Disturbance observer based adaptive trajectory tracking control for Unmanned Surface Vehicle with input and state quantization
Ocean Engineering,
Год журнала:
2024,
Номер
308, С. 118206 - 118206
Опубликована: Май 30, 2024
Язык: Английский
Adaptive Fault-Tolerant Fuzzy Containment Control for Networked Autonomous Surface Vehicles: A Noncooperative Game Approach
IEEE Transactions on Fuzzy Systems,
Год журнала:
2024,
Номер
32(7), С. 4192 - 4204
Опубликована: Июнь 5, 2024
Язык: Английский
Adaptive Sliding Mode Trajectory Tracking Control of Unmanned Surface Vessels Based on Time-Domain Wave Inversion
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(8), С. 1278 - 1278
Опубликована: Июль 29, 2024
In
this
work,
we
develop
a
trajectory
tracking
control
method
for
unmanned
surface
vessels
(USVs)
based
on
real-time
compensation
actual
wave
disturbances.
Firstly,
information
from
the
sea
is
extracted
through
stereoscopic
visual
observations,
and
data
preprocessing
performed
using
task-driven
point
cloud
downsampling
network.
We
reconstruct
phase-resolved
field
in
real
time.
Subsequently,
disturbances
are
modeled
mechanically,
used
as
feedforward
inputs.
Furthermore,
an
adaptive
backstepping
sliding
mode
law
command
filters
designed
to
avoid
differential
explosion
mitigate
chattering.
An
also
estimate
compensate
other
external
inversion
error
bounds
that
cannot
be
computed
Finally,
feasibility
of
proposed
strategy
validated
stability
analysis
numerical
simulation
experiments.
Язык: Английский
Trajectory tracking control for unmanned amphibious surface vehicles with actuator faults
Applied Ocean Research,
Год журнала:
2024,
Номер
152, С. 104182 - 104182
Опубликована: Авг. 20, 2024
Язык: Английский
Transient-Reinforced Tunnel Coordinated Control of Underactuated Marine Surface Vehicles With Actuator Faults
IEEE Transactions on Intelligent Transportation Systems,
Год журнала:
2023,
Номер
25(2), С. 1872 - 1881
Опубликована: Окт. 23, 2023
This
paper
is
concerned
with
a
performance-prescribed
coordinated
control
problem
of
multiple
underactuated
marine
surface
vehicles
(MSVs)
subject
to
internal
uncertainties,
external
disturbances,
and
actuator
faults.
An
echo
state
network-based
(ESN-based)
transient-reinforced
tunnel
method
proposed
for
MSVs
prescribed
performance
metrics.
Specifically,
graph-based
trajectory
generator
designed
generate
reference
signals
various
application
scenarios.
In
the
guidance
loop,
(TPP)
established
characterize
position
heading
coordination
metrics
MSVs.
With
TPP-based
equivalent
transformation,
laws
are
devised
by
an
underactuation
principle.
ESN-based
neural
estimator
constructed
identify
unknown
kinetics
consisting
Utilizing
estimated
information,
surge
yaw
presented.
The
closed-loop
system
proven
be
input-to-state
stable
via
theoretical
analysis,
tracking
errors
can
evolve
within
TPP
constraints
regardless
Finally,
comparison
simulation
results
employed
verify
effectiveness
superiority
method.
Язык: Английский
Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer
Journal of Marine Science and Engineering,
Год журнала:
2023,
Номер
11(10), С. 1874 - 1874
Опубликована: Сен. 26, 2023
The
motion
of
unmanned
surface
vehicles
(USVs)
is
frequently
disturbed
by
ocean
wind,
waves,
and
currents.
A
poorly
designed
controller
will
cause
failures
safety
problems
during
actual
navigation.
To
obtain
a
satisfactory
control
performance
for
the
USVs,
model
predictive
(MPC)
method
based
on
an
improved
Nonlinear
Disturbance
Observer
(NDO)
proposed.
First,
USV
approximately
linearized
MPC
multivariable
system
with
constraints.
compensate
influence
disturbances,
NDO
where
calculation
time
reduced.
Finally,
comparison
simulations
are
conducted
between
original
NDO,
results
show
that
they
have
similar
performances
to
USVs.
However,
proposed
has
fewer
parameters
need
be
tuned
much
more
time-saving
compared
traditional
NDO.
Язык: Английский
Saturation-Tolerant Tunnel Prescribed Control for Vessel-Train Formation of Underactuated MSVs
IEEE Transactions on Vehicular Technology,
Год журнала:
2024,
Номер
73(12), С. 18380 - 18390
Опубликована: Авг. 28, 2024
Язык: Английский
Trajectory tracking for autonomous surface ships using Gaussian process regression and model predictive control with BVS strategy
Journal of Marine Engineering & Technology,
Год журнала:
2024,
Номер
unknown, С. 1 - 15
Опубликована: Ноя. 3, 2024
Autonomous
navigation
is
critical
to
the
development
of
next-generation
shipping
systems.
The
proposal
intelligent
ships
enables
innovation
in
and
shipbuilding
industry
increases
safety
efficiency
ship
operations.
control
surface
follow
a
prescribed
trajectory
variety
maritime
applications.
This
paper
proposes
tracking
strategy
for
autonomous
that
combines
nonparametric
modelling
using
Gaussian
Process
Regression
(GPR)
with
Model
Predictive
Control
(MPC)
framework.
A
Bézier
curve-based
Virtual
Ship(BVS)
guidance
proposed
convert
dynamic
points
into
reference
heading
angles
speeds,
such
problem
can
be
decomposed
speed
problems.
process
regression
utilised
identify
correlation
between
propeller
revolution
speed,
as
well
rudder
angle
based
on
experimental
data.
Two
GPR
models
are
therefore
constructed
prediction
designing
MPC
controllers
control,
respectively.
Nonlinear
optimisation
algorithms
search
optimal
commands
each
sampling
interval
solve
input
constraints.
Simulations
carried
out
evaluate
effectiveness
method.
Язык: Английский