Empirical Data-Driven Linear Model of a Swimming Robot Using the Complex Delay-Embedding DMD Technique
Biomimetics,
Год журнала:
2025,
Номер
10(1), С. 60 - 60
Опубликована: Янв. 16, 2025
Anguilliform
locomotion,
an
efficient
aquatic
locomotion
mode
where
the
whole
body
is
engaged
in
fluid-body
interaction,
contains
sophisticated
physics.
We
hypothesized
that
data-driven
modeling
techniques
may
extract
models
or
patterns
of
swimmers'
dynamics
without
implicitly
measuring
hydrodynamic
variables.
This
work
proposes
empirical
kinematic
control
and
a
soft
swimming
robot.
The
robot
comprises
six
serially
connected
segments
can
individually
bend
with
segmental
pneumatic
artificial
muscles.
Kinematic
equations
relations
are
proposed
to
measure
desired
actuation
mimic
anguilliform
kinematics.
was
tested
experimentally
position
velocities
spatially
digitized
points
were
collected
using
QualiSys®
Tracking
Manager
(QTM)
1.6.0.1.
data
analyzed
offline,
proposing
new
complex
variable
delay-embedding
dynamic
decomposition
(CDE
DMD)
algorithm
combines
state
filtering
time
embedding
linear
approximate
model.
While
experimental
results
exhibited
exotic
curves
phase
plane
series,
analysis
showed
extracts
chaotic
modes
contributing
data.
It
concluded
be
described
by
linearized
model
interrupted
modes.
technique
successfully
coherent
from
limited
measurements
linearizes
system
dynamics.
Язык: Английский
Evaluation of stability Enhancement and CO reduction in wake reactor at fine combustion States: PIV measurements and POD flame structure analysis
Chemical Engineering Journal,
Год журнала:
2025,
Номер
505, С. 159633 - 159633
Опубликована: Янв. 23, 2025
Язык: Английский
From Patterns to Cocktails: A Novel Visualization Method for Turbulent Flow Fields in Stirred Reactors
Industrial & Engineering Chemistry Research,
Год журнала:
2024,
Номер
63(44), С. 19320 - 19328
Опубликована: Окт. 24, 2024
Visualizing
flow
fields
in
stirred
reactors
under
turbulent
conditions
remains
a
long-standing
challenge.
Inspired
by
bartenders
creating
patterns
while
mixing
cocktails,
we
introduced
pearlescent
powder
to
achieve
field
visualization.
We
captured
images
of
wall
structures
various
and
extracted
their
fractal
dimensions.
In
comparison
the
time,
this
method
effectively
reflects
degree
chaos
variability
performance.
Additionally,
dimension
shows
sensitivity
greater
than
that
traditional
metrics.
By
integrating
proper
orthogonal
decomposition
(POD)
dynamic
mode
(DMD)
techniques,
clarified
interactions
between
vortices
different
scales
within
reactors,
confirmed
Hilbert–Huang
spectrum
analysis.
These
analyses
revealed
underlying
mechanisms
for
reduced
performance
triple-shaft
validated
through
large-eddy
simulation
(LES)
results.
Furthermore,
work
provides
novel
rapidly
validating
computational
fluid
dynamics
(CFD)
models
direct
observation
structures.
Язык: Английский
Optimal DMD Koopman Data-Driven Control of a Worm Robot
Biomimetics,
Год журнала:
2024,
Номер
9(11), С. 666 - 666
Опубликована: Ноя. 1, 2024
Bio-inspired
robots
are
devices
that
mimic
an
animal's
motions
and
structures
in
nature.
Worm
inspired
by
the
movements
of
worm
This
robot
has
different
applications
such
as
medicine
rescue
plans.
However,
control
is
a
challenging
task
due
to
high-nonlinearity
dynamic
model
external
noises
applied
robot.
research
uses
optimal
data-driven
controller
First,
data
obtained
from
nonlinear
Then,
Koopman
theory
used
generate
linear
The
mode
decomposition
(DMD)
method
operator.
Finally,
quadratic
regulator
(LQR)
for
simulation
results
verify
performance
proposed
method.
Язык: Английский