Mathematics,
Journal Year:
2023,
Volume and Issue:
11(23), P. 4810 - 4810
Published: Nov. 28, 2023
This
work
introduces
an
innovative
approach
that
unites
a
PIDND2N2
controller
and
the
balanced
arithmetic
optimization
algorithm
(b-AOA)
to
enhance
stability
of
automatic
voltage
regulator
(AVR)
system.
The
controller,
tailored
for
precision,
stability,
responsiveness,
mitigates
limitations
conventional
methods.
b-AOA
optimizer
is
obtained
through
integration
pattern
search
elite
opposition-based
learning
strategies
into
algorithm.
optimizes
parameters
AVR
system’s
response,
harmonizing
exploration
exploitation.
Extensive
assessments,
including
evaluations
on
23
classical
benchmark
functions,
demonstrate
efficacy
b-AOA.
It
consistently
achieves
accurate
solutions,
exhibits
robustness
in
addressing
wide
range
problems,
stands
out
as
promising
choice
various
applications.
In
terms
system,
comparative
analyses
highlight
superiority
proposed
transient
response
characteristics,
with
shortest
rise
settling
times
zero
overshoot.
Additionally,
excels
frequency
ensuring
robust
broader
bandwidth.
Furthermore,
compared
state-of-the-art
control
methods
showcasing
impressive
performance.
These
results
underscore
significance
this
work,
setting
new
by
advancing
reliability
power
systems.
IET Renewable Power Generation,
Journal Year:
2024,
Volume and Issue:
18(6), P. 959 - 978
Published: Feb. 20, 2024
Abstract
The
pressing
need
for
sustainable
energy
solutions
has
driven
significant
research
in
optimizing
solar
photovoltaic
(PV)
systems
which
is
crucial
maximizing
conversion
efficiency.
Here,
a
novel
hybrid
gazelle‐Nelder–Mead
(GOANM)
algorithm
proposed
and
evaluated.
GOANM
synergistically
integrates
the
gazelle
optimization
(GOA)
with
Nelder–Mead
(NM)
algorithm,
offering
an
efficient
powerful
approach
parameter
extraction
PV
models.
This
investigation
involves
thorough
assessment
of
algorithm's
performance
across
diverse
benchmark
functions,
including
unimodal,
multimodal,
fixed‐dimensional
CEC2020
functions.
Notably,
consistently
outperforms
other
approaches,
demonstrating
enhanced
convergence
speed,
accuracy,
reliability.
Furthermore,
application
extended
to
single
diode
double
models
RTC
France
cell
model
Photowatt‐PWP201
module.
experimental
results
demonstrate
that
approaches
terms
accurate
estimation,
low
root
mean
square
values,
fast
convergence,
alignment
data.
These
emphasize
its
role
achieving
superior
efficiency
renewable
systems.
e-Prime - Advances in Electrical Engineering Electronics and Energy,
Journal Year:
2023,
Volume and Issue:
5, P. 100225 - 100225
Published: July 29, 2023
In
the
field
of
digital
filter
design
and
system
identification,
accurately
modeling
Infinite
Impulse
Response
(IIR)
systems
is
utmost
importance.
This
paper
introduces
a
new
adaptive
algorithm
that
combines
gazelle
optimization
with
simulated
annealing
to
achieve
superior
performance
for
IIR
filters
used
in
identification.
To
evaluate
algorithm's
effectiveness,
extensive
experiments
were
conducted
on
two
fronts:
challenging
CEC2020
benchmark
functions
fifth
order
identification
problem.
The
proposed
proves
its
effectiveness
by
achieving
optimal
solutions
when
compared
other
well-known
algorithms
such
as
arithmetic
optimization,
particle
swarm
differential
evolution,
sine
cosine
algorithm,
grey
wolf
optimizer,
biogeography-based
salp
original
algorithm.
measured
ability
find
best
these
functions.
For
problem,
study
considers
both
same
reduced
cases.
be
identified
represented
plant.
statistical
analysis
convergence
behavior
are
artificial
hummingbird
mountain
widely
bee
colony
These
comparisons
demonstrate
capability
efficiency
identifying
parameters
systems.
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 105830 - 105842
Published: Jan. 1, 2023
This
paper
addresses
the
design
of
an
optimally
executed
proportional-integral-derivative
(PID)
controller,
tailored
for
speed
regulation
a
direct
current
(DC)
motor.
To
achieve
this
objective,
we
present
novel
hybrid
algorithm,
combining
gazelle
optimization
algorithm
(GOA)
with
effective
simplex
search
method
known
as
Nelder-Mead
(NM)
technique.
The
fusion
these
algorithms
yields
innovative
hybridized
version,
striking
balance
between
exploration
and
exploitation.
proposed
approach,
named
optimizer
(GSO),
showcases
great
promise
when
applied
to
task
controlling
DC
motor
using
PID
controller.
identify
optimal
values
gains,
harness
power
objective
function
well,
which
guides
GSO
in
determining
most
favorable
controller
settings.
Rigorous
comparative
simulations
are
then
undertaken,
where
pit
against
several
other
algorithms,
namely
reptile
prairie
dog
weighted
mean
vectors
optimization,
original
GOA
algorithm.
These
allow
us
assess
system's
behavior
through
various
lenses,
such
statistical
tests,
time
frequency
domain
responses,
robustness
analysis,
changes
function.
evaluations
from
comprehensive
tests
demonstrate
superiority
GSO-based
controlled
system.
exhibits
better
performance
than
alternative
providing
solid
evidence
its
effectiveness.
Furthermore,
approach
outperforms
reported
tuning
methods,
affirming
prowess
achieving
superior
motors.
