Adaptive Super-Twisting Controller-Based Modified Extended State Observer for Permanent Magnet Synchronous Motors
Actuators,
Journal Year:
2025,
Volume and Issue:
14(4), P. 161 - 161
Published: March 23, 2025
A
novel
sliding
mode
control
(SMC)
strategy
incorporating
an
adaptive
super-twisting
algorithm
is
developed
for
permanent
magnet
synchronous
motors
(PMSMs),
effectively
mitigating
high-frequency
chattering
while
enhancing
external
disturbance
rejection
capabilities.
Initially,
a
surface
crafted
based
on
the
dynamic
characteristics
of
PMSM
and
real-time
feedback.
The
subsequently
applied
adaptively
to
dynamically
adjust
effort
required
maintain
state,
thereby
ensuring
precise
prompt
intervention
uphold
system
stability
enhance
response
speed.
Additionally,
in
light
operational
challenges
such
as
road-induced
load
disturbances,
Lyapunov-based
observer
proposed
torque
estimation
systems.
efficacy
observation
methods
substantiated
through
hardware-in-the-loop
experiment
test,
demonstrating
that
controller,
leveraging
algorithm,
exhibits
superior
tracking
capabilities,
reduces
steady-state
current
error,
bolsters
parameter
robustness,
modified
extended
state
(MESO)
commendable
performance.
Language: Английский
PMSM Speed Control Based on Improved Adaptive Fractional-Order Sliding Mode Control
Symmetry,
Journal Year:
2025,
Volume and Issue:
17(5), P. 736 - 736
Published: May 10, 2025
Addressing
the
problem
of
poor
robustness
and
anti-interference
ability
in
permanent
magnet
synchronous
motor
(PMSM)
speed
control
system,
an
adaptive
fractional-order
sliding
mode
controller
based
on
a
disturbance
observer
is
proposed.
Firstly,
mathematical
model
PMSM
established,
which
combines
with
fractional
order
to
effectively
reduce
drawbacks
traditional
integer
improve
accuracy
system.
At
same
time,
new
approach
law
used
replace
exponential
law,
reduces
system
buffeting
improves
performance.
We
use
observe
external
disturbances
perform
feedforward
compensation
observed
values
system’s
ability.
By
combining
techniques,
mitigates
limitations
integer-order
approaches.
It
enhances
symmetry
preservation
response
under
asymmetric
conditions.
The
simulation
results
show
that
using
improved
can
enhance
stability
ability,
has
better
dynamic
steady-state
Language: Английский
Development of a Fault-Tolerant Permanent Magnet Synchronous Motor Using a Machine-Learning Algorithm for a Predictive Maintenance Elevator
Machines,
Journal Year:
2025,
Volume and Issue:
13(5), P. 427 - 427
Published: May 19, 2025
Elevators
serve
as
essential
vertical
transportation
systems
for
both
passengers
and
heavy
loads
in
modern
buildings.
Electromechanical
lifts
have
become
the
dominant
choice
due
to
their
performance
advantages
over
hydraulic
systems.
A
critical
component
of
drive
mechanism
is
Permanent
Magnet
Synchronous
Motor
(PMSM),
which
subject
mechanical
electrical
stress
during
continuous
operation.
This
necessitates
advanced
monitoring
techniques
ensure
safety,
system
reliability,
reduced
maintenance
costs.
In
this
study,
a
fault-tolerant
PMSM
designed
evaluated
through
2D
Finite
Element
Analysis
(FEA),
optimizing
key
electromagnetic
parameters.
The
design
validated
experimental
testing
on
real
elevator
setup,
capturing
operational
data
under
various
loading
conditions.
These
signals
are
preprocessed
analyzed
using
machine-learning
techniques,
specifically
Random
Forest
classifier,
distinguish
between
Normal,
Marginal,
Critical
states
motor
health.
model
achieved
classification
accuracy
94%,
demonstrating
high
precision
predictive
capabilities.
results
confirm
that
integrating
with
real-time
analytics
offers
reliable
solution
early
fault
detection,
minimizing
downtime
enhancing
safety.
Language: Английский