26,184 research outputs found
Adaptive Control By Regulation-Triggered Batch Least-Squares Estimation of Non-Observable Parameters
The paper extends a recently proposed indirect, certainty-equivalence,
event-triggered adaptive control scheme to the case of non-observable
parameters. The extension is achieved by using a novel Batch Least-Squares
Identifier (BaLSI), which is activated at the times of the events. The BaLSI
guarantees the finite-time asymptotic constancy of the parameter estimates and
the fact that the trajectories of the closed-loop system follow the
trajectories of the nominal closed-loop system ("nominal" in the sense of the
asymptotic parameter estimate, not in the sense of the true unknown parameter).
Thus, if the nominal feedback guarantees global asymptotic stability and local
exponential stability, then unlike conventional adaptive control, the newly
proposed event-triggered adaptive scheme guarantees global asymptotic
regulation with a uniform exponential convergence rate. The developed adaptive
scheme is tested to a well-known control problem: the state regulation of the
wing-rock model. Comparisons with other adaptive schemes are provided for this
particular problem.Comment: 29 pages, 12 figure
joineR: Joint modelling of repeated measurements and time-to-event data
The joineR package implements methods for analysing data from longitudinal studies in which the response
from each subject consists of a time-sequence of repeated measurements and a possibly censored time-toevent
outcome. The modelling framework for the repeated measurements is the linear model with random
effects and/or correlated error structure. The model for the time-to-event outcome is a Cox proportional
hazards model with log-Gaussian frailty. Stochastic dependence is captured by allowing the Gaussian
random effects of the linear model to be correlated with the frailty term of the Cox proportional hazards
model
Maximum-likelihood estimation of delta-domain model parameters from noisy output signals
Fast sampling is desirable to describe signal transmission
through wide-bandwidth systems. The delta-operator provides an ideal discrete-time modeling description for such fast-sampled systems. However, the estimation of delta-domain model parameters is usually biased by directly applying the delta-transformations to a sampled signal corrupted by additive measurement noise. This problem is solved here by expectation-maximization, where the delta-transformations of the true signal are estimated and then used to obtain the model parameters. The method is
demonstrated on a numerical example to improve on the accuracy of using a shift operator approach when the sample rate is fast
A revised model of fluid transport optimization in Physarum polycephalum
Optimization of fluid transport in the slime mold Physarum polycephalum has
been the subject of several modeling efforts in recent literature. Existing
models assume that the tube adaptation mechanism in P. polycephalum's tubular
network is controlled by the sheer amount of fluid flow through the tubes. We
put forward the hypothesis that the controlling variable may instead be the
flow's pressure gradient along the tube. We carry out the stability analysis of
such a revised mathematical model for a parallel-edge network, proving that the
revised model supports the global flow-optimizing behavior of the slime mold
for a substantially wider class of response functions compared to previous
models. Simulations also suggest that the same conclusion may be valid for
arbitrary network topologies.Comment: To appear in Journal of Mathematical Biolog
Self-consistent Modeling of the of HTS Devices: How Accurate do Models Really Need to Be?
Numerical models for computing the effective critical current of devices made
of HTS tapes require the knowledge of the Jc(B,theta) dependence, i.e. of the
way the critical current density Jc depends on the magnetic flux density B and
its orientation theta with respect to the tape. In this paper we present a
numerical model based on the critical state with angular field dependence of Jc
to extract the Jc(B,theta) relation from experimental data. The model takes
into account the self-field created by the tape, which gives an important
contribution when the field applied in the experiments is low. The same model
can also be used to compute the effective critical current of devices composed
of electromagnetically interacting tapes. Three examples are considered here:
two differently current rated Roebel cables composed of REBCO coated conductors
and a power cable prototype composed of Bi-2223 tapes. The critical currents
computed with the numerical model show good agreement with the measured ones.
The simulations reveal also that several parameter sets in the Jc(B,theta) give
an equally good representation of the experimental characterization of the
tapes and that the measured Ic values of cables are subjected to the influence
of experimental conditions, such as Ic degradation due to the manufacturing and
assembling process and non-uniformity of the tape properties. These two aspects
make the determination of a very precise Jc(B,theta) expression probably
unnecessary, as long as that expression is able to reproduce the main features
of the angular dependence. The easiness of use of this model, which can be
straightforwardly implemented in finite-element programs able to solve static
electromagnetic problems, is very attractive both for researchers and devices
manufactures who want to characterize superconducting tapes and calculate the
effective critical current of superconducting devices
Adaptive identification and control of structural dynamics systems using recursive lattice filters
A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center
CopulaDTA: An R Package for Copula Based Bivariate Beta-Binomial Models for Diagnostic Test Accuracy Studies in a Bayesian Framework
The current statistical procedures implemented in statistical software
packages for pooling of diagnostic test accuracy data include hSROC regression
and the bivariate random-effects meta-analysis model (BRMA). However, these
models do not report the overall mean but rather the mean for a central study
with random-effect equal to zero and have difficulties estimating the
correlation between sensitivity and specificity when the number of studies in
the meta-analysis is small and/or when the between-study variance is relatively
large. This tutorial on advanced statistical methods for meta-analysis of
diagnostic accuracy studies discusses and demonstrates Bayesian modeling using
CopulaDTA package in R to fit different models to obtain the meta-analytic
parameter estimates. The focus is on the joint modelling of sensitivity and
specificity using copula based bivariate beta distribution. Essentially, we
extend the work of Nikoloulopoulos by: i) presenting the Bayesian approach
which offers flexibility and ability to perform complex statistical modelling
even with small data sets and ii) including covariate information, and iii)
providing an easy to use code. The statistical methods are illustrated by
re-analysing data of two published meta-analyses. Modelling sensitivity and
specificity using the bivariate beta distribution provides marginal as well as
study-specific parameter estimates as opposed to using bivariate normal
distribution (e.g., in BRMA) which only yields study-specific parameter
estimates. Moreover, copula based models offer greater flexibility in modelling
different correlation structures in contrast to the normal distribution which
allows for only one correlation structure.Comment: 26 pages, 5 figure
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