Actuators,
Год журнала:
2024,
Номер
13(12), С. 525 - 525
Опубликована: Дек. 19, 2024
In
order
to
improve
the
control
performance
of
position
sensorless
system
permanent
magnet
synchronous
motors
and
reduce
influence
external
uncertainties
on
system,
such
as
inertia
ingestion
load
disturbance,
this
paper
proposes
a
novel
algorithm
for
based
an
interleaved
parallel
extended
sliding
mode
observer.
Firstly,
in
identify
time-varying
moment
inertia,
torque
viscous
friction
coefficient
observer
single-observer
model
is
proposed,
robust
activator
designed
coupling
between
parameters
be
measured.
Then,
new
predefined-time
controller
face-mounted
motor
using
film
theory,
which
improves
response
speed
accuracy
system.
proposed
are
used
design
stability
proved
Lyapunov
theorem.
Finally,
through
simulation
analysis
experimental
tests,
it
verified
that
strategy
can
identification
parameters,
time
identification,
tracking
speed.
Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi,
Год журнала:
2025,
Номер
14(2), С. 680 - 687
Опубликована: Апрель 15, 2025
Bu
çalışma,
kalıcı
mıknatıslı
fırçasız
doğru
akım
motoru
(SMFDAM)
sürücüsünde
gereken
rotor
hızını
tahmin
etmek
için
en
küçük
ortalama
kare
(Least
mean
square,
LMS),
kurtosis
(LMK)
ve
dördüncü
fourth,
LMF)
yaklaşımlarına
dayalı
model
referanslı
adaptif
sistem
(Model
reference
adaptive
system,
MRAS)
edicilerini
tanıtmaktadır.
Önerilen
MRAS
edicileri,
referans
modeli
olarak
hizmet
eden
ölçülen
stator
akımları
ile
modelin
çıkışında
üretilen
arasındaki
hata
terimini
minimize
ederek
doğrudan
kestirmektedir.
Ayrıca,
kapsayan
ağırlık
vektörleri
üç
edicide
de
her
örnekleme
adımında
güncellendiğinden,
geleneksel
çerçevelerinde
yaygın
kullanılan
sabit
kazançlı
orantılı-integral
bir
denetleyiciye
olan
ihtiyacı
ortadan
kaldırmaktadır.
edicilerin
başarımları,
zorlu
çalışma
senaryoları
altında
moment
kontrolü
(DMK)
tabanlı
SMFDAM
sürücüsü
aracılığıyla
değerlendirilmiştir.
Benzetim
sonuçları,
önerilen
kestiricilerin
başarımlarının
birbirlerine
alternatif
olduğunu
göstermiştir.
Özellikle,
hız
kestiriminde
LMF
yapısı
diğer
yapılarından
miktar
daha
iyi
başarım
sağlarken,
3-faz
LMS
LMK
yapıları
başarımlar
sağlamıştır.
Mathematics,
Год журнала:
2024,
Номер
12(21), С. 3407 - 3407
Опубликована: Окт. 31, 2024
The
optimal
performance
of
direct
current
(DC)
motors
is
intrinsically
linked
to
their
mathematical
models’
precision
and
controllers’
effectiveness.
However,
the
limited
availability
motor
characteristic
information
poses
significant
challenges
achieving
accurate
modeling
robust
control.
This
study
introduces
an
approach
employing
artificial
neural
networks
(ANNs)
estimate
critical
DC
parameters
by
defining
practical
constraints
that
simplify
estimation
process.
A
model
was
introduced
for
parameter
estimation,
two
advanced
learning
algorithms
were
proposed
efficiently
train
ANN.
thoroughly
analyzed
using
metrics
such
as
mean
squared
error,
epoch
count,
execution
time
ensure
reliability
dynamic
priority
arbitration
data
integrity.
Dynamic
involves
automatically
assigning
tasks
in
real-time
depending
on
relevance
smooth
operations,
whereas
integrity
ensures
remains
accurate,
consistent,
reliable
throughout
entire
ANN-based
estimator
successfully
predicts
electromechanical
electrical
characteristics,
back-EMF,
moment
inertia,
viscous
friction
coefficient,
armature
inductance,
resistance.
Compared
conventional
methods,
which
are
often
resource-intensive
time-consuming,
solution
offers
superior
accuracy,
significantly
reduced
time,
lower
computational
costs.
simulation
results
validated
effectiveness
ANN
under
diverse
real-world
operating
conditions,
making
it
a
powerful
tool
enhancing
with
applications
industrial
automation
control
systems.
International Journal of Circuit Theory and Applications,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 23, 2024
ABSTRACT
As
a
result
of
the
increasing
use
electric
vehicles,
ensuring
high‐performance
speed
and
torque
control
brushless
direct
current
(BLDC)
motors
has
become
great
importance
for
energy
efficiency.
In
order
to
prevent
ripple
finite
set
model
predictive
(FCS‐MPCC),
commutation
moments
are
detected
by
Hall
effect
sensors
in
conventional
methods.
However,
this
method
cannot
exhibit
long‐life
structure
because
physical
strain
damaging
electrical
connections.
study,
durations
captured
determined
with
new
approach.
Commutation
zero
crossing
detectors
using
position
information
obtained
from
encoder.
Moreover,
three‐phase
back
electromotive
forces
(EMFs)
BLDC
motor
applied
FCS‐MPCC
predict
stator
phase
currents
estimated
novel
adaptive
extended
Kalman
filter
(AEKF)
which
estimation
capability
without
any
sensor.
Furthermore,
another
improvement
is
implemented
calculation
cost
function
taking
into
account
difference
between
predicted
reference
different
MPCC
The
proposed
drive
system
tested
under
scenarios
at
various
speeds
load
torque,
resistance,
leakage
inductance
variations
simulation.
It
proven
simulation
results
that
commutations
can
be
achieved
stably
determination
method.
addition,
show
AEKF
estimator
calculated
regarding
not
only
error
but
also
moment
have
impressive
prediction
performance,
respectively.
This
paper
investigates
the
integration
of
Kalman
filter
with
fluorescence
analysis
in
biomedical
imaging,
a
synergy
that
holds
promise
advancing
diagnostic
accuracy
and
enhancing
research
methodologies
study
biological
systems.
Employing
rigorous
bibliometric
through
VOSviewer,
we
explore
key
trends,
influential
clusters,
seminal
publications
have
marked
evolution
this
interdisciplinary
field.
The
filter,
renowned
for
its
predictive
capabilities
real-time
signal
processing,
emerges
as
crucial
tool
improving
signal-to-
noise
ratio
thereby
facilitating
extraction
more
accurate
meaningful
data
from
complex
phenomena.
Our
reveals
dynamic
growing
landscape,
where
methodological
advancements
computational
challenges
intersect
practical
applications
imaging.
By
highlighting
significant
contributions
identifying
areas
ripe
future
investigation,
underscores
potential
filter-enhanced
to
revolutionize
diagnostics
offering
new
insights
into
cellular
molecular
processes.
Through
synthesis,
aim
provide
comprehensive
overview
current
state
art
chart
course
next
wave
innovations
The
study
involves
the
creation
of
a
solar-powered
car
that
can
travel
up
to
70
km
with
maximum
speed
35.7
km/h,
vehicle
mass
is
300
kg.
It
stores
some
energy,
which
then
converted
into
electric
energy
be
consumed
by
other
electrical
appliances,
making
it
an
generator.
two
back
wheels
are
equipped
3,000
W
motors
enable
movement.
When
moves,
power
dissipates
due
resistances
must
overcome
move
it.
Auxiliary
components
and
battery
powering
system
also
require
resulting
in
not
all
being
transmitted
vehicle's
wheels.
This
article
aims
create
prototype
model.
A
model
photovoltaic
system,
considering
geographic
coordinates
solar
parameters
location,
as
well
BLDC
motor
dynamics,
required
examine
component
behavior
based
on
observable
parameters.
These
pa-rameters
consist
resistive
torque,
angular
speed,
resistance
values
need
evaluate
performance.
Once
lost
has
been
determined,
remaining
will
allocated
devices.
variations
considered
crucial
for
performance
mechanical
supply
one
sources
our
provides
400
power.
Actuators,
Год журнала:
2024,
Номер
13(10), С. 403 - 403
Опубликована: Окт. 6, 2024
This
paper
addresses
performance
degradation
in
nonlinear
flux
linkage
algorithms,
arising
from
estimation
errors
rotor
due
to
fluctuations
current
and
temperature.
We
introduce
a
parameter-adaptive
model
using
MRAS,
which
dynamically
adjusts
the
linkage,
significantly
minimizing
improving
control
performance.
When
of
motor
undergoes
sudden
changes,
shows
speed
fluctuation
5%,
whereas
reduces
error
0.6%.
The
algorithm
demonstrates
strong
robustness
when
stator
resistance
change.
effectiveness
under
conditions
such
as
load
start
mutation
is
excellent.
Simulations
experiments
demonstrate
that
improves
accuracy
position
parameters
