22 results match your criteria: "Automatica[Journal]"

Article Synopsis
  • Epidemic surveillance testing is crucial for managing new outbreaks but is expensive and resource-intensive, limiting its effectiveness.
  • The study explores two key control problems: minimizing testing needs while keeping infections below a target level and reducing peak infections within a limited testing budget.
  • Findings reveal that adaptive testing strategies, which adjust based on the current epidemic state, save costs significantly and can be enhanced by combining molecular and serology tests for better estimation of the epidemic status.
View Article and Find Full Text PDF
Article Synopsis
  • A novel approach combining LQG control in Hilbert space, random abstract parabolic systems, and new transdermal alcohol biosensor technology aims to automate inpatient management of alcohol withdrawal syndrome and intravenous alcohol infusion studies.
  • * The method utilizes a complex model of alcohol distribution in the body, described through a combination of differential equations and advanced mathematical frameworks.
  • * Simulation studies using real drinking data demonstrate the effectiveness of this approach in accurately tracking and managing alcohol concentration levels.
View Article and Find Full Text PDF

A Markovian model for the spread of the SARS-CoV-2 virus.

Automatica (Oxf)

May 2023

University of Trento, Department of Information Engineering and Computer Science, Via Sommarive 9 - Povo, 38123 Trento (TN), Italy.

We propose a Markovian stochastic approach to model the spread of a SARS-CoV-2-like infection within a closed group of humans. The model takes the form of a Partially Observable Markov Decision Process (POMDP), whose states are given by the number of subjects in different health conditions. The model also exposes the different parameters that have an impact on the spread of the disease and the various decision variables that can be used to control it (e.

View Article and Find Full Text PDF
Article Synopsis
  • Mathematical models are essential for understanding how pathogens spread and for assessing the effectiveness of non-pharmaceutical interventions (NPIs) in populations.
  • Recent strategies aim to minimize either the peak number of infections or the overall epidemic size, but there's no agreement on how to optimize both at the same time while limiting the negative impacts of interventions.
  • This study introduces a new approach to managing SIR-type models by distinguishing between short-term and long-term control goals, demonstrating its effectiveness through detailed analysis and simulations related to the COVID-19 pandemic.
View Article and Find Full Text PDF

Quantitative assessment of the infection rate of a virus is key to monitor the evolution of an epidemic. However, such variable is not accessible to direct measurement and its estimation requires the solution of a difficult inverse problem. In particular, being the result not only of biological but also of social factors, the transmission dynamics can vary significantly in time.

View Article and Find Full Text PDF

Persistence of Excitation for Identifying Switched Linear Systems.

Automatica (Oxf)

March 2022

Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242.

This paper investigates the uniqueness of parameters via persistence of excitation for switched linear systems. The main contribution is a much weaker sufficient condition on the regressors to be persistently exciting that guarantees the uniqueness of the parameter sets and also provides new insights in understanding the relation among different subsystems. It is found that for uniquely determining the parameters of switched linear systems, the needed minimum number of samples derived from our sufficient condition is much smaller than that reported in the literature.

View Article and Find Full Text PDF

We estimate the distribution of random parameters in a distributed parameter model with unbounded input and output for the transdermal transport of ethanol in humans. The model takes the form of a diffusion equation with the input being the blood alcohol concentration and the output being the transdermal alcohol concentration. Our approach is based on the idea of reformulating the underlying dynamical system in such a way that the random parameters are now treated as additional space variables.

View Article and Find Full Text PDF

The widespread adoption of closed-loop control in systems biology has resulted from improvements in sensors, computing, actuation, and the discovery of alternative sites of targeted drug delivery. Most control algorithms for circadian phase resetting exploit light inputs. However, recently identified small-molecule pharmaceuticals offer advantages in terms of invasiveness and potency of actuation.

View Article and Find Full Text PDF

As IP video services have emerged to be the predominant Internet application, how to optimize the Internet resource allocation, while satisfying the quality of experience (QoE) for users of video services and other Internet applications becomes a challenge. This is because the QoE perceived by a user of video services can be characterized by a staircase function of the data rate, which is nonconcave and hence it is "hard" to find the optimal operating point. The work in this paper aims at tackling this challenge.

View Article and Find Full Text PDF

Velocity-weighting & velocity-penalty MPC of an artificial pancreas: Improved safety & performance.

Automatica (Oxf)

May 2018

Harvard John A. Paulson School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA.

A novel Model Predictive Control (MPC) law for the closed-loop operation of an Artificial Pancreas (AP) to treat type 1 diabetes is proposed. The contribution of this paper is to simultaneously enhance both the safety and performance of an AP, by reducing the incidence of controller-induced hypoglycemia, and by promoting assertive hyperglycemia correction. This is achieved by integrating two MPC features separately introduced by the authors previously to independently improve the control performance with respect to these two coupled issues.

View Article and Find Full Text PDF

Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.

Automatica (Oxf)

September 2016

Harvard John A. Paulson School of Engineering & Applied Sciences, Harvard University, Cambridge, MA 02138, USA.

Article Synopsis
  • - A new Model Predictive Control (MPC) method is presented for an Artificial Pancreas, designed to automatically regulate insulin delivery for people with type 1 diabetes.
  • - This enhanced MPC approach targets safe use outside of clinical settings, maintaining blood-glucose levels within a time-dependent range and adhering to strict safety constraints.
  • - The method uniquely incorporates asymmetric input costs to improve responses to high and low blood sugar levels, and its effectiveness has been validated through studies, including a clinical trial approved by the US FDA with 32 participants.
View Article and Find Full Text PDF

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

Automatica (Oxf)

January 2015

School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia ; Department of Control Science and Engineering and State Key Laboratory of Industrial Control Technology, Zhejiang University, 388 Yuhangtang Road Hangzhou, Zhejiang Province, 310058, PR China.

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication.

View Article and Find Full Text PDF

Simulation can be a very powerful tool to help decision making in many applications but exploring multiple courses of actions can be time consuming. Numerous ranking & selection (R&S) procedures have been developed to enhance the simulation efficiency of finding the best design. To further improve efficiency, one approach is to incorporate information from across the domain into a regression equation.

View Article and Find Full Text PDF

Autoregressive models of singular spectral matrices.

Automatica (Oxf)

November 2012

Research School of Information Sciences and Engineering, Australian National University, Canberra, ACT 0200, Australia ; Canberra Research Laboratory, National ICT Australia Ltd., PO Box 8001, Canberra, ACT 2601, Australia.

Article Synopsis
  • The paper focuses on autoregressive (AR) models for singular spectra, highlighting a stable AR matrix fraction description that utilizes a tall constant matrix with full column rank.
  • It introduces a canonical form for the AR model, demonstrating properties such as minimal maximum lag and a nesting feature under specific conditions.
  • Additionally, the study provides an upper limit on the number of real parameters in the canonical AR model, showing that this number increases linearly with the rows in the tall constant matrix.
View Article and Find Full Text PDF

Properties of blocked linear systems.

Automatica (Oxf)

October 2012

Research School of Information Sciences and Engineering, Australian National University, Canberra, ACT 0200, Australia.

Article Synopsis
  • This paper investigates the characteristics of blocked linear systems that emerge from blocking discrete-time linear time invariant systems.
  • It emphasizes the connection between blocked and unblocked systems, reviewing previous findings and introducing new significant results.
  • A special focus is placed on the zero properties of the blocked system, filling a gap in existing literature on the topic.
View Article and Find Full Text PDF

Many patients with diabetes experience high variability in glucose concentrations that includes prolonged hyperglycemia or hypoglycemia. Models predicting a subject's future glucose concentrations can be used for preventing such conditions by providing early alarms. This paper presents a time-series model that captures dynamical changes in the glucose metabolism.

View Article and Find Full Text PDF

We derive optimal pricing strategies for conspicuous consumption products in periods of recession. To that end, we formulate and investigate a two-stage economic optimal control problem that takes uncertainty of the recession period length and delay effects of the pricing strategy into account.This non-standard optimal control problem is difficult to solve analytically, and solutions depend on the variable model parameters.

View Article and Find Full Text PDF

On influences of global and local cues on the rate of synchronization of oscillator networks.

Automatica (Oxf)

June 2011

Department of Chemical Engineering, University of California, Santa Barbara, California 93106 USA.

Article Synopsis
  • - Synchronization of connected oscillator networks is a vital topic in various fields like biology and physics, focusing on how different cues affect this process.
  • - This research demonstrates that the strength of global cues (like external signals) primarily determines the speed of synchronization, while stronger local cues (like intercellular signals) don’t always lead to faster synchronization.
  • - The findings are validated through simulations and are applicable to both ideal scenarios and situations with noise in oscillator frequencies, without needing symmetrical interactions.
View Article and Find Full Text PDF

State Estimation and Detectability of Probabilistic Discrete Event Systems.

Automatica (Oxf)

December 2008

School of Electronics and Information Engineering, Tongji University, Shanghai, China.

A probabilistic discrete event system (PDES) is a nondeterministic discrete event system where the probabilities of nondeterministic transitions are specified. State estimation problems of PDES are more difficult than those of non-probabilistic discrete event systems. In our previous papers, we investigated state estimation problems for non-probabilistic discrete event systems.

View Article and Find Full Text PDF

Multivariable Harmonic Balance for Central Pattern Generators.

Automatica (Oxf)

December 2008

Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22904-4746, USA.

Article Synopsis
  • The central pattern generator (CPG) is a group of neurons that acts as a nonlinear oscillator, controlling rhythmic movements in animals.
  • The study explores how the structure and strength of connections between identical neurons in a CPG influence its oscillation characteristics, like frequency and amplitude, through a concept called multivariable harmonic balance.
  • A method is introduced for designing CPGs to create specific oscillation profiles, utilizing the relationship between eigenvalues and eigenvectors to predict and control the desired outcomes.
View Article and Find Full Text PDF

Towards Identification of Wiener Systems with the Least Amount of a priori Information: IIR Cases.

Automatica (Oxf)

April 2009

Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242.

In this paper, we investigate what constitutes the least amount of a priori information on the nonlinearity so that the linear part is identifiable in the non-Gaussian input case. Under the white noise input, three types of a priori information are considered including quadrant information, point information and monotonic information. In all three cases, identifiability has been established and the corresponding nonparametric identification algorithms are developed along with their convergence proofs.

View Article and Find Full Text PDF

Electrical muscle stimulation demonstrates potential for restoring functional movement and preventing muscle atrophy after spinal cord injury (SCI). Control systems used to optimize delivery of electrical stimulation protocols depend upon mathematical models of paralyzed muscle force outputs. While accurate, the Hill-Huxley-type model is very complex, making it difficult to implement for real-time control.

View Article and Find Full Text PDF