TELKOM
NIKA
, Vol.11, No
.4, Dece
mbe
r
2013, pp. 69
1~6
9
8
ISSN: 1693-6
930,
accredited
A
by DIKTI, De
cree No: 58/DIK
T
I/Kep/2013
DOI
:
10.12928/TELKOMNIKA.v11i4.1039
691
Re
cei
v
ed
Jun
e
26, 2013; Revi
sed Aug
u
st
17, 2013; Accepted Sept
em
ber 8, 201
3
Study of an Improved Fuzzy Direct Torque Control of
Induction Motor
Dong Ming*
1
, Tang Yong-qi
2
, Song Hai-liang
1
, Wang Bing-jie
2
1
Huna
n Univ
er
sit
y
of techn
o
l
o
g
y
, Z
huz
hou, C
h
in
a
2
Huna
n Institute of Engi
n
eer
in
g, Xi
angta
n
, C
h
in
a
*Corres
p
o
ndi
n
g
author, e-ma
i
l
: 3309
02
740
@
qq.com
Abs
t
rak
Kend
ali t
o
rsi l
angs
un
g konv
ensi
ona
l p
a
sti
akan
men
gha
silkan
riak tor
s
i kare
na c
a
ra
estima
s
i
fluks-nya. Unt
u
k me
ngatas
i mas
a
l
ah
ini, strategi kend
al
i
baru disaj
i
ka
n pada
mak
a
l
ah ini. Strateg
i
ini
me
ngk
o
m
bi
nas
ikan k
end
ali
pe
mb
ag
ian s
e
kto
r
tegan
ga
n vek
t
or dan k
end
al
i
logik
a
fu
z
i
pa
da p
eng
en
dal
i
a
n
torsi langs
un
g tradisi
ona
l. Pada mod
e
l ini, l
ogik
a
fu
z
i
me
n
gga
bu
ngka
n
sudut fase dari
fluks, galat fluks
dan g
a
lat torsi
sebag
ai varia
bel fu
z
i
da
n me
ngk
elask
a
n
variabe
l fu
z
i
i
n
i, agar men
g
opti
m
a
l
kan p
ili
h
a
n
vektor rua
ng t
ega
ng
an, da
n
pad
a saat ya
n
g
sa
ma re
gu
la
tor PID tradisi
ona
l di
ga
ntika
n
de
nga
n re
gu
lator
fu
z
i
. Has
il si
mulasi
me
nu
nju
kkan ad
anya
perb
a
ika
n
yan
g
signifik
an at
as tangg
apa
n torsi, peng
ura
nga
n
riak torsi d
an
strategi in
i
me
mi
liki ki
nerj
a
y
ang l
e
b
i
h b
a
ik
pada k
o
n
d
isi
din
a
m
is d
an stabil, terut
a
ma
di
daer
ah kec
epa
tan rend
ah.
Ka
ta
k
unc
i
:
torque ri
ppl
e; dire
ct torque contr
o
l; fu
zz
y
co
ntro
l; vectors subdi
vision; fu
zz
y
sp
eed re
gul
ator
A
b
st
r
a
ct
The conv
enti
o
nal
direct torq
u
e
cont
ro
l w
ill i
n
evitab
ly pro
duc
e torqu
e
rip
p
l
e
beca
u
se
of its w
a
y of
flux estimates.
F
o
r the purpo
se of handli
n
g
this probl
e
m
, a new
control
strategy w
a
s p
r
esente
d
in this
pap
er. T
h
is strategy co
mb
ine
d
subd
ivid
es control w
i
th
volt
age vector a
n
d
fu
zz
y
log
i
c co
ntrol in trad
itio
na
l
direct torq
ue c
ontrol. In th
is
mo
de
l, the fu
zz
y
l
o
g
i
c
co
mb
i
ned th
e p
has
e
ang
le of th
e flu
x
, the flux err
o
r an
d
torque error a
s
fu
zz
y
vari
ab
l
e
s and classifi
ed these fu
zz
y
variabl
es, in order to opti
m
i
z
e
the cho
i
ce of
voltag
e spac
e vector, and th
e same time the traditi
on
al PID regul
ator i
s
repl
ac
ed by
a fu
zz
y
re
gul
ator.
Simulati
on res
u
lts show
that,
a great
improv
ement torque r
e
spo
n
ses , a gr
eat reductio
n
of torque rippl
e
s
is
achi
eved
and t
he strategy h
a
s
a better dyna
mic a
nd
stea
dy
performanc
e, espec
ial
l
y in lo
w
-
speed are
a
.
Ke
y
w
ords
:
torque ri
ppl
e; dire
ct torque contr
o
l; fu
zz
y
co
ntro
l; vectors subdi
vision; fu
zz
y
sp
eed re
gul
ator
1. Introducti
on
Dire
ct torque
control (DT
C
) technology wa
s a new high performan
ce variabl
e freque
ncy
spe
ed-re
gulat
ing syste
m
a
fter vect
or co
ntrol.
The DT
C
is cha
r
a
c
te
rize
d by the
absen
ce of PI
regul
ators, co
ordin
a
te tran
sform
a
tion
s, curre
n
t regul
ators an
d PWM sign
als. The DT
C is a kind
of dire
ctly on the analysis of t
he sta
t
or co
ordi
nat
e of in an
indu
ction mot
o
r drive of the
mathemati
c
al
model. Acco
rding to
a m
o
ment of torque e
r
ror
e
, and the stato
r
f
l
ux error e
,
sele
ct a voltage of spa
c
e
vector to limit
torque e
r
rors and
stator
flux erro
rs
wi
thin a relativ
e
ly
small
zon
e
. This
cont
rol
mode h
a
s
a
fast re
spo
n
s
e a
nd a
si
mple st
ru
cture. Ho
wever,
this
method
ha
s
a majo
r d
r
a
w
back i
s
that t
he torque
rip
p
le, be
cau
s
e
in a
sampli
ng
peri
od the
di
rect
torque
control can only cho
o
se one
swit
chin
g vector voltage
to control th
e amplitude
and
rotation
spe
e
d
of the stato
r
flux [2], which i
s
not
the
expecte
d vector voltage. T
h
is i
s
a key why
the stator a
n
d
torque
control have a larg
e deviation.
Acco
rdi
ng to the conve
n
tio
nal dire
ct torque
control o
f
defects a
n
d
deficien
c
ie
s,
and to
improve the
perfo
rman
ce
of dynamic resp
on
se of
convention
a
l
direct torq
u
e
control, so
me
studie
s
h
a
ve
been
ca
rri
ed
out in the
pa
st to increa
se t
he respon
se
spe
ed of to
rq
ue ste
p
cha
n
ge.
The literatu
r
e [3] has de
veloped a m
e
thodol
ogy
o
f
incre
a
si
ng
the sele
ction
of the voltage
vectors to 12
. But in this literature, the two hy
steresis cont
rollers
is
u
s
e
d
in
the system, t
h
e
torque ri
pple
in low speed area is still great. T
he literature [4] has used fuzzy logic control to
repla
c
e th
e h
y
stere
s
is to create th
e swit
che
s
a
c
cordi
ng to the exa
c
t value of th
e torqu
e
an
d
flux
errors and h
a
s su
cce
ssful
ly decrea
s
e
d
the tor
que ripple
s
. However the conve
n
tional PID was
still use
d
in speed
-loo
p, the spe
ed fo
llo
w wa
s not go
od eno
ugh in
low-sp
eed a
r
ea.
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 11, No. 4, Decem
ber 20
13 : 691 – 698
692
This pa
per a
i
med to take
advantage of fu
zzy logi
c techni
que to solve the probl
em
s
mentione
d ab
ove. This pap
er is used a fuzzy l
ogic co
ntrol to repla
c
e conventio
n
a
l PID of speed-
loop. Thi
s
fu
zzy logi
c control ca
n adj
ust
torque
re
al time a
cco
rdi
n
g
to the sp
eed
error
and th
e
spe
ed rate of
chan
ge. And
then anothe
r fuzzy logi
c combine
s
the
pha
se an
gle of the flux,
the
flux error an
d
torque erro
r as fuzzy variable
s
and cla
ssifi
cated the
s
e fuzzy variable
s
, in orde
r to
optimize th
e choi
ce of voltage spa
c
e ve
ctor. Thi
s
sy
stem has a g
r
eat flux and torqu
e
follow,
and
improve
s
the
robu
stne
ss of the system a
l
so.
2. Principle
s
of DTC
The coordinat
e system of t
he th
re
e-p
h
a
s
e stato
r
ele
c
tromag
net
ic t
o
rqu
e
of the indu
ction
motor mathematical model:
(1)
whe
r
e
s
and
r
are the stato
r
and roto
r flux vectors,
p
n
is th
e numbe
r of the pole p
a
irs,
L
is the synthe
sis of a variety of inductan
c
e, and
is the angle of the stator flux vector and
the rotor flux vector.
From (1)
we
can get the
con
c
lu
sion t
hat t
he elect
r
omagn
etic to
rque of the i
ndu
ction
motor is de
ci
ded by the multiplicat
ion
cross of stator flux and ro
tor flux, and the
amplitude of the
stator flux is a con
s
tant value,
the ampli
t
ude of rotor
flux is us
ually
determine
d by the load, so
the electrom
agneti
c
torqu
e
of the induction motor
i
s
decide
d
by comp
osed of
a stator flux
and
the roto
r flux angle.
Howe
ver the an
gle
of roto
r flux
can
not be m
u
tated, we
can only u
s
e t
he
voltage vecto
r
to co
ntrol th
e angle
of the stator fl
ux t
o
cont
rol the
electroma
gne
tic torqu
e
. Ma
ke
the stator flux
walki
ng thro
ugh the ad
dition of si
x voltage vecto
r
s a
nd make the stator flux sto
p
throug
h the addition of two
zero vecto
r
s. And we c
an
use this meth
od to make the stator flux to
run an
d stop
repe
atedly to achi
eve the c
ontrol of the e
l
ectro
m
ag
neti
c
torqu
e
.
2.1 Space v
o
ltage v
ector s
y
nthesis and flux interv
al subdiv
i
sion
In orde
r to improve the
control pe
rformanc
e of the system effe
ct, we ca
n u
s
e spa
c
e
vec
t
or pulse width modulation (SVPWM), the s
y
nt
hes
i
s
voltage vec
t
or
c
a
n be
any direc
t
ion at
any amplitud
e. Based o
n
this theory
we can
sy
nthesi
z
e 1
2
workin
g voltage vecto
r
s: six
traditional
wo
rkin
g voltage
vectors a
n
d
six sy
nthesi
z
ed
workin
g voltage vecto
r
s (30 de
gre
e
s
each
voltage vector).
The new synt
he
si
zed volta
ge v
e
ctor is
sh
ow
n in Fig
1.Th
e ba
sic volta
g
e
vectors are solid line
s
and
the synthe
sized voltage ve
ctors are da
shed line
s
.
Figure 1. Synthesi
z
e
d
voltage vecto
r
31
31
sin
22
n
ps
p
s
Te
n
r
n
r
LL
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
1693-6
930
Res
e
arch of NiMH Battery M
odeling and Simulation Bas
ed on Linear ... (Chang-hao Piao)
693
3. Fuzzy
controller sch
e
m
atics and d
esign
Fuzzy co
ntrol
method i
s
a
kind of intell
igent
co
ntrol;
it can be i
n
accordan
ce
with the
controlle
r’s in
put automati
c
ally adju
s
t the corr
e
s
pon
ding
control
strategy, en
a
b
ling fa
ster a
n
d
more
accu
rat
e
ly mimic the
experie
nce
of experts
, e
s
pe
cially it can deal
with
impre
c
i
s
e mo
del
and un
ce
rtain
t
ies. In this fu
zzy
controller, the flux erro
r
E
, the torque
error
Te
E
and the
angle
of flux
are the
inputs, and t
he output is t
he sig
nal of p
o
we
r switch
e
s
.
The Figu
re 2
is sh
own that the schemat
i
c
of fuzzy di
rect torq
ue co
ntrol.
Figure 2 Fuzzy c
ontr
o
ller
sc
hematics
3.1 The opti
on of fu
zz
y
variables
Fuzzy control
inputs are the corre
s
po
n
d
ing
fuzzy langua
ge, therefore we ne
e
d
to
b
e
conve
r
sed the flux erro
r, the torque de
viation,
and the flux angle to
the corre
spo
ndin
g
fuzzy
langu
age. According to th
e req
u
iremen
ts of the cont
rol, we
divide
the flux error into three
fu
zzy
sets:
P for p
o
s
itive, N fo
r n
egative, Z for ze
ro.
We
divi
de the to
rqu
e
error in
to five fuzzy sets:
PB
for positive big, PS for positive
small, NB for negative big, NS fo
r
negative sma
ll, Z
for zero. In
orde
r to m
a
ke the control
actually, we
divi
de the a
n
gle of the flu
x
into 12 sections
(
11
2
).
The output of
fuzzy co
ntrol
is 12
synthe
sized
workin
g voltage vecto
r
s
Figure 3 Flux deviation me
mbershi
p
dist
ribution
Figure 4 Torq
ue error m
e
m
bership di
stri
bution
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 11, No. 4, Decem
ber 20
13 : 691 – 698
694
Figure 5 flux angle me
mbe
r
shi
p
dist
ribut
ion
Figure 6 fuzzy output members
h
ip dis
t
r
i
bution
3.2 The rule of fu
zzy
control
Fuzzy co
ntrol
inputs ate th
e flux deviation, t
he torque
deviation, flux angle, the ou
tput is
the corre
s
p
o
n
d
ing switchin
g sign
al. The rule
s of fuzzy control a
r
e:
:,
,
ii
T
e
i
i
i
k
R
if
E
A
E
B
and
N
t
he
n
n
u
Whe
r
e
i
A
s
t
ands
for
the fuzzy s
e
ts
of the flux er
r
o
r
,
i
B
s
t
ands
for the fuz
z
y
sets
of the
torque e
r
ror,
i
C
stand
s for the
fuzzy set
s
of the angle of flux,
i
N
stan
ds fo
r the fuzzy set
s
of
power switch
es si
gnal.
Referen
c
e vo
ltage vector a
nd flux angle
control expe
ri
ence ca
n be
summ
ed up 1
80
rule
s. The tab
l
e 1 is sh
own the rule
s of fuzzy control
4. The desig
n
of the fuzzy
speed reg
u
lator
For p
r
e
c
ise
control of spe
ed, we mu
st
add a spee
d
feedba
ck lo
op. The conv
entional
spe
ed regulat
or is
conve
n
tional PI
D cont
rol, but wh
en
the exter
nal environ
ment cha
nge
s
o
r
o
u
r
control req
u
irements
chan
ge, t
he PID
para
m
eters cannot be real
-t
ime cha
nge
s as our
cont
rol
requi
rem
ents need. It has a very serio
u
s impa
ct on
the control requireme
nt we want. In this
pape
r, we use fuzzy PI replace
the co
nventional PID cont
rolle
rs,
so that the
para
m
eters o
f
PI
can a
d
ju
st au
tomatically the external en
vironme
n
t an
d the cont
rol requireme
nt of the system.
In this pape
r,
a rate of sp
eed e
rro
r an
d spe
ed e
rro
r are fu
zzy speed
cont
roll
er input
s
and outp
u
t of fuzzy controller is t
he
corre
s
po
ndin
g
PI param
eters.
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
1693-6
930
Res
e
arch of NiMH Battery M
odeling and Simulation Bas
ed on Linear ... (Chang-hao Piao)
695
Table 1. Fu
zzy control rule
table
E
Te
E
1
2
3
4
5
6
7
8
9
10
11
12
N
PL
5 6 7
8
9
10
11
12
1
2
3
4
PS
6 7 8
9
10
11
12
1
2
3
4
5
ZE
7 8 9
10
11
12
1
2
3
4
5
6
NS
8
9
10
11
12
1 2 3 4
5
6
7
NL
9
10
11
12
1 2 3 4 5
6
7
8
Z
PL
4
5
6 7 8 9
10
11
12
1
2
3
PS
6 7 8
9
10
11
12
1
2
3
4
5
ZE
0
0
0 0 0 0 0 0 0
0
0
0
NS
10
11
12
1 2 3 4 5 6
7
8
9
NL
10
11
12
1 2 3 4 5 6
7
8
9
P
PL
3
4
5 6 7 8 9
10
11
12
1
2
PS
2
3
4 5 6 7 8 9
10
11
12
1
ZE
1
2
3 4 5 6 7 8 9
10
11
12
NS
12
1
2 3 4 5 6 7 8
9
10
11
NL
11
12
1 2 3 4 5 6 7
8
9
10
Figure 7 Spe
ed error m
e
m
bership di
stri
butio
n
Figure 8 Rate
of speed e
r
ror memb
ershi
p
distrib
u
tion
The rul
e
s of fuzzy spe
ed regulato
r
are:
whe
r
e
i
A
stand
s for the fuzzy
sets of the sp
eed erro
r,
i
B
s
t
ands
for the fuzz
y s
e
ts
of the rate of
spe
ed erro
r,
ki
stand
s for the
fuzzy set
s
of the prop
ortio
n
para
m
eters,
kp
stan
ds fo
r the fuzzy
sets of integ
r
ation paramet
ers.
:,
,
,
ii
i
i
i
i
f
Re
Ae
B
t
h
e
n
k
i
I
k
p
P
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 11, No. 4, Decem
ber 20
13 : 691 – 698
696
Figure 9. PI param
eters m
e
mbe
r
ship di
stributio
n
The Tabl
es 2
-
3 are sh
own the ru
le
s of fuzzy spee
d co
ntrol.
Table 2 Th
e rules of kp
e
e
NB NM NS
ZE
PS
PM
PB
N
B
M S M S M
B
Z
B
M B
Z
B M
B
P
B
M B
Z
B M
B
Table 3. The
rule
s of ki
e
e
NB NM NS
ZE
PS
PM
PB
N
Z
S M B
S
S
Z
Z
Z
S M B
B
S
Z
P
Z
M B
B
S M
Z
5 .Sy
s
tem Simulation an
d Analy
s
is
The pa
ramet
e
rs of the ind
u
ction moto
r
are:
-
Pn=
3
.7k
w
,
U
n=
460V,f=
50Hz
,
-
Stator Re
sist
ance: 0.435
,
Stator Induct
ance:0.004
H,
-
Rot
o
r
Re
sist
a
n
ce:
0.
81
6
,
Rotor Induc
t
anc
e
0.004H,
-
Mutual Indu
ctance: 0.069
H,
Sampling period of sy
ste
m
:50
-
Moment of in
ertia: 0.189
kg
.m2 Pole pairs: 2.
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TELKOM
NIKA
ISSN:
1693-6
930
Res
e
arch of NiMH Battery M
odeling and Simulation Bas
ed on Linear ... (Chang-hao Piao)
697
Figure10. Fu
zzy control direct
torque
co
ntrol sy
stem model
6.2
Simulation and An
aly
s
is
Figures 1
1
a
nd 12 sho
w
the perfo
rma
n
c
e
s
of
the sp
eed re
sp
on
se of the motor at 100
rad/sec
and no load for
conventional di
rect torq
ue control and fuzzy direct torque cont
rol before
t=0.5s.An
d
it clearly sho
w
n t
hat the
fuzzy dire
ct torque c
ontrol has no u
ndersh
oot an
d it
respon
se m
o
re quickly than
conv
entio
nal
direct torque
control.
Figure 11. Co
nventional
co
ntrol sp
eed
respon
se
Figure 12. Fu
zzy control sp
eed re
sp
on
se
Figure 13. Co
nventional
co
ntrol torq
ue
respon
se
Figure 14. Fu
zzy control torque
re
spo
n
se
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ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 11, No. 4, Decem
ber 20
13 : 691 – 698
698
Figure 15. Co
nventional
co
ntrol flux resp
onse
Figure 16. Fu
zzy control flux respo
n
se
Figures 1
3
a
nd 14
sho
w
the perfo
rma
n
ce
s of
the torqu
e
re
sp
on
se of the m
o
tor at
100rad/sec.
Whe
n
the mo
tor start
s
, the
starting
to
rq
ue and to
rqu
e
ripple i
s
m
u
ch
smalle
r than
conve
n
tional
method
s, so
that it very h
e
lpful
to redu
cing th
e
start
i
ng current
of the moto
r a
nd
device syste
m
.
Figures 1
5
and 16 sh
ow
the perfo
rm
ances
of th
e flux ripple.
The fu
zzy di
rect
torque
cont
rol
has very goo
d static an
d d
y
namic respo
n
se.
6. Conclusio
n
Dire
ct torque
cont
rol i
s
a
mode
rn hi
gh-per
fo
rman
ce
AC speed
co
ntrol meth
od.
A fuzzy
logic ba
se
d
direct torqu
e
control
system
is impl
emented in this pape
r to improve the
perfo
rman
ce
of conventio
nal DT
C system. This
co
ntrolle
r enabl
es to the system to cho
o
se
optimal stator voltage vectors p
r
od
uci
n
g the most suitable rate o
f
torque cha
n
ge acco
rding
to
the 12 fu
zzy variabl
es. S
i
mulation
re
sults hav
e
sh
own th
e effe
ctivene
ss
of the p
r
opo
sed
method. The
fuzzy controll
er makes
so
me improvem
ent in redu
cin
g
torque ri
ppl
es, faster torque
response, and stability
at very low speed.
Referen
ces
[1]
Li Su. Direct to
rque co
ntrol of
ind
u
ction mo
t
o
r. Beijin
g: Mechan
ical In
dustr
y Press. 19
94.
[2]
Z
hang Ji
yo
ng, Liu
Xia
n
x
in
g, W
ang Demi
ng.
Improved
dire
ct torque control for inductio
n
motor sensor
less driv
e.
Co
mp
uter Meas
ur
ement & Contr
o
l.
2004; 1
2
(3)
:
1-8.
[3]
Hua
ng Z
hen-
xi
ang, Guo Yan
-
w
e
n,L
i
ao Jia
n
-
xi
a.
Applic
atio
n of F
l
ux Section Sub
d
ivi
d
i
n
g Control in
DTC
. Proceed
i
ngs of the CSU
-
EPSA. 2008.
[4]
He D
e
-hu
a
, Li
u
Guo-ron
g
, W
e
i
T
i
n-ghua. Stu
d
y
of T
o
rque R
i
ppl
e Mi
nimiz
a
tion for
Direct T
o
rqu
e
Co
ntro
l
of Inductio
n
Motors.
Drive an
d control
. 20
11
; 10.
[5]
Xi
ao A
n
-
w
e
n
,
She Z
h
i-ti
ng. A
pplic
atio
n of F
u
zz
y
Co
ntrol T
e
chn
o
lo
g
y
i
n
th
e Direct T
o
rqu
e
Co
ntrol of
an
Inductio
n
Moto
r.
Journal of C
han
gsh
a
Co
mmu
n
ic
ations U
n
iversity
. 20
05;
21(2): 1-10.
[6]
Gao Shen
g-
w
e
i, W
ang You-H
ua, Cai Yan, Z
han
g Chu
ang.
Rese
arch on Red
u
cin
g
T
o
rque Rip
ple o
f
DTC Fu
zz
y
L
o
g
ic-b
ased
. 2
0
1
0
2n
d Internati
ona
l Co
nferenc
e on
Adv
anc
ed
Computer
Con
t
rol (ICACC)
.
201
0; 2: 631-6
34..
[7]
YAN Wei-She
ng, LIN Hai, LI Hon
g
, Yan Wei.
Sensor less D
i
rect T
o
rque C
ont
rol
l
ed Driv
e of Brushless
DC Motor bas
ed on F
u
zz
y
Log
ic
. 4th IEEE Conferenc
e on Industria
l Electron
ics an
d Applic
atio
ns
200
9. ICIEA 2009: 34
11-
341
6.
[8]
T
u
rki Y. Abdall
a
, Haroutio
n Antranik Hair
ik, Adel M. Dakhil
.
Minimi
z
a
t
i
on
of T
o
rque Rip
ple in DT
C of
Inductio
n
Moto
r Using F
u
zzy Mode Duty
Cycle Co
ntrol
l
e
r
. 201
0 1st Internatio
nal C
o
nferenc
e on
Energ
y
, Po
w
e
r and Control
(EPC-IQ). 2010: 237-2
44.
[9]
Nur Hakima
h Ab Aziz, Azhan Ab Rahman.
Simul
a
tio
n
on
Simul
i
nk AC4
Model (200
hp
DT
C
Inductio
n
Motor Drive) using Fu
zz
y
L
o
g
ic Contro
ller
.
Internationa
l Confer
ence o
n
Computer Ap
plicati
ons an
d
Industria
l Elect
r
onics (I
CCAIE
). 2010: 55
3-55
7.
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