Mathematics,
Год журнала:
2023,
Номер
11(8), С. 1783 - 1783
Опубликована: Апрель 8, 2023
In
this
paper,
a
novel
simple,
but
effective
output
feedback
robust
control
(OFRC)
for
achieving
highly
accurate
position
tracking
of
pump-controlled
electro-hydraulic
system
is
presented.
To
cope
with
the
unavailability
all
state
information,
an
extended
observer
(ESO)
was
adopted
to
estimate
angular
velocity
and
load-pressure-related
variable
actuator
total
matched
disturbance,
which
enters
through
same
channel
as
input
in
dynamics.
addition,
first
time,
another
ESO
acting
disturbance
(DOB)
skillfully
integrated
effectively
compensate
adverse
effects
lumped
mismatched
uncertainty
caused
by
parameter
perturbation
external
loads
Then,
dynamic
surface-control-based
backstepping
controller
(DSC-BC)
based
on
constructed
ESOs
studied
synthesized
guarantee
that
closely
tracks
desired
trajectory
avoid
inherent
computational
burden
conventional
method
because
repetitive
analytical
derivative
calculation
at
each
iteration.
Furthermore,
stability
two
observes
overall
closed-loop
verified
using
Lyapunov
theory.
Finally,
several
extensive
comparative
experiments
were
carried
out
demonstrate
advantage
recommended
approach
comparison
some
reference
methods.
Journal of Field Robotics,
Год журнала:
2023,
Номер
40(4), С. 934 - 954
Опубликована: Янв. 20, 2023
Abstract
The
application
of
robotic
technologies
in
building
construction
leads
to
great
convenience
and
productivity
improvement,
robots
(CRs)
bring
enormous
opportunities
for
the
way
we
conduct
design
construction.
To
get
a
better
understanding
trends
track
CRs
on‐site
conditions,
this
paper
conducts
systematic
review
control
models
status
monitoring
CRs,
which
are
two
key
aspects
that
determine
accuracy
efficiency.
Control
flexibility
primary
needs
applied
different
scenes,
so
methods
based
on
driving
vitally
important.
Status
contains
knowledge
fault
detection,
intelligence
maintenance,
fault‐tolerant
control,
multiple
objectives
need
be
met
optimized
whole
drive
chain.
Moreover,
state‐of‐the‐art
is
comprehensively
summarized,
new
insights
also
provided
carry
promising
researches.
International Journal of Robotics and Control Systems,
Год журнала:
2022,
Номер
2(2), С. 435 - 447
Опубликована: Июль 6, 2022
The
use
of
DC
motors
is
now
common
because
its
advantages
and
has
become
an
important
necessity
in
helping
human
activities.
Generally,
motor
control
designed
with
PID
control.
main
problem
that
often
discussed
parameter
tuning,
namely
determining
the
value
Kp,
Ki,
Kd
parameters
order
to
obtain
optimal
system
performance.
In
this
study,
one
method
for
tuning
on
a
will
be
used,
Particle
Swarm
Optimization
(PSO)
method.
Parameter
optimization
using
PSO
stable
results
compared
other
methods.
controller
MATLAB
Simulink
obtained
where
Kp
=
8.9099,
K
2.1469,
0.31952
rise
time
0.0740,
settling
0.1361
overshoot
0.
Then
hardware
testing
by
entering
Arduino
IDE
software
produce
speed
response
1.4551,
Ki=
1.3079,
0.80271
4.3296,
7.3333
1.
International Journal of Robotics and Control Systems,
Год журнала:
2023,
Номер
3(2), С. 233 - 244
Опубликована: Апрель 7, 2023
Industries
use
numerous
drives
and
actuators,
including
DC
motors.
Due
to
the
wide-ranged
adjustable
speed,
motor
is
widely
used
in
many
industries.
However,
prone
external
disturbance
parameter
changes,
causing
its
speed
be
unstable.
Thus,
a
requires
an
appropriate
controller
design
obtain
fast
stable
with
small
steady-state
error.
In
this
study,
was
designed
based
on
PID
control
method,
gains
tuned
by
trial-and-error
MATLAB
Tuner
identification
system.
The
proposed
implemented
using
PLC
OMRON
CP1E
NA20DRA
hardware
implementation.
Each
tuning
method
repeated
five
times
so
that
system
performances
could
compared
improved.
Based
implementation
results,
trial-error
gave
acceptable
results
but
had
errors.
On
other
hand,
of
provided
responses
no
error
still
oscillations
high
overshoot
during
transition.
Therefore,
acquired
from
must
finely
get
better
responses.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Апрель 10, 2024
Abstract
To
overcome
the
disadvantages
of
premature
convergence
and
easy
trapping
into
local
optimum
solutions,
this
paper
proposes
an
improved
particle
swarm
optimization
algorithm
(named
NDWPSO
algorithm)
based
on
multiple
hybrid
strategies.
Firstly,
elite
opposition-based
learning
method
is
utilized
to
initialize
position
matrix.
Secondly,
dynamic
inertial
weight
parameters
are
given
improve
global
search
speed
in
early
iterative
phase.
Thirdly,
a
new
optimal
jump-out
strategy
proposed
"premature"
problem.
Finally,
applies
spiral
shrinkage
from
whale
(WOA)
Differential
Evolution
(DE)
mutation
later
iteration
accelerate
speed.
The
further
compared
with
other
8
well-known
nature-inspired
algorithms
(3
PSO
variants
5
intelligent
algorithms)
23
benchmark
test
functions
three
practical
engineering
problems.
Simulation
results
prove
that
obtains
better
for
all
49
sets
data
than
3
variants.
Compared
algorithms,
69.2%,
84.6%,
84.6%
best
function
(
$${f}_{1}-{f}_{13}$$
f1-13
)
kinds
dimensional
spaces
(Dim
=
30,50,100)
80%
solutions
10
fixed-multimodal
functions.
Also,
design
obtained
by
classical
Energies,
Год журнала:
2023,
Номер
16(2), С. 926 - 926
Опубликована: Янв. 13, 2023
In
this
article,
a
novel
methodology
is
proposed
by
utilizing
technique
which,
in
light
of
the
change
African
vulture
optimization
known
as
Sine
Cosine,
adopted
an
algorithm
(SCaAVOA)-based
tilt
integral
derivative
(TID)
regulator
for
load
frequency
control
(LFC)
five-area
power
system
with
multi-type
generations.
At
first,
execution
Cosine-adopted
calculation
tried
contrasting
it
standard
AVOA
while
considering
different
benchmark
functions.
To
demonstrate
superiority
SCaAVOA
algorithm,
results
are
contrasted
using
approaches.
next
stage,
method
used
thermal
and
likewise
applied
to
five-area,
ten-unit
comprising
conventional
sources
well
some
renewable
energy
sources.
The
performance
analysis
planned
completed
various
boundaries
loading
conditions.
It
seen
that
said
more
viable
comparison
other
controllers.
Agronomy,
Год журнала:
2023,
Номер
13(5), С. 1423 - 1423
Опубликована: Май 21, 2023
China’s
field
crops
such
as
cotton,
wheat,
and
tomato
have
been
produced
on
a
large
scale,
but
their
cultivation
process
still
adopts
more
traditional
manual
fertilization
methods,
which
makes
the
use
of
chemical
fertilizers
in
China
high
causes
waste
fertilizer
resources
ecological
environmental
damage.
To
address
above
problems,
hybrid
optimization
genetic
algorithms
particle
swarm
(GA–PSO)
is
used
to
optimize
initial
weights
backpropagation
(BP)
neural
network,
optimization-based
BP
network
PID
controller
designed
realize
accurate
control
flow
integrated
water
precision
system
for
crops.
At
same
time,
STM32
microcontroller-based
application
was
developed
performance
verified
experimentally.
The
results
show
that
has
an
average
maximum
overshoot
5.1%
adjustment
time
68.99
s,
better
than
based
(BP–PID)
controllers;
among
them,
algorithm
by
algorithm(GA–PSO–BP–PID)
best-integrated
when
rate
0.6m3/h.
IEEE Access,
Год журнала:
2023,
Номер
11, С. 61091 - 61102
Опубликована: Янв. 1, 2023
When
traditional
proportional
integral
and
differential
controllers
are
applied
to
speed
control
in
permanent
magnet
synchronous
motors(PMSM),
their
coefficients
basically
determined
based
on
experience,
which
inevitably
leads
unsatisfactory
results
when
using
this
parameter
the
stability
of
motors.
Therefore,
paper
proposes
an
improved
quantum
genetic
algorithm
states
as
basic
unit.
Utilizing
properties
for
global
optimization
optimize
control,
improving
rotation
angle
state
particles
through
idea
velocity
changes
particle
swarm
optimization(PSO),
introducing
adaptive
weight
changes,
Hadamard
gates
replace
mutation
strategies,
incorporating
disaster
mechanisms.
In
addition,
uses
four
test
functions
find
minimum
value,
thereby
verifying
that
our
has
better
performance
iteration
compared
other
algorithms,
providing
initial
basis
next
step
application
PID
optimization.
Prove
method
can
solve
problem
algorithms
falling
into
local
optima
due
improper
selection,
crossover,
methods,
cannot
effectively
motor
speed.
Finally,
Matlab2018a
simulation
compare
with
show
values
achieve
oscillation,
overshoot,
faster
target
