International Journal of Adaptive Control and Signal Processing,
Journal Year:
2024,
Volume and Issue:
39(1), P. 116 - 131
Published: Oct. 27, 2024
ABSTRACT
This
article
is
aimed
to
study
the
parameter
estimation
problems
of
a
non‐commensurate
fractional‐order
system
with
saturation
and
dead‐zone
nonlinearity.
In
order
reduce
structural
complexity
system,
model
separation
scheme
used
decompose
nonlinear
into
two
subsystems,
one
includes
parameters
linear
part
other
part.
Then,
we
derive
an
auxiliary
separable
gradient‐based
iterative
algorithm
help
scheme.
addition,
improve
utilization
real
time
information,
multi‐innovation
presented
based
on
sliding
measurement
window.
Finally,
feasibility
algorithms
validated
by
numerical
simulations.
International Journal of Robust and Nonlinear Control,
Journal Year:
2023,
Volume and Issue:
34(2), P. 1120 - 1147
Published: Oct. 17, 2023
Abstract
This
article
investigates
the
parameter
identification
problems
of
stochastic
systems
described
by
input‐nonlinear
output‐error
(IN‐OE)
model.
IN‐OE
model
consists
two
submodels,
one
is
an
input
nonlinear
and
other
a
linear
The
difficulty
in
that
information
vector
contains
unknown
variables,
which
are
noise‐free
(true)
outputs
system,
approach
taken
here
to
replace
terms
with
auxiliary
Based
on
over‐parameterization
hierarchical
principle,
gradient‐based
iterative
algorithm
least‐squares‐based
proposed
estimate
parameters
systems.
Finally,
numerical
simulation
examples
given
demonstrate
effectiveness
algorithms.
International Journal of Adaptive Control and Signal Processing,
Journal Year:
2023,
Volume and Issue:
38(1), P. 255 - 278
Published: Oct. 19, 2023
Summary
This
article
proposes
a
novel
identification
framework
for
estimating
the
parameters
of
controlled
autoregressive
moving
average
(CARARMA)
models
with
colored
noise.
By
means
building
an
auxiliary
model
and
using
hierarchical
principle,
this
investigates
highly‐efficient
parameter
estimation
algorithm.
In
order
to
meet
need
identifying
systems
large‐scale
parameters,
whole
CARARMA
system
is
separated
into
two
sets
decomposition
composition
recursive
algorithm
(i.e.,
generalized
extended
least
squares
or
decomposition‐based
algorithm)
presented.
Moreover,
analyzes
convergence
proposed
The
performance
analysis
shows
that
can
reduce
complexity
compared
without
decomposition.
International Journal of Adaptive Control and Signal Processing,
Journal Year:
2024,
Volume and Issue:
38(4), P. 1363 - 1385
Published: Jan. 28, 2024
Summary
By
using
the
collected
batch
data
and
iterative
search,
based
on
filtering
identification
idea,
this
article
investigates
proposes
a
filtered
multi‐innovation
generalized
projection‐based
method,
gradient‐based
least
squares‐based
method
for
equation‐error
autoregressive
systems
described
by
models.
These
methods
can
be
extended
to
other
linear
nonlinear
scalar
multivariable
stochastic
with
colored
noises.
International Journal of Robust and Nonlinear Control,
Journal Year:
2023,
Volume and Issue:
33(13), P. 7755 - 7773
Published: June 3, 2023
Summary
This
paper
studies
the
parameter
estimation
problems
of
feedback
nonlinear
systems.
Combining
multi‐innovation
identification
theory
with
negative
gradient
search,
we
derive
a
gradient‐based
iterative
algorithm.
In
order
to
reduce
computational
burden
and
further
improve
accuracy,
decomposition
algorithm
is
proposed
by
using
technique.
The
key
transform
an
original
system
into
two
subsystems
estimate
parameters
each
subsystem,
respectively.
A
simulation
example
provided
demonstrate
effectiveness
algorithms.
International Journal of Adaptive Control and Signal Processing,
Journal Year:
2023,
Volume and Issue:
37(11), P. 2983 - 3007
Published: Aug. 23, 2023
Summary
Multiple‐input
multiple‐output
(MIMO)
models
are
widely
used
in
practical
engineering.
This
article
derives
a
new
identification
model
of
the
MIMO
system
by
decomposing
into
several
multiple‐input
single‐output
subsystems.
By
means
auxiliary
idea,
an
model‐based
recursive
least
squares
(AM‐RLS)
algorithm
is
derived
for
identifying
systems.
In
order
to
reduce
computational
burden
systems,
this
presents
hierarchical
applying
principle,
(AM‐HLS)
proposed
improving
efficiency.
The
efficiency
analysis
indicates
that
AM‐HLS
effective
reducing
calculation
amount
compared
with
AM‐RLS
algorithm.
Moreover,
analyzes
convergence
simulation
example
shows
and
algorithms
studied
effective.
International Journal of Robust and Nonlinear Control,
Journal Year:
2023,
Volume and Issue:
33(18), P. 11411 - 11433
Published: Aug. 29, 2023
Abstract
The
fractional‐order
equivalent
circuit
model
can
reflect
the
internal
reaction
mechanism
of
a
lithium‐ion
battery
well.
This
article
aims
to
design
an
effective
and
optimization
method
describe
analyze
operating
characteristics
based
on
online
measurement
data.
controlled
autoregressive
is
derived
by
exploiting
memory
superiorities
fractional‐order,
which
comprises
electrochemical
impedance
spectroscopy
‐RC
as
special
cases.
utilization
polynomial
properties
reduces
difficulty
identification
while
preserving
ability
fit
battery.
To
realize
simultaneous
parameter
order
estimation,
weighted
gradient
descent
algorithm
proposed.
approach
designs
new
direction
fully
utilizes
data
from
adding
suitable
factor.
In
addition,
forgetting
factor
introduced
speed
up
convergence
produce
more
accurate
estimation.
Furthermore,
in
proposed
algorithms,
are
proved
using
martingale
theory
stochastic
principle.
Finally,
experimental
simulation
result
shows
performance
algorithms.
International Journal of Robust and Nonlinear Control,
Journal Year:
2024,
Volume and Issue:
34(11), P. 7265 - 7284
Published: March 28, 2024
Summary
In
this
paper,
we
use
the
maximum
likelihood
principle
and
negative
gradient
search
to
study
identification
issues
of
multivariate
equation‐error
systems
whose
outputs
are
contaminated
by
an
moving
average
noise
process.
The
model
decomposition
technique
is
used
decompose
system
into
several
regressive
subsystems
based
on
number
outputs.
order
improve
parameter
estimation
accuracy,
a
decomposition‐based
iterative
algorithm
proposed
means
method.
numerical
simulation
example
indicates
that
method
has
better
results
than
compared
algorithm.
