
at
ure.
T
heref
o
re,
to
i
mp
rov
e
the
perf
o
r
man
ce
o
f
t
h
e
P
V
system;
a
m
ech
a
n
is
m
to
t
rac
k
t
he
m
ax
im
um
power
po
in
t
(MP
P
)
i
s
requ
ired.
Con
v
en
ti
onal
m
a
xim
u
m
pow
er
p
o
i
n
t
t
rack
in
g
app
r
oach
es
,
s
u
ch
a
s
o
b
s
e
rvati
o
n
and
pert
urb
a
tio
n
t
echn
i
q
u
e
p
r
es
ent
so
m
e
diff
icu
lti
es
i
n
id
entif
y
i
ng
t
he
t
rue
MPP.
T
heref
o
re,
inte
l
l
i
g
e
n
t
sys
t
e
m
s
in
clu
d
i
ng
f
u
zzy
l
o
g
i
c
c
on
trolle
rs
(
F
L
C)
a
re
i
ntro
duced
f
or
t
he
ma
x
i
m
u
m
po
wer
p
o
i
n
t
t
r
ack
i
n
g
sy
st
em
(
MP
P
T
).
I
n
t
h
i
s
p
aper
,
w
e
pr
e
s
e
nt
a
c
o
m
pa
ra
tive
st
ud
y
of
t
h
e
P
V
s
t
and
a
lo
ne
s
ystem
which
is
c
o
n
trolled
by
t
h
r
ee
techn
i
q
u
es
.
Th
e
fi
rst
o
n
e
is
c
on
ven
t
i
onal
based
o
n
t
he
observ
a
ti
on
and
pert
u
r
bati
on
tech
ni
que,
t
h
e
other
are
in
tell
ig
e
n
t
b
a
sed
o
n
f
uzzy
l
og
ic
accor
ding
M
a
m
da
n
i
and
Tak
a
gi
-Su
g
en
o
m
o
dels
.
T
h
e
i
n
v
e
sti
g
atio
ns
s
h
o
w
th
at
t
he
f
uzz
y
log
i
c
con
t
ro
llers
prov
id
e
t
h
e
bes
t
r
esu
lts
a
nd
T
akag
i-S
u
g
e
no
m
o
d
el
p
r
esent
s
t
h
e
lo
wer
o
v
ers
hoot
v
alu
e
.
K
eyw
ord
s
:
Conve
r
ter
Fu
zz
y
l
ogi
c
M
a
md
an
i
mo
de
l
MPP
T
P&O
Phot
o
v
o
lta
ic
Taka
gi
-
S
uge
n
o
model
Co
pyri
gh
t © 2
019 In
stit
u
t
e
of Advanced
En
gi
neeri
n
g
an
d
S
c
ien
ce.
All
rights
res
e
rv
ed.
Corres
pon
d
i
n
g
Au
th
or:
Moham
m
ed. Sli
m
i
,
D
e
pa
rtme
nt
o
f
El
e
c
t
rica
l
Eng
i
ne
eri
ng,
Lab
o
ra
tor
y
of
R
e
sear
ch C
o
n
t
r
ol, A
nalysis
a
nd O
p
timiz
at
io
n
of El
e
c
t
ro-E
ner
g
e
tic S
yste
ms,
U
n
i
v
ersi
ty o
f
Tahri M
o
ham
m
e
d
BP
417,
Bec
har
(080
00),
A
l
geria
.
Em
ail:
moha
mm
ed.
s
lim
i21
3
@
gm
ai
l.c
o
m
1.
I
N
TR
OD
U
C
TI
O
N
S
o
lar
ener
gy
i
s
i
n
e
xha
us
t
i
b
l
e
,
f
re
e
an
d
c
l
e
a
n
a
nd
i
t
i
s
c
on
side
red
as
t
he
c
or
e
of
r
e
n
ew
a
b
le
e
nerg
y
(RE)
i
n
t
h
e
rec
e
nt
tim
es
p
r
i
m
a
r
i
ly
b
eca
us
e
o
f
r
un
nin
g
d
ow
n
o
f
f
oss
il
fue
l
s.
A
m
ong
vari
ous
R
E
r
e
sourc
e
s,
ph
o
t
o
v
o
l
t
a
i
c
(P
V)
s
ystem
pla
y
s
a
ve
ry
i
m
por
tan
t
r
ole
e
ithe
r
i
n
gr
id-c
o
nnec
t
e
d
o
r
isla
n
d
i
ng
c
o
n
f
ig
urati
o
ns.
H
o
w
e
ve
r,
t
he
P
V
system
s
ge
nera
t
e
i
nter
mi
t
t
en
t
p
o
w
e
r
u
nde
r
fl
uct
ua
t
i
n
g
w
e
a
ther
w
hic
h
i
s
the
m
a
i
n
i
ss
ue
t
ha
t
must be
t
a
ke
n i
n
co
n
s
i
de
rat
i
o
n
[
1]
, [2].
T
he
pow
er
-vo
l
t
a
ge
and
c
u
rre
nt–
v
o
lta
ge c
har
acte
r
istics
are
re
spo
n
sib
l
e
f
o
r
t
h
e
p
o
w
e
r
g
en
e
r
at
ed
f
rom
t
h
e
PV
c
e
ll.
T
h
e
re
fo
re
,
to
w
o
r
k
th
e
P
V
g
e
n
e
r
at
io
n
at
i
ts
p
ea
k
;
t
he
M
P
P
T
me
cha
n
ism
is
h
i
g
hly
si
g
n
i
f
i
c
ant
in
P
V
syst
em
[
3]-[6]
.
N
u
m
e
r
ous
M
PPT
m
e
c
h
ani
s
ms
h
a
v
e
b
e
en
i
nt
rod
u
c
ed
by
m
a
n
y
sc
h
o
l
ars
s
i
nce
year
1
96
0
.
S
om
e
w
e
ll-k
n
o
w
n
M
M
P
T
m
e
t
h
o
d
s
are
inc
r
em
ent
a
l
c
o
nd
u
c
tance
(IC)
me
tho
d
,
per
t
ur
b
a
nd
o
b
ser
v
e
(P
&O)
me
t
h
o
d
an
d
c
ons
ta
nt
v
o
lta
ge
(
CV)
m
e
thod
[
7]-[
9].
The
m
e
thod
o
f
P&O
w
a
s
e
x
t
e
ns
ive
l
y
use
d
d
ue
t
o
i
t
s
sim
p
l
e
c
o
n
tr
ol
m
eth
o
d
a
s
w
e
l
l
a
s
t
h
e
m
i
nim
u
m
n
u
mbe
r
o
f
it
s
in
put
para
me
ters.
H
o
w
e
ver,
t
he
u
se
o
f
th
is
a
lg
or
ith
m
le
ads
t
o
a
l
o
s
s
in
pow
er
d
u
e
t
o
a
n
e
norm
ous
o
sc
i
l
l
a
tio
n
in
t
h
e
are
a
o
f
m
a
xim
u
m
pow
e
r
p
o
i
nt
(
M
P
P
)
.
O
t
her
s
,
li
ke
I
C
m
e
th
o
d
s
ha
ve
b
e
e
n
pro
p
o
sed
by
s
o
me
r
ese
a
rc
hers
[7],
[
8]
,
w
h
ich
som
e
how
c
o
u
l
d
e
l
i
m
ina
t
e
t
h
e
osc
i
l
l
at
i
o
n
s
i
n
t
h
e
a
re
a
of
t
he
M
P
P
.
H
ow
e
v
er,
th
is
k
i
nd
of
me
tho
d
s
ne
e
d
g
o
o
d
a
nd
a
cc
u
r
ate
se
nsor
t
o
m
e
a
s
ure
e
ithe
r
v
olta
ge
o
r
c
u
rrent.
R
e
ce
nt
l
y
,
the
M
P
PT-
b
ased
A
r
tificia
l
inte
l
l
i
g
e
n
ce
(
A
I)
is
w
ide
l
y
use
d
i
n
P
V
c
on
ve
rte
r
w
i
t
h
grea
t
d
ynam
i
cs
a
n
d
h
i
g
h
e
f
fe
c
tive
n
e
ss.
V
a
r
i
ous
i
nte
l
li
gen
t
m
et
h
ods
i
ncl
u
di
n
g
f
uzz
y
l
o
g
i
c
a
nd
a
r
t
i
f
i
c
i
a
l
ne
ural
n
e
t
w
o
r
k
(
A
N
N
)
ha
ve
b
ee
n
me
nt
io
ne
d
i
n
t
h
e
l
i
t
e
r
a
t
u
r
e
.
T
h
e
f
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
s
a
r
e
w
i
d
e
l
y
u
s
e
d
for
the
MP
P
trac
kin
g
[
7].
They
a
r
e
i
n
d
epe
nde
nt
o
f
p
r
o
c
e
s
s
m
o
d
e
l
,
w
h
i
c
h
p
r
e
s
e
n
t
a
n
a
b
i
l
i
t
y
t
o
a
p
p
r
e
h
e
n
d
t
h
e
p
r
o
ble
m
s
of
n
o
n
li
nea
r
it
y
a
nd
ha
ve
r
ob
u
s
t
perform
ance
t
o
t
h
e a
t
m
o
sphe
r
i
c c
o
n
d
iti
on
s
c
h
an
ges.
T
he tw
o
m
os
t
impor
ta
nt t
ype
s of fuz
z
y
in
f
e
r
enc
e
m
eth
o
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st, Vol. 10,
N
o.
1, Mar
c
h 2
0
1
9
:
42
3 –
43
2
42
4
are
Mam
d
an
i’s
fuzz
y
in
fer
e
n
c
e
m
e
th
od
a
n
d
T-S
m
e
thod.
I
n
t
h
is
s
t
ud
y,
t
he
M
P
P
T
i
s
d
evel
o
p
ed
u
si
ng
t
hre
e
d
i
f
f
e
r
e
n
t
t
e
c
h
n
i
q
u
e
s
t
o
a
s
s
e
s
s
t
h
e
i
r
p
e
r
f
o
r
m
a
n
c
e
s
.
T
h
i
s
p
a
p
e
r
i
s
organ
i
z
e
d
a
s
f
o
l
l
ow
s.
T
he
d
e
s
c
r
ip
t
i
on
a
n
d
mode
l
i
ng
o
f
t
h
e
P
V
syst
e
m
i
s
me
nt
i
o
ned
i
n
s
e
c
t
i
on
2.
M
P
P
T
based
o
n
P
e
rturb
a
nd
o
b
se
rve
(P
&O
)
algor
ithm
i
s
d
e
s
c
r
i
b
e
d
i
n
se
ct
io
n
3
.
M
P
P
T
b
a
se
d
on
f
u
z
zy
l
og
i
c
i
s
ex
pl
ai
n
e
d
i
n
se
cti
o
n
4.
T
he
s
im
ulat
ion
a
n
d
r
e
su
lts
ana
l
ys
is ar
e
d
i
s
cusse
d
in sec
t
i
on 5.
F
i
n
a
l
ly,
the
conc
l
u
s
i
on
i
s
e
xp
osed
i
n
se
cti
o
n 6.
2.
DESCRIPTIO
N
AN
D MODE
LING OF
THE PV
SYS
TE
M
The
b
l
ock d
i
a
g
ram
of
t
he pr
o
pos
ed s
t
a
n
d
a
l
o
n
e
P
V
s
ystem
a
s
s
how
n
in F
i
gure
1.
T
he s
ys
t
e
m cons
is
t
s
of
a
P
V
a
rra
y
(BP
S
o
la
r
SX
150S
),
a
M
P
P
T
contro
ller
c
o
mbi
n
e
d
t
o
a
D
C
-
D
C
c
o
n
v
e
r
t
e
r
(
B
o
o
s
t
)
a
n
d
a
load (
resist
a
n
ce)
.
F
i
gure
1.
B
l
o
c
k
d
ia
gram
of th
e
gl
o
b
a
l
P
V
syst
e
m
The
G
a
n
d
T
a
r
e
in
c
h
a
r
g
e
of
t
he
w
orki
n
g
p
o
i
nt
o
f
P
V
s
ys
t
e
m
at
the
MP
P
[1
3]
,
[1
4]
.
The
ce
ll
curr
ent,
I
,
w
h
ich r
e
pre
s
ent t
h
e
ma
t
h
e
m
a
tic
al
m
odel o
f
t
he PV
c
e
ll c
a
n be
e
xp
r
e
ss a
s
[
1
5
]:
sh
s
T
K
.
A
IR
V
(
q
0
ph
R
IR
V
1
e
I
I
I
c
s
(
1
)
Wh
e
r
e
Iph
i
s
l
ig
ht
-g
en
era
t
e
d
c
e
l
l
c
u
rre
n
t
(
A),
I
0
i
s
cell
reverse
saturation
current
(
A),
q
is
e
l
e
ctr
o
nic
cha
r
ge,
A
i
s
i
deal
i
t
y
fac
t
or
,
K
c
i
s
Bo
ltzm
a
nn’s
c
o
n
s
ta
n
t
,
a
nd
T
i
s
ce
ll
t
e
m
p
era
t
ur
e
(K
)
.
A
cc
ordi
ng
to
t
he
equa
t
i
o
n
a
bo
v
e
,
the
o
u
t
p
ut
p
ow
e
r
v
ar
i
e
s
ac
c
o
rd
in
g
to
G
(
irra
di
a
nce)
a
n
d
T
.
The
m
a
the
m
atica
l
m
ode
l
ca
n
be
use
d
t
o
de
ter
m
in
e
t
h
e
ce
l
l
o
u
t
pu
t
c
u
rr
ent.
F
i
gur
es
b
e
l
o
w
s
how
t
he
e
le
ctrica
l
c
h
ara
c
teris
tic
s
u
nde
r
var
y
i
n
g
w
e
a
t
he
r
G
and
T of the
B
P
S
o
la
r S
X
150S
ac
c
ord
i
n
g
i
ts c
ha
ra
cter
isti
cs as
shows
in Table
1
.
Tabl
e 1
.
PV
mo
dul
e ch
a
r
ac
t
e
ri
st
i
c
s
PV
m
odul
e
B
P
S
ola
r
S
X
150S
Ma
xi
m
u
m
po
we
r
(P
m
a
x)
1
50
W
V
o
lta
g
e
at
P
m
a
x
(Vm
p)
34.
5
V
C
u
rr
e
n
t a
t
P
m
a
x
(
I
m
p
)
4.
35
A
O
p
e
n
c
ir
c
u
it
vol
t
a
ge
(
V
o
c
)
43.
5
V
Short
c
i
r
c
uit c
u
rrent
(Isc
)
4
.
75
A
Tem
p
e
r
a
t
ure
c
o
e
f
f
i
c
i
e
n
t
of
I
sc
0
.
065
±
0
.
0
15%/°C
Tem
p
e
r
a
t
ure
c
o
e
f
f
i
c
i
e
n
t
of
V
o
c
-
16
0±20
m
V
/
°
C
T
e
m
p
e
r
a
t
ur
e
c
o
e
f
fic
i
e
n
t
of
powe
r
-
0.
5±0.
05%
/°C
N
O
C
T
47±2°C
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
El
e
c
&
D
ri S
yst
I
S
S
N
:
2088-
86
94
Max
i
m
u
m
po
w
e
r c
o
n
t
ro
l f
o
r p
h
o
t
ovo
l
ta
i
c
sys
t
em
usin
g
inte
lli
ge
nt s
t
ra
t
e
g
i
e
s
…
(
Mo
h
a
m
m
e
d
Slim
i)
42
5
A
t
c
o
n
s
t
a
n
t
t
e
m
p
e
r
a
t
u
r
e
2
5
°
C
s
h
o
w
s
i
n
F
i
g
u
r
e
3
a
n
d
F
i
g
u
r
e
5
,
t
h
e
incre
a
s
e
i
n
i
r
r
adia
nc
e
va
lue
leads
to
a
n
incre
a
se i
n
m
a
xim
u
m
p
o
w
er
a
nd
a
m
i
n
o
r
incre
a
se i
n
ope
n
c
i
rc
u
i
t
v
o
l
ta
ge,
w
h
i
l
e
th
e
shor
t
c
i
rcu
i
t
c
u
rrent
varie
s
s
i
g
n
i
fica
nt
l
y
.
Th
is
i
m
p
lie
s
tha
t
t
he
o
pt
i
m
al
p
ow
er
g
e
n
er
a
t
or
i
s
a
l
m
o
st
p
r
opor
ti
ona
l
to
t
he
i
l
l
u
min
a
ti
o
n
.
Wi
t
h
a
c
ons
ta
n
t
i
r
r
ad
iat
i
o
n
is
s
how
n
i
n
F
igur
e
2
an
d
F
i
gure
4,
the o
p
en
c
ir
cui
t
v
o
l
tag
e
d
e
c
r
ea
ses
no
ta
bl
y
w
ith
incre
a
s
i
ng
t
e
m
pe
rat
u
re
a
n
d
t
he
m
a
x
i
m
um
pow
er
t
o
o
.
F
o
r
t
h
i
s
c
ase
,
w
e
c
a
n
d
e
duce
tha
t
t
he
v
o
l
ta
ge
c
han
g
e
s
sign
ifica
n
tl
y
w
h
i
l
e
t
h
e
c
u
rr
ent
r
e
m
a
ins
c
o
n
s
t
a
nt.
T
o
get
a
m
axi
m
u
m pow
er
,
it i
s
imp
ortan
t
t
o
w
o
rk i
n
t
h
e
are
a
of
M
P
P
o
f
the
P
V
g
ener
ator.
In
t
he
n
e
x
t
se
ctio
ns,
w
e
w
ill
c
ompa
re
c
on
v
e
nt
i
ona
l
a
n
d
i
n
te
l
lige
n
t
strat
e
gie
s
w
h
ic
h tra
c
k
th
e
MP
P
of the P
V
ge
nera
tor.
BP S
X
1
5
0
S
Ph
ot
ovolta
ic
Mod
u
l
e
I-V
F
i
gure
2.
I-V
c
ur
ves a
t
v
ar
io
u
s
te
m
per
a
tures
F
i
gure
3.
I
-V
c
urv
es a
t
v
a
rious rad
i
a
ti
on
s
F
i
gure
4.
P
-
V
c
urves a
t
var
io
us t
e
m
pe
rat
u
re
s
F
i
gure
5.
P
-V
cur
v
es a
t
vari
o
u
s r
a
dia
tio
ns
3.
MPPT BASE
D
O
N
P&O ALG
O
RIT
H
M
P
&
O
algori
t
h
m
a
r
e
w
idely
use
d
i
n
MP
P
T
b
eca
use
o
f
t
h
e
ir
s
imple
s
t
r
u
c
t
u
r
e
a
n
d
t
h
e
i
r
f
e
w
m
e
a
s
u
r
e
d
p
a
r
a
m
e
t
e
r
s
w
h
i
c
h
a
r
e
r
e
q
u
i
r
e
d
.
A
s
i
t
s
n
a
m
e
i
n
d
i
c
a
t
e
s
,
i
t
i
s
b
a
s
e
d
o
n
the
s
y
s
t
em
p
ert
u
rba
t
i
o
n
b
y
i
nc
rea
s
in
g
or
dec
r
ea
si
ng
of
V
P
V
,
then
obs
er
ving
the
e
f
fe
ct
o
n
t
h
e
o
u
t
p
ut
p
ow
e
r
of
t
h
e
p
a
n
e
l
.
If
t
he
c
ur
rent
v
a
l
ue
o
f
th
e
pow
er
P
P
V
(k)
of
t
he
p
a
n
e
l
i
s
gr
eate
r
t
ha
n
t
h
e
p
r
e
v
i
o
us
v
a
l
ue
P
P
V
(
k-1)
t
hen
t
h
e
d
i
r
ect
i
on
o
f
p
e
r
t
u
rba
t
io
n
is
mai
n
t
a
i
n
e
d
o
the
r
wi
se
i
t
i
s
r
everse
d
.
W
ith
t
his
alg
o
ri
th
m
th
e
o
p
er
a
t
i
ng
v
o
lta
ge
V
P
V
i
s
pe
r
t
ur
bed
a
t
eac
h
c
y
cle
o
f
t
h
e
M
PPT.
W
h
e
n
t
h
e
M
P
P
i
s
r
ea
ch
ed
,
VPV
o
s
c
i
ll
at
e
s
a
ro
und
t
h
e
m
a
x
i
m
u
m
p
o
w
e
r
p
o
i
n
t
w
h
i
c
h
c
a
u
s
e
s
syste
m
p
ow
er
l
o
sses,
d
e
p
e
n
d
i
n
g
o
n
t
he
s
te
p
w
i
d
t
h
of
a
s
imple
pe
rtur
ba
t
i
o
n
.
I
f
t
he
s
te
p
w
i
d
t
h
is
l
ar
g
e
,
th
e
P
&
O
a
l
g
o
r
i
t
h
m
w
i
l
l
r
es
po
nd
quic
k
ly
t
o
ra
pid
c
h
a
nges
i
n
oper
a
t
i
n
g
co
nd
iti
o
n
s
w
i
th
i
nc
rea
s
i
n
g
osc
i
l
l
a
t
io
n
arou
nd
t
he
M
P
P
under
s
t
a
b
l
e
o
r
sl
ow
l
y
c
ha
n
g
i
n
g
c
o
n
d
iti
o
n
s.
I
f
t
he
s
t
e
p
w
i
d
t
h
is
s
m
a
ller
the
osc
i
l
l
a
t
i
o
n
arou
nd
t
h
e
M
P
P
w
ill
be
r
educ
e
d
b
u
t
t
he
s
ys
tem
w
i
l
l
r
e
s
p
ond
s
l
ow
ly
t
o
su
dde
n
c
h
ange
s
i
n
a
tm
o
s
phe
ri
c
con
d
i
t
i
on
s [1
6],
[17].
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
0
8
8
-
86
94
I
nt
J
P
ow
E
l
e
c
&
Dr
i
S
y
st,
Vol.
10,
N
o.
1
,
Mar
c
h
2
0
1
9
:
42
3
–
432
42
6
4.
M
PPT
B
AS
ED
ON FUZZ
Y
LOGIC
F
u
zzy
l
o
g
ic
co
n
tr
ol
ler
(F
LC
) is a
no
n
l
i
ne
ar
c
on
tro
l
m
eth
od.
H
en
c
e
,
it
c
a
n
b
e
easil
y
a
ppl
ie
d
for
no
n
l
i
n
ea
r
c
h
ar
a
c
ter
i
s
t
ics
of
P
V
s
yst
e
m
to
t
r
a
c
k
m
axim
um
pow
er
poi
nt.
F
L
C
i
s
oper
a
t
e
d
u
s
i
n
g
m
e
mber
sh
ip
f
u
n
c
t
io
ns
in
stea
d
of
m
at
he
ma
t
i
ca
l
m
o
d
e
l
[
13]
.
4.
1.
Fu
zz
y MPPT b
ased
on
mamd
ani’s in
feren
ce
Con
v
e
n
ti
ona
l
m
e
tho
d
s
of
t
r
a
c
k
in
g
t
h
e
op
t
i
m
a
l
p
o
i
nt
o
f
o
p
er
at
i
o
n
h
a
v
e
show
n
t
h
e
i
r
l
i
m
its
t
o
s
u
dde
n
c
h
an
ges
of
w
eathe
r
a
n
d
t
h
e
l
o
ad
c
on
nec
t
e
d
t
o
the
pa
ne
l,
s
ever
al
m
eth
o
d
s
ha
ve
e
m
e
r
g
e
d
t
o
tr
y
t
o
a
l
l
e
via
t
e
the
s
e
sh
or
t
c
omin
gs
a
nd
impr
o
v
e
t
h
e
oper
a
tio
n
o
f
t
hese
g
e
n
er
a
t
o
r
s.
T
he
a
p
p
roac
h
of
A
rti
f
icia
l
In
te
ll
ige
n
ce
i
n
t
h
e
c
a
s
e
o
f
f
u
z
z
y
l
o
g
i
c
i
s
i
m
p
l
e
m
e
n
t
e
d
t
o
i
m
p
r
o
v
e
c
o
n
t
r
o
l
p
e
r
f
o
r
m
anc
e
a
nd
t
h
e
p
u
r
s
u
i
t
of
m
aximum
pow
e
r
p
o
in
t
by
s
i
m
ula
t
ion
a
n
d
mo
de
l
i
ng
o
f
a
c
o
n
t
ro
ll
e
r
b
ase
d
on
f
u
zzy
l
o
g
ic
[
17]
.
The
adve
nt
o
f
m
i
c
r
oc
on
tr
ol
ler
s
ha
s
e
n
a
b
led
t
h
e
sprea
d
o
f
fu
zzy
c
o
n
tr
ol
i
n
t
h
e
p
u
r
s
u
i
t
of
o
p
tim
a
l
poi
n
t
d
u
r
ing
t
h
e
l
a
st
d
ec
ad
e.
T
h
e
f
u
zzy
c
o
n
t
r
o
ller
has
the
f
o
l
l
ow
i
ng
t
h
r
e
e
bloc
ks:
F
u
zzi
f
i
ca
t
i
on
of
i
n
p
ut
v
ari
a
bl
es
b
y
usi
n
g
th
e
t
r
ap
ezo
id
al
f
u
n
c
t
ion
s
,
t
h
e
n
t
h
e
s
e
f
u
z
z
i
f
i
e
d
v
a
r
i
a
b
l
e
s
a
r
e
c
o
m
p
a
r
e
d
w
i
t
h
p
r
e
-
d
e
f
i
n
e
d
pa
cka
g
es
t
o
de
ter
m
ine
t
h
e
a
ppr
opr
ia
te
r
e
s
ponse
.
A
nd
f
i
na
l
l
y,
t
he
d
e
f
uzz
i
f
i
ca
t
i
o
n
c
o
nve
r
t
s
the
ob
ta
in
ed
a
r
e
a
ac
c
or
d
i
ng
t
o
f
i
r
e
d
r
u
le
s
to
c
r
i
s
p
v
a
l
ue
w
hic
h
c
o
n
t
r
o
l
s
t
he
p
la
nt.
Ma
mda
n
i
’
s
fuz
z
y
in
fe
r
e
n
c
e
m
e
th
od
i
s
t
he
m
os
t
c
o
mmo
n
l
y
se
en
f
u
zzy
m
et
hodo
log
y
.
M
a
m
d
a
n
i
’
s
m
e
t
h
o
d
w
a
s
a
m
o
n
g
t
h
e
f
i
r
s
t
c
o
n
t
r
o
l
s
y
s
t
e
m
s
b
u
i
l
t
u
s
i
n
g
fu
zz
y
se
t
t
h
eor
y
.
I
t
w
as
p
r
o
p
o
s
e
d
by
M
a
md
an
i
(1975
)
a
s
a
n
a
t
t
e
mp
t
t
o
c
on
t
r
ol
a
s
t
e
a
m
e
n
g
i
n
e
an
d
b
o
il
er
c
om
bina
t
i
o
n
by
syn
t
he
siz
i
n
g
a
s
et
o
f
li
n
g
u
i
s
t
ic
c
o
n
tr
ol
r
u
l
es
o
bta
i
n
e
d
f
r
o
m
e
xper
i
enc
e
d
huma
n
ope
r
a
t
or
s.
M
a
m
da
n
i
’
s
e
ff
or
t
w
a
s
ba
se
d
o
n
Z
a
d
eh’
s
(
1973)
p
a
p
er
o
n
f
u
zz
y
a
l
gor
it
hms
f
o
r
com
p
l
e
x
sy
stem
s
an
d
dec
i
s
i
o
n
p
ro
ce
sses.
I
n
t
his
wor
k
,
ea
ch
l
in
gu
i
s
t
i
c
va
r
i
a
b
le
o
f
t
h
e
f
u
zz
y
MP
P
T
c
on
tr
o
l
l
e
r
has
f
i
ve
l
i
n
gu
ist
i
c
v
a
lue
s:
N
B
(N
egat
i
v
e
Big),
NS
(
Ne
gativ
e
Sm
all),
Z
(
Z
ero
A
p
pr
o
x
i
m
a
tely),
P
S
(Pos
iti
ve
S
m
a
ll),
P
B
(
Posi
t
i
v
e
B
i
g
)
.
T
he
t
w
o
F
LC
i
n
p
u
t
va
r
i
able
s
a
r
e
the
e
r
r
o
r
E
a
nd
cha
n
ge
o
f
er
r
o
r
C
E
a
t
sampled
t
i
m
e
s
k
def
i
ne
d
b
y
:
)
1
(
)
(
)
1
(
)
(
)
(
k
V
k
V
k
P
k
P
k
E
(
2
)
(3
)
Whe
r
e
P
(
k)
i
s
the
insta
n
t
a
n
e
ou
s
p
o
w
e
r
of
t
he
P
V
gener
a
tor
.
T
he
i
n
put
E
(
k
)
sh
ow
s
if
t
he
l
o
a
d
ope
ra
ti
o
n
p
oin
t
a
t
the
ins
t
a
n
t
k
i
s
l
oca
t
e
d
o
n
t
h
e
le
ft
o
r
on
t
he
r
ig
ht
o
f
t
h
e
m
a
xim
u
m
po
w
e
r
poi
nt
o
n
t
h
e
P
V
c
h
ara
c
teris
t
ic,
whi
l
e
the
i
n
pu
t
C
E
(k)
e
xpre
sse
s
t
h
e
m
o
v
i
n
g
d
ir
e
c
t
i
o
n
o
f
t
his
p
o
i
n
t
.
T
he
f
uz
z
y
i
nfer
en
ce
i
s
c
a
r
r
i
e
d
ou
t
b
y
u
s
i
n
g
Mam
da
n
i
’
s
i
n
f
e
r
enc
e
show
s in
T
a
b
l
e
2
,
a
n
d
the
def
u
z
z
if
ica
t
i
o
n
use
s
t
he ce
n
tr
e
o
f
g
r
a
vit
y
to
c
omp
u
t
e
t
h
e
out
p
u
t
o
f
t
h
i
s
F
L
C
w
h
ich
is
t
he
d
u
t
y
c
y
cl
e:
n
1
j
j
j
n
1
j
j
)
d
(
d
d
d
(
4
)
Tab
l
e
2.
F
uzz
y
r
ul
e
s
tab
le
o
f
m
a
m
d
ani’s
i
n
f
e
re
nce
E/
CE
N
B
N
S
Z
P
S
P
B
N
B
P
B
P
B
P
S
PB
P
B
NS
P
S
P
S
P
S
P
S
P
B
Z
NS
N
S
Z
P
S
P
S
PS
N
B
N
S
N
S
N
S
NB
PB
N
B
NB
N
S
NB
N
B
4.
2.
Fu
zz
y MPPT b
ased
on
ta
k
a
gi
-
s
u
g
en
o’s inf
ere
nc
e
Th
is
m
eth
o
d
w
as
i
ntr
o
d
u
ced
by
S
uge
no
(
1
9
85)
.
The
ma
in
d
i
ffe
r
e
nc
e
be
t
w
e
e
n
Mam
d
a
n
i
an
d
Ta
ka
g
i
S
ugen
o
i
s
t
h
a
t
t
he
T
S
o
u
t
p
u
t
m
e
m
be
r
s
hip
f
unc
t
i
on
s
ar
e
e
ithe
r
l
i
ne
ar
f
unc
t
i
o
n
o
r
co
ns
tan
t
.
A
l
s
o
t
he
d
if
f
e
r
e
nc
e
lie
s
in
t
he
c
ons
e
que
nce
s
o
f
t
h
e
i
r
fuz
z
y
r
u
les,
a
nd
de
f
u
zz
i
f
ic
at
i
o
n
pr
oc
e
dur
e
s
.
A
typ
i
ca
l
r
u
le
i
n
a
S
ugeno
f
u
z
z
y
m
odel
ha
s
t
h
e
f
o
r
m
:
I
F
I
nput
1
x
A
N
D
I
npu
t
2
y
,
T
HEN Ou
tp
ut is z
a
x
+
by
+
c
.
)
1
(
)
(
)
(
k
E
k
E
k
CE
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
P
o
w
Elec
&
D
r
i
S
y
st
I
S
S
N
:
2088-
86
94
Max
i
mum
po
we
r con
t
ro
l f
o
r p
h
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t
ovo
l
t
a
ic
sys
t
em
usi
n
g in
te
l
l
i
g
e
n
t s
t
ra
te
g
i
e
s
…(M
o
ham
med Sl
imi)
42
7
F
o
r
a
zer
o-
or
de
r
S
uge
n
o
m
o
d
el,
t
h
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h
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r
u
l
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o
r
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amp
l
e,
f
o
r
a
n
AND
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u
l
e
w
ith
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put
1
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n
pu
t
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h
e
firin
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streng
th
i
s:
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),
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2
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x
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And
M
ethod
w
i
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h
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F
1
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ar
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ersh
ip
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un
ctio
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o
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uts
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h
e
f
i
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l
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h
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t
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ver
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ge
o
f
a
ll
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u
le
o
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t
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ts,
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ompu
te
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5)
:
(5
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I
n
t
h
i
s
w
o
r
k
,
t
h
e
f
u
z
z
y
M
P
P
T
b
a
s
e
d
o
n
S
u
g
e
n
o
’
s
i
n
f
e
r
e
n
c
e
h
a
s
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e
en
i
mp
l
e
me
nt
ed
a
c
c
o
r
di
ng
t
o
t
h
e
fu
zzy
ru
le
t
a
b
le b
elo
w
.
T
a
b
l
e 3.
F
uzzy
r
ules
t
a
b
l
e
of
Suge
n
o
’s in
f
er
ence
E/
C
E
N
B
N
S
P
S
PB
NB
P
B
P
B
N
B
N
B
N
S
PS
P
S
N
S
N
S
PS
PS
P
S
N
S
N
S
P
B
N
B
N
S
P
S
PB
The
tw
o
i
n
pu
ts
E
r
r
o
r
A
nd
change
o
f
er
r
o
r
have
t
he
s
am
e
mem
b
er
sh
i
p
f
un
c
tio
ns
a
s
show
n
in
F
ig
ur
e
6:
F
i
gur
e
6.
I
npu
t
e
r
r
o
r
and
chan
ge
o
f
er
r
o
r
m
e
m
b
er
ship
f
u
n
c
t
io
ns
A
nd
t
h
e
ou
tpu
t
’
s
s
ing
l
e
t
o
n
s
a
r
e
r
e
spe
c
tive
l
y
as
b
e
l
ow
:
N
B
-0.
08,
N
S
-
0
.
04,
P
S
1
, PB
2.
5.
S
I
MULAT
I
O
N
AND RESULTS
A
NALYSIS
B
P
S
olar
S
X
150S
P
V
modul
e
i
s
c
hose
n
f
or
t
he
s
imula
tio
n
w
h
ic
h
h
as
t
he
c
ha
r
a
c
t
er
is
t
i
c
s
a
bo
ve
.
The
simu
la
ti
o
n
ha
s
bee
n
d
one
und
e
r
M
a
t
l
a
b
/
S
i
m
lin
k
as
s
how
n
in
F
i
g
ur
e
7:
The
sim
u
la
te
d
system
h
a
s
f
our
m
a
i
n
bl
oc
ks
:
the
P
V
m
odu
le
(
B
P
S
o
l
a
r
S
X
150S
)
,
t
he
M
P
P
T
c
o
n
t
r
o
ller
w
h
ic
h
is
b
a
s
ed
on
P
&
O
,
M
am
dani
’
s
,
and
suge
no’
s
m
odel
a
t
e
ach
s
imu
l
a
t
i
o
n,
P
W
M
g
e
n
era
t
or
,
an
d
D
C
-
D
C
bo
os
t
c
o
n
v
er
ter
.
T
h
e
c
ompa
r
i
son
i
s
d
o
n
e
unde
r
G
10
00
KW/
m2
a
n
d
T
25
°
C
.
N
i
i
N
i
i
i
w
z
w
output
Final
1
1
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st, Vol. 10,
N
o.
1, Mar
c
h 2
0
1
9
:
42
3 –
43
2
42
8
F
i
gure
7.
L
ayo
u
t o
f
t
he
sim
ul
a
t
e
d
s
yst
e
m
5.1.
MPPT
base
d
on
P
&
O
algorit
h
m
res
u
lt
s
O
n
F
ig
ure
8
th
e
o
b
ta
i
n
ed
r
es
ul
ts
o
f
the
P
&
O
alg
o
ri
t
h
m
sh
ow
t
hat
t
he
P
V
vo
l
t
a
g
e
i
s
e
qua
l
t
o
3
4
V
and
the
o
u
t
p
u
t
pow
er
on F
i
g
u
r
e 8 (c) pre
s
ent
s
a
s
ma
l
l
overs
ho
o
t
.
(a
)
(b
)
(c
)
(d
)
F
i
gure
8.
P
&O
a
lgor
it
hm
r
esult
s
:
(a) P
V
’s volta
ge,
(b)
P
V
’s c
ur
rent,
(c
) P
V
’s
pow
er, (d) P
WM sig
na
l
0
0.
02
0.
04
0.
06
0.
0
8
0.
1
34
36
38
40
42
44
t(
s
)
Vp
v
(
V
)
Pa
n
d
O
0
0.
0
2
0.
04
0.
0
6
0.
08
0.
1
0
1
2
3
4
5
t(
s
)
Ip
v
(
A
)
P
andO
0
0.
02
0.
04
0.
06
0.
08
0.
1
0
50
100
150
t(
s
)
Ppv
(
W
)
P
andO
0
1
2
x
1
0
-4
0
0.
2
0.
4
0.
6
0.
8
1
t(
s)
PW
M
P
andO
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
El
e
c
&
D
ri S
yst
I
S
S
N
:
2088-
86
94
Max
i
m
u
m
po
w
e
r c
o
n
t
ro
l f
o
r p
h
o
t
ovo
l
ta
i
c
sys
t
em
usin
g
inte
lli
ge
nt s
t
ra
t
e
g
i
e
s
…
(
Mo
h
a
m
m
e
d
Slim
i)
42
9
5.2.
Fu
z
z
y
MPPT
ba
s
ed o
n ma
m
d
a
n
i
’
s
i
n
fer
e
nc
e re
s
u
l
t
s
Ma
mda
n
i’s
in
fere
nce
r
e
sults
a
re
d
e
p
i
c
te
d
o
n
F
ig
ure
9.
W
e
ca
n
n
o
tice
t
h
a
t
t
he
o
u
t
pu
t
po
w
e
r
is
n
e
a
rly
w
itho
u
t
ove
rs
h
o
o
t
a
n
d
the
P
V
vol
t
a
ge
p
resen
t
s a
sm
all un
de
rsho
o
t.
(a
)
(b
)
(c
)
(d
)
F
i
gure
9. Ma
m
da
n’s i
n
fe
renc
e
r
e
sul
t
s
:
a
) P
V
’s vo
lta
ge
, b)
P
V
’s
cur
r
ent
,
c)
P
V
’s pow
er, d)
PWM
si
gnal
5.3.
Fu
z
z
y
MPPT based on su
ge
no’
s
in
f
erence results
C
o
m
p
a
r
ed
t
o
abo
v
e
res
u
l
t
s,
t
he
o
utp
u
t
p
o
w
er
o
b
t
ai
ne
d
us
in
g
su
ge
n
o
’s
i
nfere
n
ce
F
ig
ur
e
1
0
(
c)
i
s
wi
t
h
out
o
v
e
rsho
ot
a
nd
t
h
e
PWM
si
g
n
a
l
F
i
gu
re 1
0
(d
) s
h
ows t
h
e ef
fi
c
i
ency
o
f
t
h
i
s
me
t
ho
d
.
(a
)
(b
)
0
0.
0
2
0.
04
0.
0
6
0.
0
8
0.
1
34
36
38
40
42
44
t(
s
)
Vp
v
(
V)
F
u
z
zy
M
a
m
d
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n
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0
2
0.
04
0.
06
0.
08
0.
1
0
1
2
3
4
5
t(
s
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v
(
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F
u
z
z
y
Ma
md
a
n
i
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02
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04
0.
0
6
0.
0
8
0.
1
0
50
100
150
t(
s
)
Pp
v
(
W
)
F
u
zzy
M
a
m
d
a
n
i
6.
7
6.
8
6.
9
7
x 1
0
-3
0
0.
2
0.
4
0.
6
0.
8
1
t(
s
)
PW
M
F
u
zz
y
M
a
m
d
a
n
i
0
0.
0
2
0.
04
0.
06
0.
08
0.
1
34
36
38
40
42
44
t(
s
)
Vp
v
(
V)
F
u
z
zy
S
u
g
e
n
o
0
0.
02
0.
04
0.
06
0.
08
0.
1
0
1
2
3
4
5
t(
s)
Ip
v(
A
)
F
u
zzy
S
u
g
e
n
o
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st, Vol. 10,
N
o.
1, Mar
c
h 2
0
1
9
:
42
3 –
43
2
43
0
(c
)
(d
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F
i
gur
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0
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S
u
g
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no’s i
n
fe
renc
e
r
e
sult
s
:
(
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V’
s vol
t
a
ge,
(b) P
V
’s cur
rent, (
c)
P
V
’
s
p
o
w
e
r, (d) PWM signal
The
com
p
ari
s
o
n
o
f
the
P
V
’s
pow
ers
is
p
rese
nte
d
on
F
i
gur
e
11.
O
n
F
igure
1
1
(
a
)
w
e
c
a
n
no
t
i
c
e
t
h
r
o
u
g
h
t
h
e
z
o
o
m
t
h
a
t
t
h
e
M
P
P
T
b
a
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d
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n
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u
g
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n
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c
e
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l
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ve
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a
m
a
x
i
m
um
p
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r
i
n
s
t
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dy
s
ta
te
zone
a
nd
t
he
i
nt
e
l
l
i
ge
n
t
c
on
t
r
o
ller
s
a
re
m
ore
perf
orm
a
nce
t
h
a
n
th
e
co
nv
ent
i
on
al
c
o
n
t
roll
e
r
b
as
e
d
o
n
P
&
O
algori
t
h
m
.
The
Ta
b
l
e
4 sh
ow
s
t
h
e
n
u
m
e
rica
l va
l
u
es
o
f t
h
e
P
V
pow
er
for
e
a
c
h
strat
egy.
(a
)
(b
)
F
i
gure
1
1
.
(a
)
P
V
’s pow
e
r
s for e
ach
m
e
t
ho
d
,
(
b) z
oom
o
f P
V
’s po
we
r
s
Ta
ble
4.
N
umerica
l
v
a
l
ue
s
of c
on
t
r
ol
ler
s
’
perform
a
nc
es
P
&
O a
l
gorithm
Ma
m
d
a
n
i’s
infe
re
n
c
e
Suge
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re
nc
e
R
i
s
e
Ti
m
e
(
s)
0
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0056
0.
0050
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0050
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t
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m
e
(
s
)
0.
0075
0.
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e
ttl
ingM
in
(
W
)
134.
06
05
134.
95
13
135.
27
11
S
e
tt
lingMa
x
(
W)
149.
81
05
149.
79
50
149.
81
05
O
v
e
r
shoot
0
.
9057
0.
2234
0
.
0003
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nde
rshoot
0
0
0
P
e
a
k
(
W
)
149.
81
05
149.
76
50
149.
81
05
P
e
a
k
T
i
m
e
(
s)
0
.
0092
0.
0068
0
.
0293
6.
L
O
AD
CHAN
G
We
h
a
v
e
incr
e
a
sed
t
h
e
loa
d
u
p
t
o
5
0%
t
o
eva
l
ua
te
t
he
r
ob
ust
n
ess
o
f
each
strategy.
The
obtained
resul
t
s
a
c
c
o
rd
i
ng to F
i
gure
1
2
(a) and (b) s
h
ow
t
hat
F
L
Cs ar
e
m
ore
r
o
bus
t tha
n
the P
&O
a
lgor
it
hm
b
e
c
a
use a
t
0.05s w
he
n t
h
e
syste
m
i
s
l
o
a
d
ed,
they a
re
m
or
e stab
le
th
a
n
P
&
O
algori
t
h
m
.
0
0.
05
0.
1
0
50
100
150
t(
s
)
Pp
v
(
W
)
F
u
zzy
S
ugeno
6.
7
6.
8
6.
9
7
x 1
0
-3
0
0.
2
0.
4
0.
6
0.
8
1
t(
s)
PW
M
F
u
zz
y
S
u
g
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o
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
El
e
c
&
D
ri S
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I
S
S
N
:
2088-
86
94
Max
i
m
u
m
po
w
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o
n
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ro
l f
o
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h
o
t
ovo
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ta
i
c
sys
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em
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g
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lli
ge
nt s
t
ra
t
e
g
i
e
s
…
(
Mo
h
a
m
m
e
d
Slim
i)
43
1
(a)
(b)
F
i
gure
1
2
.
load
c
hange
r
esu
l
t
s
:
(a) P
V
’s pow
e
r
s for e
ach meth
o
d
,
(
b
) z
oom
o
f P
V
’s pow
ers
7.
CONCL
U
S
ION
The
P
V
a
rray
ha
s
a
m
a
x
i
mu
m
pow
er
p
o
i
nt
(
MP
P
)
w
hich
v
ar
i
e
s
w
i
t
h
t
h
e
c
h
ang
e
o
f
so
lar
irradiation
and
ce
ll
tem
p
e
r
a
t
ure.
T
he
c
o
n
tr
ol
lers
b
y
fu
zz
y
lo
gic
c
a
n
p
ro
vi
d
e
mor
e
e
ffec
t
i
ve
r
esp
o
n
se
t
ha
n
the
t
r
adi
tio
na
l
con
t
ro
l
l
er for t
he
n
on
l
i
near
s
y
s
tem
s
,
be
ca
use
ther
e i
s
mor
e
fle
x
i
bil
i
t
y
.
T
he
y
a
r
e robus
t
a
nd MP
P
w
a
s
ob
t
a
ine
d
in
s
h
o
r
t
e
r
tim
e
r
uns
a
s
i
s
s
how
n
on
T
ab
l
e
4
.
The
F
L
C
ba
se
d
on
S
ug
e
n
o
’
s
i
n
f
e
re
nce
p
r
es
ent
s
c
ert
a
in
perform
ance
s com
p
ar
ed t
o Ma
mda
n
i
’
s
i
n
fere
nce
in ter
ms of
sett
li
ng
m
ax
,
o
v
e
r
s
h
oot
a
n
d
p
e
a
k
v
alu
e
.
REFE
RENCE
[1]
T.
E
sram
a
n
d
P
.
L.
C
hapm
an,
“
C
om
pariso
n
o
f
p
h
o
t
o
v
o
ltaic
a
rray
m
axi
m
u
m
pow
er
p
oi
nt
t
rackin
g
tech
ni
qu
es,”
IEEE Transac
t
i
ons
on
Energy Co
nve
r
si
on
22
(2); pp
.
4
39
–4
49,
2007
.
[2]
F
.
D
incer
a
n
d
M
.
E.
M
eral,
“Cri
ti
cal
f
acto
r
s
that
a
ff
ecti
n
g
e
f
f
iciency
of
s
o
l
ar
cells,”
Smart Grid and
R
e
newab
l
e
Energy
1
(1)
, pp
.
47
–
5
0
, 2
01
0
.
[3]
G.
G
radit
i
,
G
.
A
d
i
nolf
i
,
and
G
.
M
.
Ti
na,
“P
hoto
voltai
c
o
ptimize
r
b
o
o
s
t
co
nv
ert
e
rs:
T
e
m
p
eratu
r
e
inf
l
uen
ce
an
d
elect
ro-th
e
rm
al d
esi
gn,
”
Applied
Energy
1
15
(c),
1
40
–1
50,
2
0
1
4
.
[4]
Gu
dimetla
R
am
esh
,
K
ari
Vasav
i
,
a
n
d
S
.
L
aks
h
mi
S
i
r
is
ha,
“
P
hotovo
lt
a
i
c
Cell
F
e
d
3
-P
h
a
se
I
nd
uct
i
on
M
ot
or
Usin
g
M
P
PT
T
echn
i
que”,
Int
e
rna
t
i
onal
Jo
urn
a
l
of Po
wer
Elect
ro
n
i
c
s
and
D
r
i
ve S
y
stem
(
I
JPEDS)
,
Vo
l
.
5
,
No
.
2,
p
p
. 20
3
-
21
0,
Oc
t
o
b
e
r
2
01
4.
[5]
Gu
rusw
am
y
Rev
a
n
a
,
an
d
Ven
k
ata
Redd
y
Ko
ta,
“M
odel
i
n
g
a
nd
F
u
zzy
L
og
ic
C
on
tro
l
o
f
PV
B
as
ed
C
ascaded
B
o
o
s
t
Con
v
erter
T
h
ree
Ph
ase
F
i
v
e
-lev
el
I
nv
erter
S
y
st
e
m
”,
Inter
nati
o
n
a
l Jo
ur
nal
of
P
o
wer E
l
ectr
onics
a
n
d
Dri
ve Syst
em
(I
J
P
E
D
S
)
,
V
ol.
8,
N
o
.
3
,
pp
.
13
8
9
-140
0,
S
ep
t
e
mb
er
2
0
1
7
.
[6]
Tao
u
fik
L
aago
u
b
i
,
M
o
staf
a
Bo
u
z
i
,
a
n
d
M
oh
a
m
ed
B
en
chagra,
“
M
P
P
T
&
P
o
w
er
F
act
or
C
ont
ro
l
fo
r
G
r
id
C
on
nected
P
V
S
y
s
t
e
m
s
w
i
t
h
F
u
z
z
y
L
o
g
i
c
C
o
n
t
r
o
l
l
e
r
s
”
,
In
ter
n
a
t
i
onal Jo
ur
nal
o
f
Power El
e
c
tro
n
i
c
s an
d D
r
i
v
e
S
y
st
e
m
(I
J
P
E
D
S
)
Vo
l
. 9
, No
. 1
, pp
.
1
0
5
-
1
13
,
M
a
rch 2
0
1
8
.
[7]
E
.
Irm
ak
a
nd
N
.
Gül
e
r,
“
Appli
cati
o
n
o
f
a
h
igh
ef
fi
cient
v
o
ltag
e
reg
u
l
a
tio
n
sy
st
e
m
w
it
h
MPP
T
a
l
g
o
r
it
hm
”,
El
ectr
i
cal Po
wer
a
n
d
En
erg
y
Sys
t
ems
4
4
(1
),
pp.
703
–7
12,
2
0
1
3
.
[8]
B.
B
.
J
.
D
.
Retnam
a
n
d
A
.
Goun
den
,
“
P
o
w
e
r
E
l
ectro
n
i
c
In
terface
w
i
t
h
M
ax
imu
m
P
ow
er
P
oin
t
T
racki
ng
Usin
g
Li
ne-comm
u
ta
t
e
d
Invert
er
f
o
r
G
rid
-
conn
ected
P
erm
a
nen
t
M
agn
e
t
S
y
n
c
hron
ou
s
Gen
e
rat
o
r”,
Electr
i
c Po
we
r
Com
pon
ent
s
a
nd Sys
t
em
s
4
3
(5
),
p
p.
5
43
–5
55,
2015
.
[9]
V. S
a
l
as,
E.
O
lia
s
,
A
.
Barrado
,
an
d
A
.
L
azaro, “
Rev
i
ew
o
f
th
e
m
a
x
i
m
um
p
o
w
er p
oi
nt
t
ra
ck
in
g
al
g
o
rit
h
m
s
f
or
s
tand-
a
l
on
e
ph
oto
v
o
l
ta
ic
sys
te
m
s
”
,
S
o
lar
En
ergy
M
a
t
e
ri
als a
nd So
lar Cel
l
s
9
0 (1
1)
, 15
5
5–
15
78
, 20
0
6
.
[10]
D.
M
i,
Y
.
Jian
,
an
d
P
.
K
e,
“
Z
e
r
o
avera
g
e
in
cre
m
en
ta
l cond
uct
a
n
ce
ma
xim
u
m
p
o
w
er po
int
t
r
a
c
kin
g
cont
ro
l fo
r
ph
ot
ovolta
ic s
y
stem
”,
P
ro
c
CSEE
3
0
,
p
p
.
4
8–
53,
2010
,
[11]
F
.
L
i
u
,
S
.
D
u
a
n
,
F
.
L
i
u
,
B
.
L
i
u
,
a
n
d
Y
.
K
a
n
g
,
“
A
V
a
r
i
a
b
l
e
S
t
e
p
S
i
ze
IN
C
M
PPT
M
e
t
ho
d
f
o
r
PV
S
y
s
t
e
m
s
”,
IEE
E
Tran
sac
t
io
ns
on
Ind
u
str
i
a
l
Ele
c
tr
on
ic
s
5
5
(7
),
pp
. 2
62
2–
262
8,
2
0
0
8.
[12]
B
.
N
.
A
l
a
j
m
i
,
K
.
H
.
A
h
m
e
d
,
S
.
J
.
F
i
n
n
e
y
,
a
n
d
B
.
W
.
W
i
l
l
i
a
m
s
,
"
F
u
zzyL
ogi
c
Co
nt
rol
Ap
pro
ach
o
f
a
M
o
d
i
fied
H
il
l-
Climb
i
ng
M
e
t
h
o
d
fo
r
Ma
xi
mu
m
Powe
r
Po
in
t
in
M
ic
ro
grid
S
t
a
nd
a
l
on
e
P
hotovolt
a
i
c
System,"
IEEE T
r
ans o
n
,
Po
wer E
l
ectr
o
n
i
cs
,
vol.
2
6
,
N
o. 4
,
p
p.
102
2-1
030,
201
1.
[13]
V.
Q
uas
c
hni
ng,
“
Re
ne
wa
ble
Ene
r
gy
an
d Clima
t
e
Ch
an
g
e
.
1
s
t e
d
”,
J
oh
n
W
iley
&
So
ns
,
Ch
i
c
hes
t
e
r
,
W
e
st
S
u
s
s
e
x,
Uni
t
ed
Kin
gd
om, 20
1
0
.
[14]
F
.
K
ining
e
r,
“
Ph
ot
ovo
lt
aic
System
s
T
echn
o
lo
g
y
.
1
s
t
ed”,
U
niv
e
rs
i
t
ät
K
ass
e
l,
W
il-h
e
lm
sh
öh
e
r
A
lle
73,
3
4
121
Kassel, German
y
, 20
0
3
.
[15]
S
.
J.
E
.
M
i
neir
o
,
S
.
Daher
,
F
.
L.
M
.
An
t
u
ne
s,
a
n
d
C
.
M
.
T
.
C
r
uz,
“
P
h
ot
ovolt
a
ic
s
y
s
t
e
m
for
su
pp
ly
p
u
b
l
i
c
illumina
t
i
on
i
n
el
e
c
t
r
ical
e
nergy
demand
p
eak”,
IEEE Co
nf
erenc
e
on
a
p
p
lied
p
o
wer
elect
ro
ni
c
s
co
nf
eren
c
e
an
d
expo
s
i
t
io
n.Fortalez
a
,
Brazi
l
:
I
EEE
Pres, pp
. 1501
–
1506,
2004.
0
0.
02
0.
04
0.
06
0.
0
8
0.
1
0
20
40
60
80
10
0
12
0
14
0
16
0
t(
s
)
Pp
v
(
W
)
P
andO
F
u
z
z
y
M
am
da
ni
F
u
z
z
y
S
ugen
o
0.
0
5
0.
06
0.
07
0.
08
14
5
15
0
15
5
t(
s
)
Ppv
(
W
)
P
a
ndO
F
u
zz
y
M
a
m
d
a
n
i
F
u
z
z
y
S
uge
no
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
0
8
8
-
86
94
I
nt
J
P
ow
E
l
e
c
&
Dr
i
S
y
st,
Vol.
10,
N
o.
1
,
Mar
c
h
2
0
1
9
:
42
3
–
432
43
2
[16]
S
.
S
aravanan
a
n
d
R
am
es
h
Babu
N
,
“
M
a
x
i
m
u
m
po
wer
p
o
i
n
t
track
in
g
a
l
g
or
ithms
f
or
p
hotov
o
lta
i
c
s
ys
t
e
m
–A
rev
i
ew”,
Ren
e
wabl
e an
d
Su
s
t
ainab
le E
n
erg
y
R
e
v
i
ews
5
7
,
pp.
19
2–20
4,
2
01
6.
[17]
N
.
P
a
t
ch
arapraki
ti
a,
e
t
a
l
.
"M
axim
um
power
p
oint
t
racki
n
g
u
s
ing
a
d
a
pti
v
e
f
u
zzy
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ogi
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con
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rol
f
o
r
gri
d
-con
nect
ed
ph
oto
v
o
lta
ic
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ys
tem"
,
in
IEE
E
P
o
wer
En
g
.
S
o
ci
e
t
y W
i
nter M
eeti
n
g
,
p
p
.
372
-37
7
,
2002.
BIOGRAPHI
E
S
OF
AUT
HORS
Mo
hamm
ed
S
li
mi
w
as
b
orn
i
n
B
e
c
h
a
r,
A
lg
eria,
in
1
9
90.
H
e
recei
ved
hi
s
li
cense
deg
r
ee
and
M
a
ster
d
egree
in
e
l
ectrical
e
ngi
neeri
ng
f
r
o
m
t
he
E
l
ectrical
E
ng
in
eerin
g
Ins
t
i
t
ute
o
f
t
h
e
Un
iversit
y
o
f
Bech
ar
i
n
201
1
and
20
13
,
res
p
ect
ive
l
y.
Cu
rrently
h
e
is
m
em
ber
o
f
t
h
e
R
esearc
h
La
bo
ra
tory
o
f C
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ntrol
An
a
l
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i
s
a
n
d
Opt
im
iz
a
t
io
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th
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E
le
c
t
ro
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E
n
erget
i
c S
y
st
em
s.
Hi
s res
earch
i
nte
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are aut
o
m
atic control, artific
i
a
l
i
n
t
e
ll
i
g
en
ce and
renew
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ble
energy
.
e-emai
l : m
o
hamm
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13@gm
ail
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co
m
Abde
l
k
r
i
m
Bo
u
c
he
ta
W
a
s
bo
rn
i
n
Bechar,
Al
geri
a,
i
n
19
71.
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e
re
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d
his
BS
d
eg
re
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a
n
d
M
.
S.
d
eg
ree
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n
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lect
rical
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n
g
in
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f
r
o
m
t
h
e
E
lect
rical
E
ng
in
e
e
ri
ng
I
nsti
t
u
t
e
o
f
the
University
Center
o
f
Bech
a
r
,
in
2
0
01
and
2006
,
r
es
pecti
v
e
l
y
He
r
ecei
ved
t
h
e
P
h
D
degree
in
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l
ectri
cal
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ng
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f
ro
m
t
h
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U
n
i
versity
o
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Dj
ilal
i
L
iabes
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i
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i
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Belabb
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(
Al
geri
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e
i
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ren
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ro
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at
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n
i
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rsity
o
f
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s
are
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s
of
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nteres
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are
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o
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e
rn
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apti
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on
tro
l
a
nd
t
he
i
r
a
pplicat
ion
in
l
inear
electri
c dri
v
es con
tro
l
.
Bo
us
m
a
ha
B
ou
ch
ib
a
was
born
i
n
1
97
7
at
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e
c
h
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r-Al
g
eria,
he’s
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ecei
ved
th
e
el
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t
r
ica
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eng
i
neeri
n
g
di
plo
m
a
f
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o
m
B
echar
U
ni
versity
,
-
Al
geri
a
in
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a
n
d
t
h
e
M
a
s
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er
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eg
ree
f
r
om
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Un
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A
lexand
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Eg
yp
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P
h
.
D
.
deg
r
ee
f
r
om
t
he
E
lectri
c
a
l
E
ngineeri
ng
In
st
itu
t
e
o
f
t
he
S
DB
i
n
20
11
.
C
u
rre
ntly
,
he
i
s
a
n
a
ssista
n
t
p
ro
f
e
ss
or
a
t
Bech
ar
U
ni
versi
t
y.
wh
ere
he
i
s
m
e
mb
er
o
f
th
e
Research
L
aborat
ory
o
f
C
o
n
trol
A
n
a
ly
s
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s
a
n
d
O
p
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l
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erg
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ti
c
Syst
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m
s.
H
is
r
es
earch
i
nteres
ts
i
ncl
ude
p
ow
er
e
l
ectro
ni
cs,
e
l
ect
ric
dri
v
es
c
ont
rol,
a
nd
artifi
c
ial
intelli
g
e
nce and their appli
cat
i
o
ns
.
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