872 research outputs found
Performance bounds for optimal feedback control in networks
Many important complex networks, including critical infrastructure and
emerging industrial automation systems, are becoming increasingly intricate
webs of interacting feedback control loops. A fundamental concern is to
quantify the control properties and performance limitations of the network as a
function of its dynamical structure and control architecture. We study
performance bounds for networks in terms of optimal feedback control costs. We
provide a set of complementary bounds as a function of the system dynamics and
actuator structure. For unstable network dynamics, we characterize a tradeoff
between feedback control performance and the number of control inputs, in
particular showing that optimal cost can increase exponentially with the size
of the network. We also derive a bound on the performance of the worst-case
actuator subset for stable networks, providing insight into dynamics properties
that affect the potential efficacy of actuator selection. We illustrate our
results with numerical experiments that analyze performance in regular and
random networks
Characterization of Model-Based Detectors for CPS Sensor Faults/Attacks
A vector-valued model-based cumulative sum (CUSUM) procedure is proposed for
identifying faulty/falsified sensor measurements. First, given the system
dynamics, we derive tools for tuning the CUSUM procedure in the fault/attack
free case to fulfill a desired detection performance (in terms of false alarm
rate). We use the widely-used chi-squared fault/attack detection procedure as a
benchmark to compare the performance of the CUSUM. In particular, we
characterize the state degradation that a class of attacks can induce to the
system while enforcing that the detectors (CUSUM and chi-squared) do not raise
alarms. In doing so, we find the upper bound of state degradation that is
possible by an undetected attacker. We quantify the advantage of using a
dynamic detector (CUSUM), which leverages the history of the state, over a
static detector (chi-squared) which uses a single measurement at a time.
Simulations of a chemical reactor with heat exchanger are presented to
illustrate the performance of our tools.Comment: Submitted to IEEE Transactions on Control Systems Technolog
Control and Synchronization of Neuron Ensembles
Synchronization of oscillations is a phenomenon prevalent in natural, social,
and engineering systems. Controlling synchronization of oscillating systems is
motivated by a wide range of applications from neurological treatment of
Parkinson's disease to the design of neurocomputers. In this article, we study
the control of an ensemble of uncoupled neuron oscillators described by phase
models. We examine controllability of such a neuron ensemble for various phase
models and, furthermore, study the related optimal control problems. In
particular, by employing Pontryagin's maximum principle, we analytically derive
optimal controls for spiking single- and two-neuron systems, and analyze the
applicability of the latter to an ensemble system. Finally, we present a robust
computational method for optimal control of spiking neurons based on
pseudospectral approximations. The methodology developed here is universal to
the control of general nonlinear phase oscillators.Comment: 29 pages, 6 figure
Optimal Control of Inhomogeneous Ensembles
This dissertation is concerned with formulating the problem and developing methods for the synthesis of optimal, open-loop inputs for large numbers of identically structured dynamical systems that exhibit variation in the values of characteristic parameters across the collection, or ensemble. Our goal is to steer the family of systems from an initial state: or pattern) to a desired state: or pattern) with the same common control while compensating for the inherent dispersion caused by the inhomogeneous parameter values. We compose an optimal ensemble control problem and develop a computational method based on pseudospectral approximations to solve these complex problems. This class of ensemble systems is strongly motivated by natural complications in the control of quantum phenomena, especially in magnetic resonance; however, similar structures are prevalent in a variety of other applications. From another perspective, the same methodology can be used to analyze systems that have uncertainty in the values of characteristic parameters, which are ubiquitous throughout science and engineering
Application of the Wireless Audiometric Testing System at a Refugee Center with a Multilingual Population
The purpose of this study was to assess the state of hearing health in the immigrant and refugee community of northern Colorado, while also determining if the new wireless automated hearing test system (WAHTS) technology is a feasible means of bringing entry-level care to this multilingual population. Twenty adult participants were recruited from various cultural/lingual groups including: Rohingya, Karenni, Spanish, and Somali. Data were analyzed for 19 participants, 57.9% of who were female and 42.1% of who were male. Mean age of participants was 52.3 years (SD= 16.05). Audiometric thresholds were obtained at .5 to 8 kHz in both ears with the use of the WAHTS in classrooms and stairwells at a community center. Recorded ambient noise measurements in these locations were well within ANSI S3.1-1999 (R2013) standards when the attenuation of the WAHTS headset was considered. An interpreter was utilized to facilitate listener instruction, and a doctoral audiology student carried out all testing procedures. Participant interviews were conducted to determine self-reported hearing health history and subjective experience with the WAHTS. The point prevalence of hearing loss in this group was 52.6%. Overall, the use of the WAHTS was successful in this multilingual population, as most participants completed the task with simple translated instructions. The information gathered suggests a higher prevalence of hearing iv loss when compared to data for the general United States adult population and a rate of treatment acquisition that is about 20% lower than the general population. High rates of hearing loss in this population could have significant impacts for individuals trying to learn a new language. In a group that is in need of hearing healthcare, the WAHTS may be useful in low-resource settings in the future, with some slight software modifications to enhance usability
ncDNA and drift drive binding site accumulation
Background: The amount of transcription factor binding sites (TFBS) in an organism's genome positively correlates
with the complexity of the regulatory network of the organism. However, the manner by which TFBS arise and
accumulate in genomes and the effects of regulatory network complexity on the organism's fitness are far from being
known. The availability of TFBS data from many organisms provides an opportunity to explore these issues, particularly
from an evolutionary perspective.
Results: We analyzed TFBS data from five model organisms -- E. coli K12, S. cerevisiae, C. elegans, D. melanogaster, A.
thaliana -- and found a positive correlation between the amount of non-coding DNA (ncDNA) in the organismļ¾s
genome and regulatory complexity. Based on this finding, we hypothesize that the amount of ncDNA, combined with
the population size, can explain the patterns of regulatory complexity across organisms. To test this hypothesis, we
devised a genome-based regulatory pathway model and subjected it to the forces of evolution through population
genetic simulations. The results support our hypothesis, showing neutral evolutionary forces alone can explain TFBS
patterns, and that selection on the regulatory network function does not alter this finding.
Conclusions: The cis-regulome is not a clean functional network crafted by adaptive forces alone, but instead a data
source filled with the noise of non-adaptive forces. From a regulatory perspective, this evolutionary noise manifests as
complexity on both the binding site and pathway level, which has significant implications on many directions in
microbiology, genetics, and synthetic biology
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