TELKOM
NIKA Indonesia
n
Journal of
Electrical En
gineering
Vol. 13, No. 1, Janua
ry 201
5, pp. 106 ~
113
DOI: 10.115
9
1
/telkomni
ka.
v
13i1.700
4
106
Re
cei
v
ed Au
gust 29, 20
14
; Revi
sed
No
vem
ber 9, 20
14; Accepted
De
cem
ber 4,
2014
A Review on Speed Control Techniques of Separately
Excited DC Motor
Mahmoud Z
a
dehb
agheri
*, Rahim Ildarabadi, Majid Bagha
ei Nej
a
d
F
a
cult
y
of Elec
trical, Dep
a
rtment of Electrica
l
E
ngi
neer
in
g, Hakim Sa
bzev
ari Univ
ersit
y
,
Sabzev
ar, Iran
*Corres
p
o
ndi
n
g
author, e-ma
i
l
: mzadeh
ba
gh
eri@gm
ail.com
A
b
st
r
a
ct
Nowadays, many moving
devices
rece
ive
their
en
ergy f
r
om a
battery.
DC
motor is
the
mos
t
suitable
option for thes
e syst
em
s. I
n
addition, the s
p
eed
of
these
motors
can be controlled easily
and in
the extensiv
e rang
e. Intelli
ge
nt control meth
ods are w
i
de
ly
used in
co
ntro
l of the industri
a
l proc
esses d
u
e
to si
mpl
i
city
an
d h
i
gh
ca
pab
ili
ties. In this
pa
per, the
fu
zz
y
resistanc
e sp
e
ed c
ontrol
l
er
h
a
s b
een
d
e
sig
n
e
d
and pr
esent
ed
for DC motor
.
T
h
is controll
er stabili
z
e
s spee
d of motor
in the desir
a
b
le p
a
th des
pi
te
chan
ges of lo
a
d
torque or ch
ang
e of motor
ele
m
e
n
ts. O
ne of the other feat
ures of thi
s
controll
er is the
mu
ltivari
a
te o
b
j
ective functi
on
w
h
ich is abl
e
to s
upply
dyna
mic
a
l b
ehav
ior
of the motor.
Rapi
d resp
ons
e,
per
ma
nent fau
l
t and low
overs
hoot are a
b
o
u
t
the other a
d
va
ntages of this
meth
od.
Ke
y
w
ords
:
resistanc
e sp
e
ed co
ntrol, fu
zz
y
l
o
g
i
c, mul
t
ivariate
ob
ject
ive functi
on,
DC
mac
h
in
e
,
PID
control
l
er
Copy
right
©
2015 In
stitu
t
e o
f
Ad
van
ced
En
g
i
n
eerin
g and
Scien
ce. All
rig
h
t
s reser
ve
d
.
1. Introduc
tion
DC d
r
ive
s
a
r
e wi
dely ap
plied in the
fields
such
as
controllab
l
e variabl
e, suitabl
e
adju
s
tment o
f
speed an
d different wo
rking stat
es
[1-2]. DC mot
o
rs a
r
e of the first electri
c
al
motors in th
e indu
stry,
which
are a
p
p
lied in
high
powers
a
nd broa
d
voltag
e
ra
nge
s an
d
in
different n
o
mi
nal spee
ds
d
ue to si
mpli
ci
ty of
controlli
ng thei
r spee
d [3]. The me
thod which h
a
s
been
con
s
id
e
r
ed fo
r co
ntro
lling the spee
d in this p
ape
r is
spe
ed co
ntrol with volt
age
control. To
control voltag
e, cla
ssi
cal
control m
e
tho
d
s
(PID)
and
mode
rn
cont
rol meth
od
s (fuzzy lo
gic) a
r
e
use
d
[4-5]. Armature voltage co
ntrol m
e
thod al
ways has a maxi
mum acce
ssi
b
le spe
ed. T
h
is
maximum sp
eed is o
b
tain
ed for maxim
u
m permi
ssib
le
voltage. In fact, a type of remote co
ntrol
applied in
DC motor pl
ays
main role in
optimal
pe
rformance of the
motor. Fu
zzy cont
rol meth
od
is one of the
suitable met
hod
s for co
n
t
rol of
nonlin
ear sy
stem
s [6]. Fuzzy system
s provid
e
system
s ba
sed on a
set
of lingual
rul
e
s
with
a no
nlinea
r map
p
i
ng. Since im
plementatio
n
of
mappin
g
s i
s
not ea
sy, fuzzy syste
m
s can b
e
fo
und in
a b
r
oad
spe
c
tru
m
of engi
ne
ering
appli
c
ation
s
[7]. Evident chara
c
te
risti
c
of the fu
zzy
controlle
rs is i
ndep
ende
nce
of the contro
ller
para
m
eters i
n
state spa
c
e and
c
ont
rol
l
ed process
variable
s
. Of
the other a
d
vantage
s of this
controlle
r are
high re
sp
on
se spee
d, lo
w co
mple
xity and volume
and controlla
bility of the motor
spe
ed in broa
d rang
e of the desi
r
ed
refe
ren
c
e spee
ds [1, 3].
2. Modeling of Separ
a
tel
y
excited DC motor
Schem
atic di
agra
m
of se
p
a
rately excite
d DC m
o
tor i
s
sho
w
n in Fig
u
re 1 a
nd rel
a
tions of
this motor in
clude [8-9]:
Figure 1. Sch
e
matic dia
g
ra
m of sepa
rate
ly excited DC motor
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
2302-4
046
A Revie
w
on
Speed Control Tech
niqu
e
s
of
Separate
l
y Excited… (Mahm
oud Za
dehb
aghe
ri)
107
V
1
=
V
f
=
V
a
=
E
c
+
I
a
R
a
(1)
I
1
=
I
a
+
I
f
(2)
Ec
=
K
Φ
n
(3)
So that V1 is terminal volt
age, Vf is ex
cita
tion volta
ge, Va is
armature volta
ge, Ec i
s
back ele
c
tro-motive
force in v
o
lt, K
is fixed coefficient
,
Φ
is
m
agneti
c
flux of each
pole
in
Web
ber,
n is
rotational
spe
ed in
r/min, Ra is
arm
a
ture
re
sista
n
ce, I1 is li
ne
cu
rre
nt in amp
e
re, If
is
ex
citation current , Ia is
armatu
re current.
It can be sho
w
n that chang
e of load causes
cha
n
ge
of line
cu
rren
t (I1)
and
cha
nge
of a
r
mat
u
re
curr
ent (Ia).
Spe
ed of motor
i
s
cal
c
ulated acco
rd
ing
to Relation (4) in case line voltage, armatu
re
current, field flux and fixed coeffici
ent are
specified.
K
R
I
V
n
a
a
1
c
K
E
(4)
No
w, spe
ed o
f
motor can b
e
obtaine
d in excitation current by su
sbti
tting Relation
(2) in (4).
K
R
I
R
I
V
n
a
f
a
1
1
(5)
With Formula
(4), ratio of speed
s can be
obtained in
t
w
o differe
nt functio
nal stat
es a
s
follows:
new
old
cold
cnew
old
new
E
E
n
n
(6)
In ca
se l
oad
is a
pplied
o
n
axis
of the
unadj
uste
d
motor, line
current an
d a
r
mature
current will increase. On the other hand, back el
ectro-motive force
is
reduced considering
that
spe
ed of motor ha
s direct
relation
with
back ele
c
tro
-
m
o
tive
force
and reve
rse relation
ship wi
th
discha
rge
[1]. Goal
of sp
e
ed control is
to return
spe
ed of moto
r t
o
a d
e
si
red
referen
c
e
spe
e
d
automatically due to
ch
an
ges
of load.
T
he spe
ed control system
has
bee
n
a
p
p
lied
with
Ma
tlab
Simulink)
sof
t
ware
ela
borated on
a
se
parately
excit
ed DC m
o
tor with n
o
minal
voltage of 3
00
volts and n
o
m
inal ro
und
of 1400 rpm
and al
so for
para
m
eters o
f
the motor whi
c
h a
r
e giv
en in
Table 1.
3. Principles of Fuzz
y
Lo
gic
The
wo
rd”fu
z
zy” in
di
ction
a
ry me
an
s v
ague, i
ndi
stinct o
r
ina
c
cu
rate an
d
cha
o
t
ic [10].
Fuzzy syste
m
s a
r
e the
systems
with
accurate def
i
n
ition and fu
zzy
control is a spe
c
ial type of
nonlin
ear
con
t
rol whi
c
h i
s
a
c
curately d
e
fined a
s
well. Although fu
zzy systems
de
scribe
un
cert
ain
and u
n
specifi
ed ph
enom
e
na, fuzzy the
o
ry is a
n
a
c
cu
rate the
o
ry [
10]. In summ
ary, startin
g
p
o
int
of con
s
tru
c
tio
n
of a fuzzy system is to obtain a
set of if-then rul
e
s from kno
w
le
dg
e the experts
or
kno
w
le
dge
of the
studied
field. The
next
stag
e is
com
b
ination
of th
ese
rul
e
s in a
sin
g
le
syste
m
[11]. Differen
t
fuzzy syste
m
s use different pr
i
n
cipl
e
s
and meth
o
d
s for combi
nation of these
rule
s. We the
n
mentio
n
so
me of the
co
nce
p
ts
and
d
e
finitions rel
a
ting to fu
zzy l
ogic.
Definition
(1) of fu
zzy
set: here, we
a
s
sume that X
is refe
ren
c
e
set and i
n
cl
u
des all
po
ssi
b
l
e eleme
n
ts a
n
d
membe
r
s i
n
discu
ssi
on
wi
th the de
sire
d user. A cl
a
ssi
c
set A is
spe
c
ified i
n
referen
c
e
sp
a
c
e X
with a func
tion
μ
A
(x) whi
c
h
can h
a
ve
only two val
ues
(0,1
) but
a fuzzy set
A is sp
ecifie
d in
referen
c
e sp
ace
X with a function
μ
A
(x) whi
c
h ta
ke
s
values i
n
inte
rval [0,1]. Th
erefo
r
e, a fu
zzy
gene
rali
zatio
n
set is a cl
assic
set whi
c
h pe
rmits
membe
r
ship
function to take a
n
y value in
interval [0,1]. In fact, we se
e that there is not
hing ambi
guou
s for fu
zzy sets b
u
t fuzzy set is a set
with a contin
uou
s memb
e
r
shi
p
fun
c
tion
[11-12]. A fuzzy set A ca
n be shown i
n
X with a se
t o
f
orde
re
d pairs x and its membershi
p
value ca
n be sh
own a
s
follo
ws:
X
x
X
x
A
A
,
.
Definition (2):
Union of two
fuzzy set
s
: u
n
ion A,B is a fuzzy set in
X which i
s
sh
own
with A
∪
B
and i
s
define
d
with
mem
b
ership
functio
n
.
x
x
x
B
A
B
A
,
max
. Definition (3
): inte
rsecti
on
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ISSN: 23
02-4
046
TELKOM
NI
KA
Vol. 13, No. 1, Janua
ry 2015 : 106 –
113
108
of two fuzzy
sets: interse
c
tion A,B of a
fuzzy set is X which ha
s been sho
w
n with A
∩
B and is
defined with membe
r
ship function.
x
x
x
B
A
B
A
,
min
. Definition (4
): compl
e
me
nt of
fuz
z
y
s
e
t: complement of fuzz
y s
e
t A is
fuz
z
y
s
e
t
A in
X of whi
c
h m
e
mbe
r
ship fu
nction i
s
d
e
fin
ed
as
x
x
A
A
1
. To
cont
rol fu
zzy l
ogi
c, othe
r
ca
ses su
ch as fuzzy rule
s and
fu
zzy
combi
nation
(fuzzy infe
re
nce
)
are
al
so impo
rt
ant.
A fuzz
y rule has
an IF-THEN format as
follows
:
If (x is A and y is B)
THE
N
(z is C)
Whe
r
e x,y,z are fuzzy varia
b
les an
d A,B,C ar
e fu
zzy subsets in refe
ren
c
e sets X,Y,Z.
Definition
(5
): fuzzification:
fuzzy co
ntro
ller h
a
s
bee
n
desi
gne
d o
n
l
y for processing
of
fuzzy
qua
ntities. T
herefore
,
all in
p
u
t val
ues shoul
d b
e
conve
r
ted i
n
to fuzzy
set
s
b
e
fore u
s
e.
In
other
words,
stage of d
e
f
inition of the fuzzy
sets relates to in
p
u
t and outp
u
t
variable
s
. For
definition of these fuzzy sets, we shoul
d have
prima
r
y kno
w
led
g
e
of definition for each one
of
these
vari
abl
es. In
mo
st
case
s, o
u
tput
error i.
e. diffe
ren
c
e
bet
wee
n
outp
u
t of t
he p
r
o
c
e
s
s a
nd
referen
c
e sig
nal
and ch
an
ges or
its derivative
con
s
titute input
s of
fuzzy
system
. Definition (6
):
defuzzificatio
n
: it converts the fuzzy
se
t into a number b
a
s
ed on o
n
e
of the common
defuzzificatio
n
metho
d
s
such
as cente
r
of g
r
av
ity method o
r
h
e
ig
ht method
which i
s
output
of
controlle
r. Among them, center of
gravity defuzzification method i
s
rega
rde
d
as
one of the m
o
st
comm
on a
nd
appli
c
able
m
e
thod
s. In this meth
od, ce
nt
er of g
r
avity of output nu
meri
cal valu
e
s
is
sele
cted
a
c
cordin
g to
cen
t
er of
gravity
of memb
ershi
p
fun
c
tion
an
d is exp
r
e
s
se
d a
s
follo
ws [
1
,
4], [9-10], [18-19]:
i
i
yi
i
yi
yi
i
CG
)
(
)
(
(7)
Figure 2. Gra
phic d
e
si
gn o
f
defu
zzifie
r
o
f
center of gravity
Figure 3 The
operations which ar
e performed on fuzzy sets.
(a)
(b)
(c
)
(d)
Figure 3. The
basi
c
ope
rati
ons o
n
fuzzy sets a
)
Conventional fu
zzy
sets b
)
union
c)
Intersec
tion
d) co
mplem
e
nt
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
2302-4
046
A Revie
w
on
Speed Control Tech
niqu
e
s
of
Separate
l
y Excited… (Mahm
oud Za
dehb
aghe
ri)
109
4. PID Controller
PID co
ntrolle
r ha
s b
een
u
s
ed to
comp
are it
s respo
n
se
with
re
sults in thi
s
p
r
opo
se
d
method [13
-
1
4
]. It is nece
s
sary to note that more
tha
n
half of the indu
strial cont
rolle
rs
which are
applie
d tod
a
y use PID con
t
rol d
e
sig
n
s [
14], [22-23
].
Since
mo
st P
I
D controllers are a
d
ju
sted
in
situ, different
adjustm
ent rules h
a
ve be
en su
gge
ste
d
. The co
ntrollers ca
n be
adjuste
d in situ
carefully and
delicately with these rule
s. Values
of this co
ntrolle
r can be obtain
ed from trial
and
error metho
d
and
with
re
sp
onse of
sy
ste
m
. In this
ca
se, the
system
is ap
plied
a
s
a
clo
s
e
d
lo
o
p
and with a PI
D co
ntrolle
r [15]. We first
delete contro
l
l
ers I, D fro
m
the circuit
obtain gai
n limit or
K
P
crit
by increasi
ng K
p
. w
e
c
o
ns
id
er
K
p
of the system
as ½ of K
P
crit
and then pu
t the integral i
n
the circuit. We chang
e coeffici
ent of the integral
from larg
e value
s
to sma
ll values until
the
system
is lo
cated in
threshold
of fluctu
ation. Th
e a
b
o
ve coefficie
n
t is the i
n
te
gral
coefficie
n
t of
the controll
er
[11, 12]. At the same tim
e
,
we
put
the
de
rivative co
ntrol in th
e ci
rcu
i
t and i
n
crea
se
its coeffici
ent from sm
all values to la
rge
values
u
n
til the syste
m
be
come
s
stable
and erro
r of the
system be
co
mes ze
ro.
In this
rega
rd, coefficient
s
of the
controll
er are sp
ecifie
d and coeffici
e
n
ts
of the PID co
ntrolle
r whi
c
h
have been d
e
sig
ned a
r
e a
s
follows:
012
.
0
,
0001
.
0
,
1
.
0
d
i
p
k
k
k
So that , K
p
, K
i
,K
d
are Proportion
al
Gai
n
, integral gai
n and de
rivative gain [16-1
7
].
4.1. Stud
y
i
ng Resul
t
s of
Simulating PID Con
t
roller
For
simulatio
n
, Matlab Simulink
softwa
r
e ha
s be
en
use
d
. Type of
the motor u
s
ed in this
simulatio
n
is sepa
rately excited DC
motor an
d p
a
ram
e
ters of the motor are given in
the
appe
ndix. Th
e load
applie
d on the m
o
tor is
T
L
=2
00
+5sint.DC a
n
d
we
studie
d
speed
of moto
r in
different stag
es.
Figure 4. Curve of speed
variation in time for pa
ram
e
ters of d
c
m
o
tor
In Figure 4, spe
ed in lo
a
d
loss is
140
0 and
whe
n
we a
pplied
2
00+5si
n
t on i
t
in 8 s, sp
ee
d is
redu
ce
d to 12
0 roun
ds a
n
d
rea
c
he
s its referen
c
e
spe
ed agai
n after some
se
con
d
s an
d rem
o
ves
moment in 2
3
s an
d the speed g
o
e
s
b
e
yond the
referen
c
e
sp
ee
d at this time
and re
ache
s its
referen
c
e spe
ed after some
second
s.
Figure 5. Curve of speed v
a
riation in tim
e
fo
r 10% increa
se of pa
ra
meters of dc
motor(
R
a
, L
a
,
TL, J
)
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TELKOM
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Vol. 13, No. 1, Janua
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113
110
Figure 6.Cu
rve of spee
d variation in time
fo
r 40% decrease of para
m
eters of dc
motor(R
a
, L
a
,
TL)
5. Fuzzy
Logic Contr
o
ller
Main st
r
u
ct
u
r
e of
a f
u
zzy
cont
r
o
l sy
st
e
m
has
comp
ose
d
of
f
u
z
z
if
ier,
f
u
zzy
r
u
l
e
s ba
se,
deci
s
io
n an
d
defu
zzifie
r
[
18-1
9
]. Fu
zzy control h
a
s been
u
s
ed
i
n
a
clo
s
ed
lo
op
system. A
n
y
cha
nge in speed of mot
o
r whi
c
h
ca
n be due to
chan
ge
s of moment, re
feren
c
e spee
d or
cha
nge
s in e
l
ements
of the motor
su
ch
as chan
ge i
n
re
sista
n
ce
of armatu
re
etc [20]. whi
c
h
cau
s
e
cha
n
g
e
of output voltage [19, 2
1
]. To cont
rol
voltage, two
para
m
eters o
f
spee
d erro
r and
cha
nge
s of speed e
r
ror
are used.
Spee
d error i
s
obt
ained a
c
co
rdi
ng to Rel
a
tio
n
8 by differe
nce
of spee
d at a
n
y moment n
(
k) and
refe
re
nce
spe
ed n
RE
F
and its po
sitivity or nega
tivity indicate
s
less or mo
re
spe
ed of m
o
tor than
the re
feren
c
e
spe
e
d
and it
s valu
es in
dicates t
h
is differen
c
e
of
spe
ed.
REF
n
k
n
k
e
(8)
The seco
nd
para
m
eter i
s
cha
nge of sp
eed erro
r whi
c
h is o
b
taine
d
from difference of
spe
ed at any moment n(k) and spee
d
at the previou
s
moment n(k-1):
1
k
n
k
n
k
e
(9)
Positivity or negativity of
this pa
ramet
e
r
indi
cate
s
ascen
d
ing o
r
descen
d
ing
trend of
motor
spee
d
chan
ge
s an
d its value in
dicate in
te
nsi
t
y of these chang
es. Th
e
fuzzy contro
ller
covers the
en
tire space of t
he inp
u
t varia
b
les
co
nsi
deri
ng the
s
e two
para
m
eters a
nd all p
o
ssibl
e
states
are co
nsid
ere
d
for cha
nge
in sp
eed of
mo
tor. For
ea
ch o
ne of th
e inp
u
t variabl
es,
the
fuzzy
syste
m
and it
s o
u
tput
are
rega
rd
ed
as me
mbe
r
ship fun
c
tion
with five
ran
g
es
of VL, L,
Z
E
,
S and VS. Consi
deri
ng th
at we
con
s
id
er five ra
nge
s for
ea
ch in
put variabl
e
and the
co
ntrol
system has t
w
o inputs b,
we will have totally 25
rules in center of
fuzzy
rul
e
s.
These rul
e
s
are
sho
w
n in Ta
b
l
e 2 for simpli
city [13-14], [28-2
9
].
Table 2. Fu
zzy rules
VL
L
ZE
S
VS
S
DS
VS
VS
VS
S
ZE
VL
VS
VS
S
ZE
L
L
S
S
ZE
L
VL
ZE
S
ZE
L
VL
VL
S
ZE
L
L
VL
VL
VS
Membe
r
ship
function
s u
s
e
d
in this
sim
u
lation for
sp
eed e
rro
r a
n
d ch
ange
s of
spe
ed
error an
d also output (
∆
V) are sh
own in
Figure 7 to 9
.
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TELKOM
NIKA
ISSN:
2302-4
046
A Revie
w
on
Speed Control Tech
niqu
e
s
of
Separate
l
y Excited… (Mahm
oud Za
dehb
aghe
ri)
111
Figure 7. Membershi
p
fun
c
tion of sp
ee
d error
Figure 8. Membershi
p
fun
c
tion of sp
ee
d error
cha
nge
s
Figure 9. Membershi
p
fun
c
tion of outpu
t (
∆
V)
5.1. Stud
y
i
ng Resul
t
s of
Simulating Fuzz
y
Controller
Figure 10. Cu
rve of spee
d variation in te
rms of
time for para
m
eters of dc
motor (spe
ed
in No
load of 140
0 rpm)
Figure 11 . Curve of spe
e
d
variation in term
s
of time for 10% incre
a
se of param
eters of dc
motor(
R
a
, L
a
, TL, J
)
Figure 12. Cu
rve of spee
d variation for 4
0
%
decrea
s
e of p
a
ram
e
ters of dc moto
r
R
a
, L
a
, TL,
J)
Figure 13. Cu
rve of spee
d variation for 1
0
%
decrea
s
e of p
a
ram
e
ters of dc moto
r
(R
a
, L
a
,
TL)
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Vol. 13, No. 1, Janua
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113
112
6. Stud
y
i
ng Resul
t
s of Si
mulation in Fuzz
y
and PID Con
t
roller
s
Figure 14. Cu
rve of spee
d variation in te
rms of
time for para
m
eters of dc
motor (
R
a
, L
a
, TL, J
)
Figure 15. Cu
rve of spee
d variation in te
rms of
time for 10% inc
r
eas
e
of parameters
of dc
motor (
R
a
, L
a
, TL, J
)
Figure 16. Cu
rve of spee
d variation in te
rms of
time for 40% inc
r
eas
e
of parameters
of dc
motor (
R
a
, L
a
, TL, J
)
Figure 17 . Curve of spe
e
d
variation in term
s
of time for 40% decrea
s
e o
f
paramete
r
s
of dc
motor (
R
a
, L
a
, TL)
As Fig
u
re
1
7
shows, o
u
r
refere
nce
spe
ed i
s
1
4
00 rpm a
n
d
we
appli
e
d
load
with
specifications of is T
L
=20
0
+
5
s
int on the
motor in 8
s
. As sh
own ab
ove, decrea
s
e of spe
ed in
a 5
-
volt phase in
PID is 50 rou
nds a
nd de
crease of sp
ee
d in the cla
ssic syste
m
is
more tha
n
th
at in
the fuzzy
systems which is one
of the disadva
n
ta
g
e
s of cl
assi
c system
s
(PI
D
). Of the ot
her
disa
dvantag
e
s
of the cla
s
sic
sy
stem
s
are flu
c
tuatio
n of spe
ed,
long sta
b
ility time (re
achin
g
referen
c
e spe
ed) an
d overshoot.
7. Conclusio
n
In this pap
er,
fuzzy an
d cl
a
ssi
c de
sig
n
of the DC m
o
to
r sp
eed
cont
roller (PI
D
) ha
s bee
n
mentione
d irresp
ective of delay re
sultin
g from
mech
anical time consta
nt of th
e motor whi
c
h is
available i
n
al
l sp
eed
co
ntrol metho
d
s. F
u
zzy c
ontrol
method
ha
s d
e
sirable
qu
ality compa
r
e
with
other meth
od
s due to
spee
d, accuracy a
nd inde
pen
de
nce of the
co
ntrolle
r from
variable
s
of the
controlled
pro
c
e
ss,
simpli
ci
ty of desig
n a
nd
contro
llabi
lity of spee
d i
n
broad
ra
ng
es
of refe
ren
c
e
spe
e
d
s
. This
prio
rity in small cha
nge
s o
f
referen
c
e
sp
eed is very consi
derable.
Referen
ces
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yedr
aso
u
l S
ane
ifard, N
adi
puram
R Pras
ad.
F
u
zz
y-Lo
gi
c-Based S
p
e
e
d
Co
ntrol
of a
Shunt
D
C
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. 19
9
8
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[2] JM
Mende
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Fuzz
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Proc. IEEE. 1995; 83: 34
5–3
7
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[3]
S T
u
ny
asrirut,
J Ngam
w
i
w
i
t,
T
Furuy
a
.
A
d
a
p
tive
F
u
zz
y
PI Contro
ller
for Spee
d of
Se
pa
rately
Exc
i
te
d
DC Motor
. 5-2
0
-1, Shii, Koku
ra-minam
i-ku, Kitak
y
ush
u
80
3-09
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an.
[4]
Gilbert C
D
S
o
u
s
a, Bimal
K B
o
se. A F
u
zz
y S
e
t
T
heor
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ontro
l of
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P
hase-
Contro
ll
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onv
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r
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n
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in
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F
u
z
z
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4
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adeh. F
u
z
z
y
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ont
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8-35
3.
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C Kings
le
y Jr, SD Umans, El
ectric
Machi
ner
y, 5th ed. Ne
w
York: McGra
w
-
Hill, 19
90.
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TELKOM
NIKA
ISSN:
2302-4
046
A Revie
w
on
Speed Control Tech
niqu
e
s
of
Separate
l
y Excited… (Mahm
oud Za
dehb
aghe
ri)
113
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M
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g
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zz
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adeh. Ne
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i
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y
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n
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