IEEE Access,
Journal Year:
2021,
Volume and Issue:
9, P. 11911 - 11920
Published: Jan. 1, 2021
The
tuning
of
the
robot
actuator
represents
many
challenges
to
follow
a
predefined
trajectory
on
account
uncertainties
parameters
and
model
nonlinearity.
Furthermore,
controller
gains
require
proper
optimization
achieve
good
performance.
In
this
paper,
use
modified
neural
network
algorithm
(MNNA)
is
proposed
as
novel
adaptive
optimize
gains.
new
mathematical
modulation
introduced
promote
exploration
manner
NNA
without
initial
parameters.
Specifically,
formed
by
using
polynomial
mutation.
applied
select
proportional
integral
derivative
(PID)
manipulator
arms
in
lieu
conventional
procedures
designer
expertise.
Another
vital
contribution
formulating
performance
index
that
guarantees
improve
settling
time
overshoot
every
arm
output
simultaneously.
evaluated
with
different
intelligent
techniques
literature,
including
genetic
(GA)
cuckoo
search
(CSA)
PID
controllers,
where
its
superiority
various
trajectories
demonstrated.
To
affirm
robustness
efficiency
algorithm,
several
are
considered
for
assessing
response
robotic
manipulator.
Artificial Intelligence Review,
Journal Year:
2024,
Volume and Issue:
57(8)
Published: July 4, 2024
Abstract
Rapid
industrialization
has
fueled
the
need
for
effective
optimization
solutions,
which
led
to
widespread
use
of
meta-heuristic
algorithms.
Among
repertoire
over
600,
300
new
methodologies
have
been
developed
in
last
ten
years.
This
increase
highlights
a
sophisticated
grasp
these
novel
methods.
The
biological
and
natural
phenomena
inform
strategies
seen
paradigm
shift
recent
observed
trend
indicates
an
increasing
acknowledgement
effectiveness
bio-inspired
tackling
intricate
engineering
problems,
providing
solutions
that
exhibit
rapid
convergence
rates
unmatched
fitness
scores.
study
thoroughly
examines
latest
advancements
optimisation
techniques.
work
investigates
each
method’s
unique
characteristics,
properties,
operational
paradigms
determine
how
revolutionary
approaches
could
be
problem-solving
paradigms.
Additionally,
extensive
comparative
analyses
against
conventional
benchmarks,
such
as
metrics
search
history,
trajectory
plots,
functions,
are
conducted
elucidate
superiority
approaches.
Our
findings
demonstrate
potential
optimizers
provide
directions
future
research
refine
expand
upon
intriguing
methodologies.
survey
lighthouse,
guiding
scientists
towards
innovative
rooted
various
mechanisms.
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Feb. 5, 2024
Metaheuristic
optimization
algorithms
are
known
for
their
versatility
and
adaptability,
making
them
effective
tools
solving
a
wide
range
of
complex
problems.
They
don't
rely
on
specific
problem
types,
gradients,
can
explore
globally
while
handling
multi-objective
optimization.
strike
balance
between
exploration
exploitation,
contributing
to
advancements
in
However,
it's
important
note
limitations,
including
the
lack
guaranteed
global
optimum,
varying
convergence
rates,
somewhat
opaque
functioning.
In
contrast,
metaphor-based
algorithms,
intuitively
appealing,
have
faced
controversy
due
potential
oversimplification
unrealistic
expectations.
Despite
these
considerations,
metaheuristic
continue
be
widely
used
tackling
This
research
paper
aims
fundamental
components
concepts
that
underlie
focusing
use
search
references
delicate
exploitation.
Visual
representations
behavior
selected
will
also
provided.
