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
)
Vol.
10, No.
1, Mar
ch 2019,
pp.
48~57
IS
S
N
: 2088-
86
94,
D
O
I
:
10.11
5
9
1
/ij
ped
s
.
v10
.
i
1.pp
4
8
-5
7
48
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
A
d
aptive filter-FLC
integration
for torque ripples minimization
in PM
S
M using PSO
Ya
sser
Ahme
d
1
, A
yman
H
o
b
allah
2
1,
2
T
a
if
U
ni
versity
,
S
au
d
i
A
rabia
1
El
ectronic
Res
earch In
s
t
i
tute,
Eg
yp
t
2
T
a
nta
Un
i
v
ers
i
ty,
E
gy
pt
Art
i
cl
e In
fo
ABSTRACT
A
r
tic
le hist
o
r
y
:
Re
ce
i
v
e
d
Ju
l
1
8,
201
8
Re
vise
d O
c
t
1
4
,
2018
A
c
c
e
pte
d
D
ec 3,
201
8
Th
e
arti
cle
present
s
t
orqu
e
and
flu
x
r
ip
pl
es
m
i
n
imi
zati
o
n
based
o
n
adap
tiv
e
filter.
T
he
a
daptive
f
i
l
t
er
c
oef
f
icients
optimi
zed
a
nd
a
dapted
on
l
in
e
b
y
u
s
i
ng
part
icl
e
s
warm
o
pt
imizat
io
n
(PS
O
)
techn
i
q
u
e.
T
he
p
rop
o
sed
m
e
th
o
do
log
y
a
p
plie
d
on
c
lo
se
d
lo
op
s
p
e
e
d
c
ontrol
ba
se
d
o
n
d
ire
c
t
t
or
qu
e
c
o
n
trol
(
DT
C)
f
o
r
s
u
rf
ace
m
ounted
p
erm
a
nen
t
m
ag
net
s
y
n
c
hronou
s
m
o
tor
(PMS
M
)
.
F
u
zzy
lo
gi
c
co
nt
ro
ll
er
(
F
L
C)
u
sed
as
s
peed
c
o
n
t
r
oll
e
r
w
h
ile
p
ro
po
rtio
nal
-
integral
(P
I)
con
t
ro
ll
er
u
s
e
d
a
s
t
orq
u
e
an
d
fl
ux
c
on
tro
l
l
e
rs.
Seco
nd
o
rd
er
i
nf
init
e
impu
l
s
e
response
(
IIR)
f
ilter
is
u
sed
for
ripple
reducti
on
gene
ra
te
d
du
e
to
FLC
.
T
h
e
d
riv
e
s
yste
m
mo
de
le
d
usin
g
Ma
tla
b/
Si
mul
i
n
k
s
o
f
twa
r
e
in
o
r
d
e
r
t
o
dy
nam
i
cal
ly
e
v
a
l
u
at
e
th
e
perf
orm
a
n
ce
of
t
he
p
rop
o
s
e
d
d
r
ive
sys
t
em
a
t
diff
erent
op
erating
con
d
i
t
i
ons.
Th
e
res
u
lt
s
pro
v
i
d
e
evid
enc
e
t
h
at
t
he
a
dap
t
i
v
e
filter-FL
C
i
n
t
egrati
on
w
i
t
h
optim
a
l
c
oeffici
ents
m
ini
m
izes
t
orq
ue
a
nd
f
l
ux
r
i
pp
le
s
w
i
t
h
r
e
d
u
c
ti
on
o
f
to
ta
l
harmonic
d
istort
io
n
g
e
nerated
i
n
t
h
e
t
h
ree-
ph
ase cu
rrents
.
K
eyw
ord
s
:
FLC
IIR fi
l
ter
PMS
M
PSO
Torq
ue
r
ip
pl
e
s
m
i
n
im
i
zat
i
o
n
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:
Yasser
Ah
med
,
Taif
U
n
i
vers
i
t
y
,
S
audi A
r
a
bia.
Em
ail:
abde
lsa
l
am
yasser
@
ya
ho
o.c
o
m
1.
I
N
TR
OD
U
C
TI
O
N
O
n
e
o
f
t
he
f
a
m
ous
d
ri
ve
s
y
s
tem
s
i
s
pe
rm
anen
t
m
a
g
n
e
t
s
ync
h
r
o
n
o
u
s
m
ot
or
(
P
M
S
M
)
t
h
a
t
i
s
use
d
i
n
t
h
e
app
l
i
c
at
io
ns
w
hi
c
h
r
e
q
ui
re
h
i
g
h
-
p
e
rfo
rman
c
e
su
ch
a
s
ro
bot
i
c
s,
t
ra
nsp
o
r
t
a
tio
n
a
n
d
ind
u
s
t
ry.
Th
e
ma
in
a
d
v
a
n
t
a
g
e
s
o
f
P
M
S
M
a
r
e
h
i
g
h
e
f
f
i
c
i
e
n
c
y
,
s
m
a
l
l
l
o
s
s
e
s
,
l
o
w
m
o
t
o
r
s
ize,
h
i
g
h
p
o
we
r
de
ns
ity,
h
i
gh
acc
elera
t
i
o
n
and
dece
l
e
rat
i
on.
S
pe
ed
o
f
P
M
S
M
c
an
b
e
c
o
n
t
r
o
lled
b
y
u
s
i
n
g
e
i
t
h
er
d
i
r
ec
t
t
o
rqu
e
o
r
fie
l
d
or
ie
n
t
e
d
c
on
tro
l
(DTC
o
r
FOC).
The
DTC
is
p
referr
ed
b
ec
a
u
se
o
f
its
r
ap
id
d
y
n
a
m
ic
t
orque
r
e
s
pon
se
,
si
m
p
le
s
t
r
uc
tur
e
a
n
d
rob
u
st
c
ontro
l
schem
e
.
H
o
w
e
ver
,
D
TC
h
a
s
d
ra
w
b
ac
k
s
s
uch
as
r
ip
p
l
e
s
i
n
tor
que
a
nd
f
l
ux,
w
h
i
c
h
c
ause
con
s
i
d
era
b
l
e
a
moun
t o
f
n
o
i
se
a
nd
v
i
b
rat
i
ons
w
hich a
ffe
c
t
t
he
d
e
ri
ve
p
er
fo
rm
ance
[1]
,
[2].
The
r
e
a
r
e
tw
o
ope
rat
i
ng
t
e
c
hn
i
que
s
of
t
he
D
T
C
,
s
p
a
c
e
v
ec
t
o
r
m
o
d
ulation
(S
V
M
-DTC)
and
con
v
e
n
t
i
ona
l
sw
itc
h
i
n
g
t
a
b
le
(
ST-D
TC
).
I
n
the
S
V
M-D
T
C,
a
rbi
t
rar
y
vo
l
t
age
vec
t
ors
w
i
t
h
v
a
r
ia
bl
e
ma
gni
tude
s
a
n
d
fixe
d
sw
i
t
c
h
i
ng
fre
que
nc
y
a
r
e
gene
rate
d
f
o
r
cont
ro
l
lin
g
t
h
e
torq
ue
a
nd
flux
w
i
t
h
l
e
s
s
r
i
pp
les
t
h
a
t
t
h
e
S
V
M
-
D
T
C
i
s
m
o
r
e
a
c
c
u
r
a
t
e
t
h
a
n
t
h
e
S
T
-
D
T
C
.
I
n
o
r
d
e
r
t
o
c
o
n
t
r
o
l
t
h
e
tor
que
a
n
d
f
lu
x
ba
se
d
o
n
t
he
ST-
D
TC
,
the
a
p
pr
opria
te
v
ol
ta
ge
v
e
c
t
o
r
is
p
i
n
p
o
i
n
ted
fr
om
s
w
itc
h
i
n
g
t
a
b
l
e
o
f
a
ce
rta
i
n
num
ber
of
s
pe
cifie
d
vo
lta
ge
v
ec
tor
s
t
ha
t
are
est
i
m
a
t
e
d
a
t
va
ria
b
le
s
w
i
tch
i
n
g
fre
que
ncy.
T
here
fore
,
t
h
e
S
V
M-D
T
C
is
u
se
d
in
t
h
i
s
work
[
3],
[
4
]
.
The
use
d
m
et
ho
d
o
l
ogie
s
f
or
r
i
p
p
l
es
m
i
n
i
m
iza
t
i
o
n
i
n
t
h
e
m
otor
d
r
ive
s
a
re
opt
ima
l
d
es
i
g
n
o
f
t
he
ma
chine
a
n
d
sui
t
a
b
le
c
o
n
trol
s
che
m
e
.
T
he
d
es
ign
pr
ocess
sho
u
l
d
o
p
timi
z
e
the
sta
t
or
a
nd
ro
t
o
r
pa
ram
e
ter
s
t
o
reduc
e
the
c
o
g
g
i
ng
t
o
rq
ue
a
s
well
as
h
arm
o
n
i
c
c
o
n
t
e
n
t
s
o
f
the
m
a
g
n
e
t
i
c
f
l
u
x
.
F
u
r
t
h
e
r
s
t
u
d
y
w
a
s
i
n
[
5
]
i
n
order
t
o
r
ed
uc
e
the
c
o
g
g
i
n
g
t
or
que
w
her
e
t
he
p
r
o
p
o
sa
l
w
a
s
ba
se
d
o
n
t
h
e
des
i
g
n
o
f
s
l
ots
w
i
dths
a
n
d
t
oot
h
p
r
o
f
i
l
e
s.
I
n
[6]
,
t
he
a
u
t
h
o
r
st
udie
d
t
he
c
om
bina
ti
on
i
n
flue
nc
e
of
c
o
n
s
i
dera
tio
n
o
f
t
he
p
o
l
e
a
nd
slo
t
s
hape
s
on
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
Ad
ap
tive
fi
l
t
e
r
-fl
c
i
n
te
gra
tio
n fo
r tor
q
ue
ri
pp
les m
i
n
i
m
i
z
a
t
i
o
n
in
pm
sm
us
in
g
PSO
(
Y
as
ser A
h
m
e
d)
49
tor
que
r
ip
p
l
e
s
i
n
a
P
M
S
M
a
nd
t
h
e
re
su
lts
c
larif
i
e
d
t
ha
t
t
h
e
ri
p
p
l
e
s
m
a
ybe
i
ncr
ease
d
i
f
t
h
e
m
ach
ine
is
n
ot
carefully designed.
Ma
ny
c
on
tro
l
m
e
t
hod
ol
o
g
i
es
h
a
v
e
bee
n
r
ep
orte
d
in
t
he
l
i
t
e
r
ature
f
o
r
l
i
m
it
ing
f
l
ux
a
nd
t
o
r
qu
e
ri
pp
l
e
s
in
w
hic
h
i
t
ma
i
n
ta
in
ed
s
m
oot
h
opera
t
i
o
n
o
f
t
h
e
drive.
T
he
c
on
tr
o
l
m
etho
d
o
lo
gy
a
d
ap
ts
t
he
c
ontr
o
l
l
er
pa
ra
me
te
r
s
t
o
o
p
ti
mi
ze
t
he
o
utpu
t
vol
t
a
ge
v
ec
tor
f
r
o
m
t
h
e
i
n
v
e
r
te
r
[
7
],
[
8
]
.
To
ward
t
he
s
p
e
e
d
c
on
t
r
ol
u
si
ng
F
O
C
i
n
t
he
i
n
t
er
i
o
r
P
M
S
M
d
r
i
ve
s
ys
tem
,
[
9]
s
ug
ges
t
ed
t
o
use
the
a
da
p
tive
f
i
l
t
er
i
n
o
r
der
to
m
inim
i
ze
the
tor
que
r
ipp
l
es
w
he
re
t
he
f
uz
z
y
l
og
i
c
c
o
n
t
rol
l
er
(
F
L
C)
w
a
s
d
es
ig
ne
d
a
n
d
the
fi
l
t
er
c
oeffic
i
en
ts
s
e
l
ect
i
o
n
w
a
s
base
d
o
n
t
h
e
t
r
i
a
l
-err
or
c
onc
e
p
t
.
T
h
e
s
pee
d
h
ar
mon
i
c
m
a
gn
i
t
u
d
e
i
s
u
s
e
d
a
s
a
f
e
e
d
b
a
c
k
c
o
n
t
r
o
l
s
i
g
n
a
l
i
n
a
clo
s
ed-l
o
op
cu
rr
ent
con
t
rol
l
e
r
i
n
or
der
to
r
educ
e
t
o
rq
ue
r
ip
p
l
e
s.
T
he
o
b
t
ai
ne
d
r
e
sults
c
o
n
f
i
r
m
t
h
e
att
a
i
n
ed
ripple
s
reducti
on
[10]
.
In
[
11]
,
a
m
odifi
e
d
s
w
i
t
c
hin
g
t
a
b
l
e
i
s
des
i
g
n
e
d
f
or
t
he
t
hre
e
vol
t
a
ge
v
ec
tors
i
n
D
T
C
selec
t
i
o
n r
a
ther
tha
n tw
o
vo
lta
ge
ve
c
t
ors. Th
e
c
orre
sp
on
d
i
n
g
le
s
s
rippl
e
conte
n
ts are
a
sc
ertai
n
e
d
in torq
ue an
d
f
l
ux
w
i
t
h
s
in
us
oida
l
sta
t
or
c
u
r
re
n
t
.
H
o
w
e
ve
r,
t
he
d
u
r
at
i
o
ns
o
f
t
h
e
th
re
e
v
ect
o
r
s
are
com
p
u
t
e
d
t
o
r
e
du
ce
t
h
e
s
w
i
t
c
h
i
n
g
fr
equ
e
n
c
y
.
I
n
[1
2]
,
variable
a
mpli
t
ude
a
nd
an
g
l
e
vo
l
t
a
g
e
vec
t
or
h
a
v
e
bee
n
c
on
tro
lle
d
t
o
r
e
d
u
c
e
rip
p
les
base
d
on
D
T
C
for
PMS
M
d
r
i
ve
s
y
s
t
e
m.
A
p
r
e
dicti
v
e
D
T
C
is
p
r
o
p
o
se
d
t
o
e
n
h
a
nce
t
h
e
c
o
nve
nti
ona
l
D
T
C
pe
rform
a
n
c
e
d
urin
g
tra
n
s
i
en
t
an
d
ste
a
dy
s
t
at
e
con
d
i
t
i
ons.
F
or
f
ast
t
r
ans
i
e
n
t
re
sponse
,
a
p
ara
m
e
t
e
r
regu
la
ti
on
o
f
t
he
v
olta
ge
v
ec
t
o
r
s
i
s
c
ons
ide
r
ed.
H
o
w
e
ve
r,
t
he
r
ip
p
l
es
a
r
e
m
ini
m
ize
d
b
y
i
nves
tiga
t
i
n
g
th
e
opt
i
m
a
l
a
mpli
t
u
d
e
,
a
n
gle
,
a
nd
du
r
a
t
i
o
n
of
th
e
vo
lta
ge
ve
c
t
or
[1
3].
Ar
ti
fi
cia
l
i
n
t
e
l
l
i
g
e
n
c
e
(AI)
a
pp
ro
ach
es
w
e
r
e
u
s
ed
f
o
r
op
t
i
m
al
s
e
l
e
c
t
i
on
of
c
o
n
tr
ol
s
c
h
e
m
e
pa
ra
me
t
e
rs
to
m
in
i
m
iz
e
t
o
rque
a
n
d
f
lu
x
r
i
p
p
l
es
a
nd
e
nhanc
e
sy
st
em
p
e
r
f
o
r
m
a
nc
e
a
s
r
e
p
or
te
d
in
[
14
].
T
h
e
f
amo
u
s
exa
m
ple
s
o
f AI
-based
m
etho
ds
a
re
ge
n
et
i
c
a
l
g
or
it
hm
(GA) a
s well
as parti
c
l
e
swarm
o
pti
m
ization (
P
S
O
)
.
I
n
t
h
i
s
w
o
r
k
,
t
h
e
spee
d
of
s
urfa
ce
m
o
u
n
t
e
d
P
MSM
con
t
ro
l
l
ed
u
sin
g
DTC
t
e
chni
qu
e.
F
LC
i
nt
eg
rat
e
d
w
ith
s
e
c
o
nd
o
r
d
er
i
nf
in
ite
i
m
p
u
l
se
r
esp
onse
(I
IR)
fi
lt
e
r
u
s
e
d
a
s
spe
e
d
co
ntr
o
l
l
er
w
hi
le
P
I
c
o
ntr
o
l
l
er
s
use
d
i
n
tor
que a
nd flu
x
l
o
o
p
s. The IIR filter
u
s
ed
t
o r
e
duc
e
the
rip
p
l
e
s ge
nera
ted b
y
F
LC. P
S
O
is use
d
t
o o
p
t
i
m
i
z
e
the
sy
st
em
p
erfo
rman
ce
o
n
-
l
i
n
e
b
y
s
e
l
e
c
tin
g
t
h
e
opt
i
m
a
l
c
o
e
ffi
c
i
e
n
t
o
f
ada
p
t
i
ve-
IIR
f
ilter
an
d
co
nt
rol
l
e
rs
w
h
i
ch
minim
i
z
e
f
l
u
x
and
t
o
r
q
ue
r
i
p
pl
e
s
.
The
ada
p
ti
ve
f
i
lter
coe
f
ficie
nts
ar
e
op
t
i
m
i
z
e
d
simu
l
t
a
n
eo
us
l
y
a
n
d
v
a
r
ied
as
a
fu
nc
ti
o
n
i
n
the
t
o
r
q
ue
r
ipple
s
.
A
close
d
l
o
o
p
s
pe
ed
c
on
tro
l
b
a
s
ed
o
n
FLC
an
d
SVM
-
DTC
i
n
s
u
r
f
a
ce
moun
te
d
P
M
S
M
i
s
pro
p
o
s
ed.
The
pro
p
o
sed
sys
t
em
m
ode
lle
d
in
M
a
tla
b
e
n
v
i
r
o
nme
n
t
.
T
he
p
r
opos
e
d
m
e
t
h
o
d
is
j
ust
i
f
ie
d
b
y
app
l
y
i
n
g the
me
t
h
o
d
o
l
og
y o
n
d
iffere
n
t
opera
t
i
ng
c
o
n
d
it
io
ns
o
f
the
sys
t
em
under
i
nves
t
i
g
a
tio
n.
2.
TEST
SY
S
T
EM STRUCTURE
The
pre
s
en
te
d t
e
st s
yste
m c
o
n
s
ists of
P
M
S
M
w
it
h in
ver
t
e
r
br
i
dge
, spe
e
d F
L
C
i
n
tegra
t
e
d
w
it
h
r
i
p
p
le
s
minim
i
z
a
t
i
on a
l
g
o
ri
t
h
m
and D
T
C
co
ntr
o
l
l
e
r
a
s dep
i
cte
d
i
n F
i
gure
1.
The
sys
t
e
m
c
om
po
nen
t
s
ar
e a
s
foll
o
w
s
.
2.1.
PMS
M
ma
t
hema
tica
l m
o
del
The
P
M
S
M
mode
l i
n
r
ot
a
t
i
n
g
d-
q fr
am
e
i
s
: [
15],
[16]
:
.
(
1
)
.
(
2
)
.
(
3
)
.
(
4
)
.
.
(
5
)
F
r
om 3,
4 a
nd 5,
the
e
lec
t
rom
a
gne
tic
t
orque
(
) c
a
n
be de
r
iv
ed a
s:
.
.
(
6
)
F
r
om
(
6)
s
how
s
that
c
ont
a
i
n
s
t
w
o
c
ompon
ent
s
t
hat
ar
e
the
torque
due
t
o
perm
ane
n
t-
m
a
gnet
an
d
the
rel
u
cta
n
ce
tor
que.
For
the
PMS
M
t
ype
c
ons
i
d
ere
d
i
n
th
e
stud
y,
t
he
s
u
r
fac
e
m
ounte
d
t
y
p
e
has
t
h
a
t
=
.
Th
is
m
e
a
n,
the
r
elucta
n
c
e
t
o
r
que i
s e
l
i
m
i
n
a
t
ed,
e
qua
tio
n
can
b
e
w
r
itt
e
n
as:
(
7
)
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
:
48
–
57
50
|
||
|
(
8
)
Th
e me
ch
a
n
i
c
al
eq
u
a
ti
on
of
t
h
e PM
SM
c
an
b
e f
o
rmu
l
a
t
e
d
by
[
1
7
]
:
(
9
)
wher
e
,
,
a
nd
a
re
s
tator
vol
t
a
ge
s
and
curre
nts
respe
c
t
i
ve
ly
i
n
d-q
r
o
t
a
ti
ng
fram
e.
i
s
t
h
e
stator
resistance.
i
s
the
m
echa
n
i
c
a
l
s
pee
d
.
,
,
,
a
nd
a
re
s
t
a
t
o
r
f
l
ux
a
n
d
indu
ct
a
n
ce
c
o
m
p
one
n
t
s,
re
sp
ec
ti
v
e
ly
.
a
nd
a
r
e
t
he
s
ta
tor
flu
x
lin
ka
ge
a
nd
pe
rm
anen
t
ma
gnet
i
c
flu
x
,
respe
c
tive
l
y.
P
i
s
the
motor
p
o
l
e
p
a
i
r
s
n
u
m
b
e
r
.
δ
i
s
t
h
e
l
o
a
d
a
n
g
l
e
.
i
s
t
h
e
l
o
a
d
t
o
r
q
u
e
.
a
nd
a
re
f
ri
c
t
ion
co
ef
fi
ci
e
n
t
a
n
d
c
o
mp
osed
motor-
loa
d
i
ne
rtia,
r
e
specti
v
e
l
y.
F
i
gure
1.
T
est sys
t
e
m
s
t
r
uct
u
re
2.2.
Sp
eed
c
ont
r
olle
r
The
F
L
C
a
c
t
s
a
s
a
P
I
spee
d
c
o
n
t
r
o
ller
i
n
t
he
D
T
C
d
ri
ve
s
ys
tem
a
s
de
p
i
c
t
e
d
i
n
F
i
gure
1.
B
y
di
ffe
re
nt
ia
tio
n
of
9
,
the
spe
e
d
i
s
regula
t
e
d
b
ased
o
n
con
t
ro
lli
ng
t
h
e
cha
n
g
e
i
n
elec
t
r
oma
g
n
e
t
i
c
t
o
rque
(
∗
)
tha
t
i
s
pr
esen
ted
i
n
(
10)
.
The
com
p
o
n
e
n
t
s
o
f
spee
d
c
o
n
t
r
o
ller
e
x
p
l
a
in
e
d
i
n
th
e
fo
l
l
ow
i
n
g
sect
i
ons.
∗
(
1
0
)
2.2.
1. F
LC
m
od
e
l
The
F
L
C
c
o
n
s
i
s
ts
o
f,
f
uzz
i
f
i
c
a
tio
n,
f
uzz
y
i
nfer
ence
,
and
def
u
zz
i
f
ica
t
ion
as
d
ep
ic
ted
i
n
F
ig
ur
e
2.
T
he
spee
d
err
o
r
(
)
and
i
t
s
chan
ge
(
a
r
e
t
h
e
F
L
C
i
n
p
u
t
s
w
h
i
l
e
t
h
e
t
o
r
q
u
e
c
h
a
n
g
e
(
∗
i
s
the
outpu
t.
T
he
in
put
s a
nd o
u
t
pu
t
rela
ti
on
sh
ips
of t
he
F
LC c
an
b
e w
r
i
tte
n
as fo
ll
ow
s:
∗
(
1
1
)
1
(
1
2
)
∗
E
,
Δ
E
(
1
3
)
wher
e
1
i
s
a
sp
e
e
d
er
ror
pre-
sa
m
p
l
e
,
,
∗
a
n
d
a
r
e
t
he
p
rese
nt
s
a
m
pl
e
s
o
f
spe
e
d
e
rror
,
refere
nce
spee
d
and
me
chan
i
c
a
l
m
ot
or
spee
d
r
e
s
pe
ct
ive
l
y.
The
fu
z
z
i
f
ica
t
i
on
pr
oc
ess
ma
ps
t
he
i
n
p
u
t
variab
les
a
nd
t
o
t
h
e
c
o
rre
s
p
o
ndi
ng
l
in
gui
st
ic
varia
b
l
e
s.
T
he
f
uz
z
y
i
nfe
r
e
n
c
e
gets
t
he
c
on
t
r
ol
r
ule
s
f
or
e
very
i
np
ut
.
The
d
e
fu
z
z
i
f
i
c
a
t
io
n
co
nv
e
r
t
s
t
he
i
np
u
t
rules t
o
t
he
c
risp
v
al
ue
o
f ou
t
p
ut
∗
.
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
Ad
ap
tive
fi
l
t
e
r
-fl
c
i
n
te
gra
tio
n fo
r tor
q
ue
ri
pp
les m
i
n
i
m
i
z
a
t
i
o
n
in
pm
sm
us
in
g
PSO
(
Y
as
ser A
h
m
e
d)
51
F
i
gure
2.
F
uzz
y
lo
g
i
c
spee
d c
ontro
l
l
er
The
E
a
n
d
Δ
E
m
e
m
be
rshi
p
f
u
nc
tio
ns
a
re
d
epic
te
d
in
F
i
g
ure
3(a
)
.
The
de
sig
n
e
d
s
e
t
s
of
t
he
i
npu
t
varia
b
l
e
s
are
as
t
ha
t
P
B
,
P
S
,
ZE,
N
S
,
a
nd
N
B
a
re
p
o
s
i
t
i
ve
b
ig
,
p
o
s
i
t
i
v
e
s
m
a
l
l
,
z
e
r
o
,
n
e
g
a
t
i
v
e
s
m
a
l
l
,
a
n
d
nega
t
i
ve
b
i
g
,
re
spe
c
t
i
v
e
l
y.
T
he
o
u
t
pu
t
var
i
a
b
le
Δ
∗
m
embe
rshi
p
f
unc
ti
on
s
are
depi
cte
d
i
n
F
i
g
u
r
e
3
(b)
w
h
e
r
e
t
h
e
o
u
t
p
u
t
s
e
t
s
a
r
e
t
h
a
t
P
B
,
P
M
,
P
S
,
Z
E
,
N
S
,
N
M
,
a
n
d
N
B
a
r
e
a
c
r
o
n
y
m
o
f
pos
i
tive
bi
g,
posi
t
ive
m
e
dium
,
pos
it
ive
sma
ll,
z
ero,
n
egat
i
v
e
sma
l
l,
n
e
g
a
t
i
v
e
m
e
dium
,
and
nega
tive
bi
g,
r
e
s
pe
c
t
i
v
e
l
y.
M
em
bershi
p
t
y
p
e
s
an
d
li
m
i
ts
a
re
ob
t
ai
ned
b
y
ex
p
e
r
ie
nce
[18]
.
(a)
(b)
F
i
gure
3.
Mem
bersh
i
p o
f
F
LC
The
fuzz
y
infe
re
nce
sys
t
em
u
ses
Mam
d
a
n
i-
t
ype
m
et
h
od
w
h
er
e
con
t
r
o
l
r
u
l
es
o
f
the
fuzz
y
co
ntr
o
l
l
er
do
ne
b
y
if
a
nd
t
h
e
n
l
o
gi
c
ope
ra
t
o
r
s
acc
ord
i
n
g
t
o
t
h
e
n
o
rma
l
i
z
e
d
v
al
ue
s
of
a
nd
i
n
or
der
to
e
st
im
ate
t
h
e
set
of
∗
as li
ste
d
in Ta
ble 1.
Th
e
c
entro
i
d
m
e
tho
d
i
s use
d
as t
h
e
de
fuz
z
i
fica
t
i
o
n
me
t
ho
d to
c
om
pu
t
e
the
∗
val
u
e
to
r
educ
e
t
h
e
val
u
e
o
f
.
Ta
ble
1.
F
uz
zy log
ic
r
ules
∆
N
B
N
S
ZE
PS
P
B
N
B
N
B
NB
N
B
NM
Z
E
NS
N
B
NM
N
S
ZE
P
M
ZE
N
B
N
S
Z
E
PS
P
B
PS
N
M
Z
E
P
S
PM
P
B
P
B
Z
E
PM
P
B
PB
P
B
2.2.
2. R
i
p
p
l
es
m
in
im
izat
ion
al
g
o
rith
m
Th
e
ma
in
s
ou
rc
e
of
s
p
e
ed
a
nd
t
o
r
q
u
e
r
i
p
pl
es
i
n
th
e
p
r
op
ose
d
D
TC
s
y
s
t
e
m
c
o
me
s
f
r
o
m
FL
C
.
2nd
order
ada
p
t
i
ve
IIR
f
i
l
ter
u
t
i
l
i
z
e
d
for
r
i
p
p
l
es
m
in
imiza
t
i
on.
T
h
is
p
rop
o
se
d
m
ode
l
is
a
s
il
lu
stra
te
d
i
n
F
igur
e
4
w
h
er
e it c
a
n be
re
p
rese
nt
e
d
b
y
the
fo
l
l
ow
ing
t
i
m
e
d
iffer
e
nce
e
q
ua
t
i
o
n
[
19]
:
1
2
1
2
(
14)
w
h
er
e
y
re
pre
s
en
ts
t
he
f
i
lter
outp
u
t
(fi
l
t
e
red
)
,
x
r
e
p
rese
nts
t
h
e
f
ilter
inp
u
t
(
)
a
nd
n
repre
s
ents
t
h
e
signa
l
i
nde
x.
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
:
48
–
57
52
The
fil
t
er
c
oe
ffi
c
i
e
n
ts
a
re
o
p
t
i
m
iz
ed
u
s
i
ng
P
SO
a
lg
ori
t
hm
t
o
mi
nimi
z
e
t
he
t
or
que
a
n
d
f
lu
x
ri
pp
le
c
o
nt
en
ts.
Ea
ch
f
i
l
t
e
r
co
e
ffi
ci
en
t
can
b
e
re
p
r
ese
n
t
e
d
b
y
∗
,
where
|
ΔT
∗
|
.
The
c
o
eff
i
ci
ent
s
a
nd
a
re
opt
i
m
ize
d
s
i
m
u
lta
ne
ous
ly b
y P
S
O
over
all the
o
p
era
t
i
ng p
o
i
nt
s.
F
i
g
u
r
e
4
.
I
I
R
filter
mode
l
2.3.
Direct
torque
c
on
trol
Th
e
vo
lt
ag
e
ve
ct
o
r
s
el
e
c
ti
on
i
s
t
h
e
m
ai
n
ke
y
i
n
t
h
e
D
TC
,
wh
ere
a
des
i
gn
o
f
t
h
e
vo
lt
age
ve
c
t
or
i
s
ma
de
f
or the
r
e
g
u
l
a
t
i
o
n
of the
electr
o
m
a
gne
ti
c
tor
que
a
n
d
s
ta
t
o
r
f
l
ux.
F
rom
(8)
,
t
he
t
orq
u
e
is
a
f
u
n
c
tio
n
i
n
t
he
δ.
T
h
e
a
ngle
δ
betw
ee
n
a
nd
r
e
m
ains
c
ons
tan
t
dur
ing
ste
a
dy
st
a
t
e
w
h
e
r
e
bot
h
and
r
u
n
a
t
t
h
e
sam
e
spe
ed.
Duri
ng t
r
ans
i
e
n
t sta
t
e,
δ is c
h
anged bec
a
u
se of the
rotat
i
on of bot
h
a
nd
a
t
di
ffe
r
e
n
t
s
pe
e
d
s
.
C
o
mp
a
r
i
n
g
with
r
es
p
ect
t
o
ele
c
t
ri
cal
t
i
m
e
co
n
s
t
a
nt
,
t
h
e
syst
e
m
m
echa
n
i
c
al
t
i
m
e
c
o
ns
t
a
nt
i
s
s
l
ow
e
r
r
espo
nse
,
the
n
t
he an
g
l
e δ ca
n be ad
j
u
s
t
e
d b
y
regu
l
at
i
o
n of the
s
pe
ed w
it
h
r
e
s
p
ec
t
to
the
.
Th
i
s
i
s imp
l
ement
e
d
by
selec
t
i
n
g
t
h
e
su
ita
b
l
e
v
o
l
t
a
g
e
vec
t
or
f
or
t
he
e
r
r
or
m
ini
m
i
z
at
io
n
o
f
t
h
e
t
orq
u
e
a
n
d
fl
ux
w
i
t
h
r
esp
e
c
t
t
o
refere
nce
va
l
u
es.
D
T
C
b
l
oc
k
c
ons
is
ts
o
f
P
I
-
t
or
q
u
e
co
n
t
ro
ller,
P
I-flu
x
co
ntr
o
l
l
er
a
n
d
f
l
ux/
tor
que
e
stim
at
or.
2
.
3
.
1
. T
o
r
que
co
ntro
l
l
e
rs
The
t
o
rq
ue
a
nd
f
l
ux
c
o
n
t
ro
lle
rs
u
t
i
l
i
z
e
c
o
nve
nt
iona
l
P
I
c
on
tr
ol
le
rs.
The
i
n
pu
t of
t
he tor
q
u
e
co
n
t
rol
l
er
is
t
he
d
iffere
nc
e
of
t
he
a
ctua
l
tor
que
w
it
h
respec
t
to
t
he
r
e
f
e
r
e
nce
value
i
n
o
rder
t
o
atta
i
n
t
he
o
u
t
p
u
t
.
The
tor
que
e
stim
at
i
on i
s
base
d
o
n the
m
easure
d
c
ur
rent
a
n
d
e
st
i
m
ate
d flu
x
:
(
1
5
)
2.3.
2. F
l
u
x c
o
n
t
r
o
l
l
er
The
i
n
pu
t
o
f
t
h
e
f
l
ux
c
o
n
t
ro
l
l
e
r
i
s
the
di
ffe
r
e
nc
e
be
tw
ee
n
a
c
tu
a
l
a
nd
refe
renc
e
fl
u
x
es
w
hi
l
e
i
s
t
h
e
atta
i
n
e
d
outp
u
t
. Then,
t
he con
tro
llers ou
t
p
u
t
t
r
a
ns
form
ed to
co
n
t
ro
l vo
ltage
c
ompone
nts in
α-β frame
(
,
)
w
h
ic
h
are
use
d
t
o
g
e
nera
te
t
he
S
V
P
WM
pul
ses
tha
t
f
ire
the
in
ver
te
r
b
r
i
d
ge
.
The
ge
n
e
r
a
ted
v
o
l
ta
ge
v
ect
or
sho
u
l
d
m
ain
t
a
i
n
t
h
e
t
o
rq
ue
a
n
d
f
l
u
x
a
t
i
ts
r
equ
i
red
val
u
e
w
i
t
h
mi
nimum
ri
pp
les.
T
he
m
agn
i
tu
d
e
a
nd
a
n
gle
o
f
Ψ
s ca
n be
esti
m
a
t
e
d
by
the
fol
l
o
w
i
ng eq
ua
tio
ns [20]
.
(
1
6
)
(
1
7
)
wh
ere:
(
1
8
)
(
1
9
)
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
Ad
ap
tive
fi
l
t
e
r
-fl
c
i
n
te
gra
tio
n fo
r tor
q
ue
ri
pp
les m
i
n
i
m
i
z
a
t
i
o
n
in
pm
sm
us
in
g
PSO
(
Y
as
ser A
h
m
e
d)
53
wher
e
a
nd
r
eprese
n
t
t
he
c
ur
rent
c
om
po
ne
n
t
s
in
α
–
β
f
r
a
m
e
,
a
nd
r
e
p
r
e
s
e
n
t
t
h
e
α
-
β
c
ompone
nts
of
the e
s
t
i
m
a
te
d
Ψ
s.
3.
PSO ALGO
RITHM
P
S
O
a
s
one
o
f
me
t
a
-heur
i
st
ic
o
pt
i
m
iza
t
i
o
n
te
chn
i
que
s
d
e
p
e
nd
s
o
n
s
ear
c
h
i
n
g
the
o
p
tim
a
l
s
ol
u
tio
n
w
ithi
n
t
he
s
ear
ch
a
re
a
based
on
the
e
x
c
h
a
n
ge
o
f
ex
per
i
e
n
c
e
s
am
o
n
g
p
a
rtic
l
e
s
in
t
h
e
popu
l
a
ti
on
.
Th
e
p
a
rt
i
c
l
e
s
in
t
he
s
w
a
rm
m
odif
y
t
heir
p
os
it
ions
i
n
t
h
e
nex
t
itera
ti
o
n
b
a
s
e
d
o
n
ind
i
v
i
dua
l
l
o
ca
l
be
s
t
p
osit
i
on
a
n
d
g
l
o
b
a
l
bes
t
p
os
it
ion
o
f
s
w
a
rm.
Ea
ch
p
art
i
cle
re
pres
e
n
ts
a
s
o
l
ut
i
on
for
t
he
c
on
t
r
o
l
v
ar
i
a
bles
o
f
t
h
e
e
n
t
i
re
o
p
timi
z
a
tio
n
pro
b
lem
.
T
he
c
on
tro
l
v
aria
bl
es
w
hic
h
u
se
d
for
m
i
ni
m
i
za
t
i
on
o
f
t
orq
u
e
r
i
pp
les
i
n
P
M
S
M
are
t
h
e
s
p
ee
d,
f
l
u
x,
tor
que
P
I
gai
n
s
c
o
n
t
r
o
l
l
e
r
s
a
n
d
fi
lt
e
r
c
oe
ffi
c
ien
t
s.
F
or
t
he
p
a
r
tic
le
(
i
)
,
it
m
od
ifies
t
h
e
pos
it
io
n
in
t
he
n
e
x
t
i
t
erat
ion
,
k
+1, (
)
based
on
the
ve
l
o
c
ity
(
)
of
t
he pa
r
t
i
cle
s
usi
ng t
h
e
fol
l
ow
i
n
g e
qua
t
i
ons
[
2
1
]:
(
2
0
)
(
21)
wh
ere,
χ
i
s
adapt
i
v
e
fa
ct
or
w
hic
h
u
se
d
to
c
on
tro
l
t
he
s
w
a
rm
c
onver
s
io
n.
z
i
s
a
w
e
i
g
h
t
f
a
c
t
o
r
f
o
r
con
t
ro
l
lin
g
t
h
e
vel
o
c
i
t
y
o
f
sw
a
r
m
tow
a
rds
th
e
op
t
i
ma
l
so
l
u
tio
n.
C
1
an
d
C2
a
r
e
g
ener
ate
d
r
a
ndom
num
be
rs
i
n
the r
a
n
g
e
of 0
a
nd
2.
and
a
r
e t
h
e
l
o
c
a
l
a
n
d
glo
b
a
l
b
e
st
po
s
itio
n
s
at
t
h
e
p
r
e
v
io
u
s
i
t
e
rati
on
s.
The
o
b
jec
t
i
v
e
fun
c
t
i
o
n
i
s
t
o
m
inim
ize
el
ectrom
a
g
n
e
tic
t
orq
u
e
ri
pp
l
e
s
,
w
h
i
c
h
ca
n
be
repr
esente
d
b
y
the
f
o
llow
i
n
g
e
xpress
i
on
:
∑
(
2
2
)
∑
(
2
3
)
w
h
er
e n
is
t
he num
ber
of
s
am
p
l
e
s
,
i
s the
ave
r
a
g
e
val
u
e of e
le
ctr
o
m
a
gne
t
i
c
torq
ue
.
Th
e
opt
i
m
al
s
o
l
ut
ion
shou
ld
s
a
t
i
s
fy
t
h
e
ope
rat
i
o
n
a
l
c
o
n
s
t
r
a
i
nt
s
.
The
c
ons
ider
ed
c
o
n
st
ra
ints
a
re
t
h
e
st
a
t
or
f
lux
rip
p
le
s
(
a
nd
mean
o
f
spe
e
d
e
rror
(
c
a
n
b
e
represe
n
te
d
b
y
t
he
f
o
l
l
o
w
i
n
g
e
x
p
r
e
ss
ions
[2
2],
[23]
.
∑
ℎ
ℎ
(
2
4
)
ℎ
∑
ℎ
(
2
5
)
∑
(
2
6
)
wher
e,
ℎ
is a
stat
or flux
ave
r
age
value.
The
c
o
nstr
ain
t
s
ar
e
ta
k
i
ng
i
n
t
o
a
c
c
o
un
t
d
u
r
i
ng
o
p
t
i
m
iza
t
i
o
n
by
a
n
a
da
pt
ive
pe
nal
t
y
fun
c
tio
n
w
h
er
e
a
modi
fie
d
o
b
j
e
c
t
i
v
e
fu
nc
t
i
o
n
f
or
mula
ted
bas
e
d
o
n
t
he
n
or
ma
l
i
z
e
d
ori
g
in
al
o
b
j
ect
i
v
e
f
unc
t
i
on
a
n
d
n
o
rm
alize
d
con
s
trai
n
t
s
vi
o
l
at
ion
s
[
24],
[20].
The
m
odifie
d
obje
c
tive
fu
nc
t
io
n
(
,
)
w
h
i
c
h
p
e
na
lize
d
t
he
i
nfeas
ib
le
sol
u
ti
on
s fo
r c
o
n
s
id
e
r
in
g
th
e
c
o
nst
r
a
i
nt
s vi
ol
at
i
o
n
s
(
,
)
ca
n be for
mulate
d
b
y
:
,
,
,
,
∗
∗
,
(
27)
Where
a
nd
a
re
t
he
num
ber
of
f
e
a
si
b
l
e
a
n
d
i
n
feas
i
b
le
s
olu
t
io
ns
i
n
sw
arm
r
espe
ctive
l
y.
X
i
s
pena
l
i
za
t
i
o
n
f
u
n
ct
i
on
w
h
ic
h
equa
l
ze
ro
a
t
no
f
ea
sible
s
o
lut
i
ons
(
0
)
or
,
w
ith
no i
n
feas
ib
le
s
ol
u
tio
ns
(
0
)
in
s
w
a
rm
a
t
t
h
e
e
n
tire
itera
tio
n.
T
he
s
che
m
a
t
i
c
d
i
a
gr
am
f
or
t
he
itera
tive
pr
o
c
ess
pr
esente
d
in Fig
ure
5.
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
:
48
–
57
54
F
i
gur
e
5.
S
c
hem
a
tic
d
ia
gr
am
f
or
P
SO
4.
S
I
M
U
L
A
TI
O
N
R
ES
U
L
T
S
Ma
tla
b
/
Simul
i
nk
s
o
ftware
i
s
util
ize
d
i
n
or
de
r
to
e
va
lua
t
e
the
p
er
form
ance
o
f
t
h
e
pr
op
o
s
e
d
d
ri
ve
sys
t
em
p
rese
nt
e
d
i
n
F
i
g
u
r
e
1
.
T
h
e
PS
O
alg
o
ri
thm
w
r
itte
n
a
n
d
t
e
s
t
e
d
usin
g
Ma
t
l
ab
m
-fi
le.
The
P
M
S
M
i
s
dr
ive
n
a
t
1
00
r
a
d/
sec
s
p
ee
d
w
h
ile
a
d
is
t
u
r
b
a
n
ce
i
n
l
o
ad
i
s
a
p
p
l
i
e
d
f
r
o
m
5
0
to
100
N
.
m
.
Th
e
sy
ste
m
s
i
m
u
l
at
ed
w
i
t
h
a
n
d
w
i
t
h
o
u
t
r
i
p
p
l
e
s
m
i
n
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
,
w
h
e
r
e
P
S
O
u
s
e
d
t
o
a
t
t
a
i
n
t
h
e
o
p
t
i
m
a
l
s
y
s
t
e
m
p
a
r
a
m
e
t
e
r
s
i
n
e
ach
t
es
t.
T
h
e
P
SO
p
a
r
am
eter
s
w
h
ic
h
use
d
dur
in
g
o
p
tim
izat
io
n
pr
oc
e
s
s
l
i
ste
d
i
n
Tab
l
e
2.
T
he
P
MS
M
pa
ram
e
ter
s
and
t
he
ob
t
a
i
n
e
d
o
p
tim
al f
i
l
ter
co
e
f
ficie
n
ts
a
re
a
s
i
l
lus
t
rate
d
in
T
ab
le
3
.
Tab
l
e
1.
P
S
O
par
am
eter
s
Var
i
a
b
l
e
n
ame
v
a
l
u
e
Var
i
ab
l
e
n
ame
v
a
l
u
e
Popula
tion
siz
e
10
M
a
x
.
i
t
e
r
a
tions
1000
1.
5
0.
95
1.
5
0.
4
1
N
o
.
o
f
c
o
ns
tr
a
i
ns
2
Tab
l
e
2.
P
MSM
para
me
t
e
rs a
nd o
p
tima
l
f
i
lte
r c
o
eff
i
c
i
en
ts
Filt
e
r
c
o
e
f
f
ic
i
e
nts
Motor pa
ram
e
t
e
r
s
,
0.
07,
0.
0
1
R
(oh
m
)
0.
0068
,
0.
66,
0.
2
L
d
(
m
H)
0
.
482
,
0.
25,
0.
2
2
L
q
(
m
H
)
0.
482
,
-0.
51,
-
0.
22
P
(
pole
s
)
4
,
-0.
04,
-
0.
25
J (
k
g
-
)
0.
0015
Ym
(
W
b
)
0.
1413
F
i
gur
e
6
a
n
d
F
i
gur
e
7
pr
e
s
e
n
t
the
p
e
r
f
o
r
m
a
nce
s
o
f
th
e
dr
i
v
e
sys
te
m
with
ou
t
a
n
d
wi
th
f
i
l
t
e
r
r
e
spec
tive
l
y.
F
ig
ur
e
6(
a
)
and
F
igur
e
7(
a)
s
h
o
w
t
he
s
pee
d
r
e
s
po
n
se
w
he
re s
peed
refere
n
ce
is
se
t
at
1
0
0
ra
d
/
s
ec
.
F
i
g
u
r
e
6
(
b
)
an
d
F
i
g
u
r
e
7
(
b
)
show
t
he
s
t
a
to
r
flu
x
r
e
s
p
ons
e
w
h
er
e
t
he
f
l
ux
r
e
f
e
r
e
nce
is
s
e
t
a
t
0.
141
3W
b.
Fi
g
u
re
s
6
(
c)
a
n
d
7
(
c)
i
ll
ust
r
at
e
t
o
rqu
e
r
es
pon
se
s
wh
ere
th
e
l
o
a
d
tor
que
c
ha
nge
d
fr
om
5
0
t
o
1
00
N
m
a
t
t
=
0.
5
sec
(
p
ar
tial
l
y
l
oade
d)
.
F
igur
e
6(
d)
a
nd
F
i
g
u
r
e
7
(
d
)
show
t
h
e
t
h
r
e
e-
pha
se
c
ur
r
e
nt
.
F
i
gur
e
6
s
how
s
a
ver
y
f
a
s
t
r
e
sp
onse
dur
in
g
star
t
i
n
g
a
n
d
l
oad
s
t
e
p
c
ha
ng
e
w
ith
a
ppr
ox
i
m
ately
z
e
r
o
st
e
a
d
y
st
at
e
erro
r
wh
e
r
e
t
h
e
f
l
ux
a
nd
t
o
r
q
u
e
p
e
rfo
rman
c
e
c
o
n
t
a
i
n
c
ons
ide
r
ab
le
r
i
p
p
l
es
a
nd
to
ta
l
har
m
onic
di
st
or
t
i
o
n
(
TH
D
)
i
n
cur
r
ent.
The
dri
v
e
s
y
s
t
em
p
er
form
an
c
e
i
nc
lu
d
i
n
g
f
i
lter
e
f
fec
t
i
s
d
e
pic
t
e
d
i
n
F
i
g
ur
e
7
at
t
he
s
a
m
e
oper
a
ti
ng
c
o
n
d
it
i
o
n
s
w
h
e
n
t
h
e
sys
t
em
oper
a
tes
w
i
th
out
f
il
ter
.
T
he
t
or
que
r
i
p
p
l
e
s
r
e
duce
d
f
r
o
m
3
.
86
t
o
1
.
0
38
N
.
m
and
the
f
l
ux
r
ip
p
l
es
r
educ
e
d
f
r
o
m
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e
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o
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h
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l
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ur
r
e
nt
wav
e
fo
r
m
i
s red
u
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f
ro
m 1
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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
Ad
ap
tive
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l
t
e
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i
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esponse w
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t fil
t
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r
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7.
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rive
r
esponse
filte
r
0
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0.
5
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i
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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
:
48
–
57
56
5.
CONCL
U
S
ION
Thi
s
p
a
p
e
r
p
re
sent
s t
h
e
app
lic
at
ion
o
f
a
d
a
pti
v
e
IIR
fi
lt
er
i
nt
e
gr
a
t
ed w
it
h F
L
C a
s
a speed
c
on
tro
l
l
e
r t
o
minim
i
z
e
t
he
t
orq
u
e
an
d
flu
x
r
i
pp
les
w
h
ic
h
c
o
min
g
from
F
L
C.
T
he
r
i
ppl
e
mi
ni
mi
zat
io
n
a
l
go
ri
th
m
u
s
e
d
t
o
up
da
te
t
he
f
il
ter
coe
fficie
n
t
s
on
li
ne
b
as
e
d
o
n
feed
ba
ck
s
ig
na
l
fro
m
the
tor
q
ue
r
i
p
ples.
T
h
e
op
t
i
m
a
l
c
o
eff
i
ci
ent
s
o
f
IIR
an
d
co
nt
rol
l
e
r
p
a
ra
me
t
e
rs
h
av
e
b
e
e
n
e
stimat
e
d
b
y
u
s
in
g
P
S
O
to
m
i
n
i
m
ize
the
tor
q
u
e
a
nd
f
l
ux
r
i
ppl
es.
Th
e
sy
st
em
b
eha
v
io
r
wit
h
a
n
d
w
i
t
h
out
t
h
e
p
ro
po
se
d
r
ipp
l
e
r
e
duc
t
i
o
n
m
et
h
od
has
bee
n
t
e
s
te
d
b
y
si
m
u
lat
i
on.
T
h
e
s
im
ula
t
i
o
n
re
su
lts
s
h
o
w
a
re
duc
tio
n
i
n
t
he
r
i
p
p
les
o
f
t
he
t
orq
u
e
a
n
d
sta
t
or
f
l
ux
ha
s
bee
n
atta
i
n
e
d
b
y
7
3
%
a
nd
6
7%
r
espec
t
i
v
e
l
y
w
i
th
r
e
s
pect
t
o
the
sys
t
e
m
p
er
forma
n
ce
w
i
t
hou
t
ripp
le
r
e
duc
t
i
on
alg
o
ri
t
h
m.
H
ow
e
v
er,
the
t
o
ta
l
harm
on
ic di
s
t
o
rt
i
o
n
in
t
he c
u
rre
n
t
wave
for
m
has
b
een
r
e
d
uc
ed
b
y
6
0
%.
ACKNOW
LEDG
E
MEN
T
S
Th
is
w
ork
is
a
p
ar
t
o
f
t
he
r
e
s
e
a
rc
h
pr
oj
e
c
t
n
u
mbe
r
5
8
53-
43
8-
1
w
hi
ch
s
upp
o
r
t
e
d
by
S
c
i
e
n
ti
fi
c
R
e
sear
ch D
ean
sh
ip,
Taif
U
n
i
v
e
rsity,
KS
A.
REFE
RENCES
[1]
Mul
d
i
Yuhendri,
A
hyanu
ardi,
Aswardi
,
“
Direct
T
orque
Control
Str
ateg
y
of
P
MS
M
E
m
p
l
oying
U
lt
ra
S
pars
e
M
a
tri
x
Converter,
”
In
tern
atio
na
l
Jour
n
a
l
of
Power
Elect
ron
i
cs
a
n
d
Dri
ve S
y
st
em (
I
JPED
S
)
,
Vol
.
9
,
No
.
1,
p
p
.
6
4
-
7
2
,
Ma
rc
h
20
18
.
[2]
M.
D
epenbrock,
“
D
i
rec
t
s
elf
-
co
ntrol
(
D
SC)
of
i
nvert
e
r-fed
ind
u
c
ti
on
m
achin
e”,
IE
E
E
T
r
ansa
c
tio
n
s
on
Power
El
ectro
n
i
c
s
v
o
l.
3
,
n
o.
4
,
p
p
.
420–4
29
,
O
ct.
1
9
8
8
.
[3]
X.
Z
han
g
a
nd
G
.
H.
B
.
F
o
o
,
"
A
Co
nst
a
nt
S
witchi
ng
F
requen
c
y-Base
d
Dire
c
t
T
o
r
q
u
e
C
o
n
t
ro
l
M
e
th
od
f
or
I
nte
r
io
r
P
e
rm
anent
-
M
a
gnet
S
y
n
c
hron
ou
s
M
o
tor
D
r
iv
es,"
i
n
IEEE/
A
SME T
r
ansa
c
t
i
o
n
s
on
M
echa
t
r
onics
,
vo
l.
2
1,
n
o.
3
,
pp
.
1
445
-14
5
6
,
J
une
201
6.
[4]
X.
W
ang
,
Z
.
W
a
ng
,
M.
C
hen
g
a
nd
Y
.
Hu
,
"Remed
ial
St
ra
tegies
o
f
T
-
N
P
C
T
hr
e
e
-
Le
v
e
l
Asym
m
e
tr
ic
S
ix
-
P
ha
s
e
P
M
SM
D
ri
ves
Based
on
S
V
M
-DTC,
"
i
n
IE
EE
Tra
n
s
a
ctio
ns
on
In
dus
tria
l Elect
ro
ni
c
s
,
vol
.
6
4
,
no.
9
,
pp
.
6
841
-68
5
3
, S
ept
.
2
01
7.
[5]
J.
W
an
ji
ku,
M
.
A.
K
han,
P
.
S
.
B
aren
dse
an
d
P
.
P
illay,
"
Infl
uen
c
e
of
S
lo
t
Op
e
n
i
n
g
s
a
nd
T
oo
th
P
ro
file
o
n
C
o
g
g
i
n
g
Torque
i
n
Ax
ial-Fl
ux
P
M
M
ac
hines,"
i
n
IEEE
Tr
ansa
c
ti
on
s
on
Ind
u
s
t
r
i
al Electr
onics
,
v
o
l
.
6
2
,
n
o
.
1
2
,
p
p
. 75
7
8
-7
58
9,
D
e
c
.
2
01
5.
[6]
R.
I
s
l
am,
I.
H
usai
n,
A
.
F
a
rdo
un
and
K.
M
cLau
ghlin
,
"P
erm
a
nent
M
ag
net
S
y
n
c
h
r
on
ou
s
M
o
to
r
M
a
g
n
et
D
esi
g
n
s
w
it
h
Sk
e
w
in
g
for
To
rq
ue
R
ipp
l
e
a
n
d
Co
gg
in
g
Torq
u
e
R
e
d
u
c
tion
,"
2
0
0
7
IE
EE Ind
u
stry Appli
c
a
t
io
n
s
An
nu
al
M
eetin
g
,
New Or
l
ean
s,
L
A, pp
. 15
5
2
-
15
5
9
, 20
0
7
.
[7]
S
h
i
noh
ara,
Y
.
In
o
u
e,
S
.
M
o
rim
o
to
a
n
d
M
.
S
a
n
a
da,
"M
a
x
im
um
T
orqu
e
P
er
A
mpe
r
e
Control
in
S
t
a
tor
F
l
ux
Linkage
S
y
n
c
hron
ou
s
F
r
am
e
f
o
r
DT
C-Ba
s
e
d
P
M
S
M
D
riv
e
s
W
i
th
out
U
sing
q
-A
xi
s
In
duct
a
nce,
"
i
n
IEEE Tra
n
sac
t
io
ns
on
I
n
d
u
s
t
r
y
A
p
p
l
i
c
at
i
o
ns
,
v
o
l
.
53,
no.
4
,
p
p
.
3
6
6
3
-3
6
7
1,
J
u
l
y-A
u
g
.
2017
.
[8]
S
.
W
ahs
h
,
Y
.
A
h
m
e
d
a
n
d
M
.
A
bd
El
A
ziz,
"
In
tell
ig
en
t
co
ntro
l
o
f
P
M
SM
d
rive
s
u
s
ing
ty
pe
-2
f
uz
z
y
,"
20
12
In
te
rn
at
io
na
l Co
nfe
r
e
n
c
e
o
n
Re
n
e
wa
ble
En
e
r
gy
Re
se
a
r
c
h
an
d
A
p
p
l
ic
a
tion
s
(IC
R
ER
A)
, Nagasak
i
,
pp
.
1
-6
, 2
01
2
.
[9]
M.
N
.
Uddin,
"
A
n
a
dapti
v
e
filter
based
torque
r
i
ppl
e
mi
ni
mi
zati
o
n
o
f
a
f
u
z
z
y
l
o
g
i
c
co
nt
rol
l
er
f
o
r
s
peed
c
on
trol
o
f
a
P
M
s
yn
chro
nous
m
o
t
or,
"
Fo
ur
ti
e
t
h IAS
An
nu
a
l
Me
e
tin
g. Co
n
f
e
r
e
n
c
e
Re
c
o
rd
o
f
the
20
05
In
du
stry
Ap
p
l
ic
at
io
ns
Con
f
eren
ce
, vo
l
.
2
.
,
Kowl
oo
n
,
H
on
g
K
o
n
g
,
pp
.
1
3
00
-13
0
6
,
20
05
.
[10]
G.
F
eng
,
C
.
Lai
an
d
N.
C
.
Kar,
"
A
Clo
s
ed
-Loo
p
F
u
zzy
-Lo
g
ic-Bas
ed
C
urrent
C
o
n
t
r
oller
f
o
r
PM
SM
T
orqu
e
Ri
pple
M
i
nimizatio
n
U
s
in
g
th
e
M
a
gn
itud
e
o
f
S
p
eed
H
a
r
m
o
n
i
c
as
t
h
e
F
e
e
d
b
a
c
k
C
on
tr
ol
S
ign
a
l,"
in
IEEE T
r
ans
ac
t
i
o
n
s
on
Ind
u
s
t
r
i
a
l
El
ectron
i
cs
, v
ol
.
6
4
, n
o. 4,
pp
.
26
42
-2
6
5
3
, Ap
r
il 20
17
.
[11]
Y.
Z
ha
n
g
a
nd
J
.
Zhu
,
"
A
No
ve
l
Duty
C
y
c
le
C
on
tr
ol
S
tra
t
e
g
y
to
R
e
du
c
e
Bo
th
T
o
r
qu
e
a
n
d
Flux
R
ipp
l
e
s
f
or
D
TC
o
f
P
e
rm
anent
M
a
gnet
S
y
n
c
hron
ou
s
Moto
r
D
r
ives
W
it
h
Swit
ch
i
ng
F
r
equ
e
ncy
Red
u
c
tio
n,
"
in
IEEE T
r
an
sa
c
tio
n
s
on
Po
wer E
l
ectr
o
n
i
cs
, v
o
l
. 2
6,
no
.
1
0
,
p
p.
30
5
5
-3
06
7, Oc
t
.
20
11
.
[12]
Y
.
Z
h
a
n
g
,
J
.
Z
h
u
,
W
.
X
u
a
n
d
Y
.
G
u
o
,
"
A
S
i
m
p
l
e
M
e
t
h
o
d
t
o
R
e
d
u
c
e
To
rqu
e
R
i
p
p
l
e
i
n
D
irect
T
orq
u
e-Co
ntro
ll
e
d
P
e
rm
anent
-
M
a
gnet
S
y
n
c
hron
ou
s
M
o
t
o
r
b
y
U
s
i
n
g
V
ect
ors
wit
h
V
ariab
le
A
mp
li
tu
de
a
n
d
An
gl
e
,
"
i
n
IEE
E
Tran
sac
t
io
ns
on
Ind
u
str
i
a
l
Ele
c
tr
on
ic
s
,
v
o
l
. 58
,
n
o. 7
, p
p.
28
4
8
-2
85
9, Ju
l
y
20
1
1
.
[13]
M
.
H
.
V
a
f
a
i
e
,
B.
M
irzaei
anDeh
k
o
r
di
,
P
.
M
o
a
ll
e
m
a
n
d
A
.
Ki
youm
ars
i,
"
M
i
n
i
mi
z
i
n
g
T
o
r
qu
e
and
F
l
ux
Ri
pples
a
nd
Im
prov
in
g
Dy
na
m
i
c
Resp
ons
e
of
P
M
S
M
Usi
n
g
a
Vo
lt
age
V
ecto
r
w
it
h
O
p
ti
ma
l
P
a
r
a
me
t
e
r
s
,
"
i
n
IEE
E
T
r
a
n
sa
c
t
i
ons
on
Ind
u
s
t
rial Ele
ctr
o
n
i
cs
, v
o
l
. 6
3,
no
. 6
, pp
.
3
8
7
6
-
38
88
, Ju
n
e 2
0
1
6
.
[14]
C
.
L
a
i
,
G
.
F
e
n
g
,
K
.
L
.
V
.
I
y
e
r
,
K
.
M
u
k
h
e
r
j
e
e
a
n
d
N
.
C
.
K
a
r
,
"
G
e
net
i
c
Al
gori
t
hm
-Based
C
u
r
ren
t
O
p
t
im
ization
for
To
rque
R
i
pple
Redu
cti
on
of
I
n
t
e
r
i
o
r
P
M
SM
s,
"
i
n
IEEE T
r
ansa
c
tio
ns
on
In
dust
r
y Ap
p
l
icati
o
n
s
,
vol.
5
3
,
n
o
.
5,
p
p
. 44
9
3
-4
50
3,
S
e
p
t.-Oc
t
.
20
17
.
[15]
K.
C
h
i
k
h
,
A.
S
aad
,
M.
K
ha
f
a
l
l
ah,
D.
Y
ou
sfi,
F
.
Z
.
Tah
i
r
i
,
M.
H
as
ou
n,
"
A
C
o
n
stant
Swit
ch
i
ng
F
r
equ
e
ncy
D
T
C
f
o
r
P
M
SM
Usi
ng
Low
S
w
it
chi
ng
Los
s
es
S
V
M
-An
E
x
p
e
rim
e
n
t
al
R
e
s
u
l
t
,
”
I
n
te
r
n
at
io
na
l
J
o
u
r
n
a
l
o
f
P
o
w
e
r E
l
e
c
tr
on
ic
s
an
d D
r
i
ve Sys
t
e
m
(
I
JPED
S
)
,
V
o
l
.
8
,
N
o.
2
,
p
p
.
5
5
8-58
3,
J
u
n
e
2
0
17
[16]
C.
X
ia,
B.
J
i
and
Y.
Y
an,
"
S
m
oot
h
S
p
ee
d
Con
t
ro
l
f
o
r
Lo
w-S
p
ee
d
H
igh
-
To
rque
P
erm
a
n
e
nt
-Mag
net
S
y
n
c
hron
ou
s
M
o
t
o
r
Using
P
ro
po
rti
ona
l
–
In
tegr
al–Res
on
ant
Contro
ll
er,"
i
n
IEEE
Tr
ans
actio
ns
o
n
Ind
u
s
t
ri
a
l
Elect
ro
ni
c
s
,
vo
l.
62,
no
.
4
,
pp
.
2
1
2
3
-2
134
,
A
pril
2
015.
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
Ad
ap
t
i
ve
fil
ter-flc
in
te
gra
t
io
n fo
r tor
que
ri
pp
l
e
s min
i
miza
ti
o
n
in pmsm
us
i
n
g
PSO (
Y
as
ser Ahm
e
d)
57
[17]
A
S
u
d
h
ak
ar,
M
V
i
j
a
ya
K
um
ar,
"
N
e
ural
N
et
wo
rk
C
on
troll
e
rs
i
n
Dir
ect
T
o
r
qu
e
Con
t
roll
e
d
S
y
n
ch
ro
no
us
M
ot
or,"
In
ter
natio
nal J
o
ur
na
l o
f
Power
Electr
onics
an
d Dri
ve S
y
stem
(
I
JPE
D
S
)
,
Vo
l.
3
,
N
o.
3
,
p
p.
3
1
1
-
32
0,
Se
pte
m
b
e
r 20
13
.
[18]
Y
e
n-S
h
i
n
L
ai
a
n
d
J
u
o
-Chi
un
Li
n
,
"
New
h
y
b
r
id
f
uzzy
c
o
n
t
r
oll
e
r
fo
r
di
rect
t
orqu
e
con
t
rol
in
du
ction
m
o
to
r
d
r
iv
es,
"
i
n
IE
EE
T
r
a
n
s
a
cti
ons o
n
Power
El
ectr
onics,
v
o
l
. 1
8, n
o
. 5
, pp
.
1
2
1
1
-
12
19
, Sep
tember
.
2
0
0
3
.
[19]
M
.
N
.
U
d
d
i
n,
"
An
A
dap
t
i
v
e-Filter-Bas
ed
T
orqu
e-Rip
p
le
M
i
n
imizat
i
on
o
f
a
Fu
zzy-L
ogic
C
ont
r
oll
e
r
f
o
r
Speed
Con
t
r
o
l
o
f
I
PM
M
otor
D
r
i
v
e
s,"
in
IE
EE Tra
n
sa
cti
o
n
s
o
n
Indust
r
y
App
l
i
c
atio
n
s
,
vol.
47
,
n
o
.
1,
p
p
.
3
50-3
5
8
,
J
a
nu
ary-F
e
bru
a
r
y
2
011
.
[20]
S.
W
AHSH
,
M
.
A
B
DEL
A
Z
I
Z
and
Y
.
AHM
ED:
“
F
u
zzy
L
ogic
Co
nt
rol
o
f
D
i
re
c
t
T
orq
u
e
Co
ntr
o
l
P
M
SM
D
r
i
ve
s
U
s
i
n
g
S
p
ace V
e
c
t
or T
echn
i
q
u
es,” in
SCIS
&
I
SIS Con
f
eren
ce
, Tok
yo
,
J
A
PA
N, p
p7
66
-7
71
,
2
0
-2
4
S
e
p
t
e
m
be
r 2
0
0
6
.
[21]
H
o
b
a
llah
an
d
I.
E
rli
c
h,
"
P
S
O
-AN
N
a
pp
roach
f
or
t
ran
s
i
e
nt
s
tabili
ty
c
on
stra
ine
d
e
c
o
no
mic
po
we
r
g
e
ne
ra
tion
,
"
IEEE
B
u
ch
ares
t P
o
we
r
T
ech
,
Bucharest,
p
p
.
1-6
, 2
0
0
9
.
[22]
K
.
D
.
H
o
a
n
g
,
Y
.
R
e
n
,
Z
.
Q
.
Z
h
u
a
n
d
M
.
F
o
s
t
e
r
,
"
M
o
d
i
f
i
e
d
s
w
i
t
c
h
i
ng-t
a
bl
e
st
rateg
y
f
o
r
r
educt
i
o
n
o
f
curren
t
h
a
rm
oni
cs
i
n
d
i
rect
t
o
r
qu
e
co
ntrol
l
ed
d
ua
l
-
t
h
ree-p
h
as
e
p
e
rm
a
n
e
n
t
mag
n
et
s
yn
c
h
ro
no
us
m
achi
n
e
d
r
ives
,"
i
n
IET
E
l
ectric Power
Ap
plica
t
i
ons
, vo
l
.
9,
n
o.
1,
pp
.
1
0
-
19
,
2
0
1
5
.
[23]
Y
.
Z
han
g
a
nd
J
.
Z
h
u
,
"
Direct
T
o
r
qu
e
Co
nt
rol
o
f
P
erm
a
nen
t
M
agnet
S
y
n
ch
rono
us
M
o
t
o
r
w
it
h
Reduced
T
orq
u
e
Ri
pp
le
a
n
d
C
o
m
m
u
t
a
ti
on
F
requ
ency
,
"
i
n
IE
EE T
r
a
n
s
a
c
t
i
ons o
n
P
o
wer
El
ectroni
cs
,
v
o
l
.
26
,
n
o
.
1,
p
p
.
2
3
5
-
24
8,
J
a
n.
201
1.
[24]
H
o
b
a
llah
and
I.
E
rli
c
h
,
"
Onlin
e
mark
et-b
ased
r
es
chedu
l
i
n
g
s
t
ra
t
egy
t
o
e
nhance
p
ower
s
yst
e
m
stabi
lity,"
i
n
IET
G
e
nerati
on, Tr
a
n
s
m
ission
&
Distribution,
v
o
l
.
6
, no
.
1
,
p
p
.
30-3
8
,
J
an
uary
201
2.
BIOGRAPHI
E
S
OF
AUT
HORS
Dr.
Yasser
Ahmed
obt
ain
e
d
h
i
s
B.S
c
.
f
r
om
T
a
n
t
a
U
ni
versity
,
E
g
y
p
t,
F
aculty
o
f
En
gi
neeri
ng,
El
ec
t
r
ical
P
ow
e
r
a
nd
Mach
in
es
d
epartm
en
t
at
1
9
99,
M
S
c
a
nd
Ph
.D.
f
ro
m
Cairo
Univers
ity,
Egy
p
t
,
Fa
c
u
lty
o
f
E
ng
in
e
e
r
in
g
a
t
2
00
6
a
n
d
2014
.
He
w
o
r
ks
a
t
E
l
e
ct
ron
i
c
Research
I
ns
tit
u
t
e
(ERI),
E
gyp
t
,
Power
El
ectroni
c
s
a
n
d
E
nerg
y
C
o
nv
e
r
s
i
o
n
d
epar
t
m
en
t
si
nce
2
001
.
H
i
s
m
a
jo
r
in
terests
are
ele
c
tri
c
d
riv
e
s,
e
le
ct
ric
and
hyb
rid
el
ectri
c
v
e
h
ic
l
e
s
,
m
od
e
l
in
g
a
n
d
si
mu
la
t
i
o
n
o
f
electri
cal s
y
s
te
ms
.
Dr.
Aym
a
n
H
oball
ah
r
ecei
ved
t
h
e
B.
Sc.
an
d
M
.
Sc.
d
e
grees
i
n
Elec
t
r
i
cal
E
n
g
i
n
eerin
g
f
r
o
m
T
an
t
a
Un
iversit
y
,
Eg
y
p
t
in
1
99
6
and
2
0
0
3
.
Sin
ce
1
998,
h
e
has
b
een
w
it
h
t
h
e
El
ectrical
P
ower
a
nd
M
achin
es
d
epar
tm
ent,
F
acu
lt
y
o
f
E
n
g
i
n
eerin
g,
U
ni
vers
it
y
of
T
ant
a/E
g
y
p
t.
H
e
co
m
p
let
e
d
h
i
s
P
h
.D.
in
e
l
ectrical
e
ng
in
e
e
ri
ng
d
epart
m
ent
f
r
om
t
he
univ
e
rsity
D
u
isburg-
Essen,
G
ermany
i
n
20
11.
H
is
P
h
.
D.
t
hes
i
s
f
o
cu
ses
o
n
t
he
pow
er
s
yst
e
m
d
yna
m
i
c
stab
ili
t
y.
E
nh
ancem
ent
utilizi
ng
artifi
c
ial
intell
igent
t
echn
i
q
u
es.
H
i
s
current
r
each
i
nterest
s
i
n
clude
p
o
w
er
s
y
s
t
e
m
stab
ilit
y
,
D
Gs,
sm
art
grid,
g
round
ing
s
y
stem
s
an
d
optim
i
zati
on
techn
i
q
u
es
.
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