18 results match your criteria Automatica[Journal]

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Closed-form expressions and nonparametric estimation of COVID-19 infection rate.

Automatica (Oxf) 2022 Jun 2;140:110265. Epub 2022 Apr 2.

Department of Information Engineering, University of Padova, Padova, Italy.

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. Read More

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Persistence of Excitation for Identifying Switched Linear Systems.

Automatica (Oxf) 2022 Mar 7;137. Epub 2022 Jan 7.

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. Read More

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Estimating the Distribution of Random Parameters in a Diffusion Equation Forward Model for a Transdermal Alcohol Biosensor.

Automatica (Oxf) 2019 Aug 16;106:101-109. Epub 2019 May 16.

Modeling and Simulation Laboratory, Department of Mathematics, University of Southern California,

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. Read More

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Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control.

Automatica (Oxf) 2019 Feb 10;100:336-348. Epub 2018 Dec 10.

Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA.

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. Read More

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February 2019

A fully distributed traffic allocation algorithm for nonconcave utility maximization in connectionless communication networks.

Automatica (Oxf) 2019 Nov 1;109. Epub 2019 Aug 1.

The Department of Computer Science and Engineering, The University of Texas at Arlington, United States of America.

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. Read More

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November 2019

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

Automatica (Oxf) 2018 May 20;91:105-117. Epub 2018 Mar 20.

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. Read More

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

Automatica (Oxf) 2016 Sep 1;71:237-246. Epub 2016 Jun 1.

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

A novel Model Predictive Control (MPC) law for an Artificial Pancreas (AP) to automatically deliver insulin to people with type 1 diabetes is proposed. The MPC law is an enhancement of the authors' zone-MPC approach that has successfully been trialled in-clinic, and targets the safe outpatient deployment of an AP. The MPC law controls blood-glucose levels to a diurnally time-dependent zone, and enforces diurnal, hard input constraints. Read More

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September 2016

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

Automatica (Oxf) 2015 Jan;51:27-39

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. Read More

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January 2015

An Efficient Simulation Budget Allocation Method Incorporating Regression for Partitioned Domains.

Automatica (Oxf) 2014 May;50(5):1391-1400

Department of Systems Engineering and Operations Research, George Mason University, Fairfax, VA 22030.

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. Read More

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Autoregressive models of singular spectral matrices.

Automatica (Oxf) 2012 Nov;48(11):2843-2849

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.

This paper deals with autoregressive (AR) models of singular spectra, whose corresponding transfer function matrices can be expressed in a stable AR matrix fraction description [Formula: see text] with [Formula: see text] a tall constant matrix of full column rank and with the determinantal zeros of [Formula: see text] all stable, i.e. in [Formula: see text]. Read More

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November 2012

Properties of blocked linear systems.

Automatica (Oxf) 2012 Oct;48(10):2520-2525

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

This paper presents a systematic study on the properties of blocked linear systems that have resulted from blocking discrete-time linear time invariant systems. The main idea is to explore the relationship between the blocked and the unblocked systems. Existing results are reviewed and a number of important new results are derived. Read More

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October 2012

Adaptive System Identification for Estimating Future Glucose Concentrations and Hypoglycemia Alarms.

Automatica (Oxf) 2012 Aug 22;48(8):1892-1897. Epub 2012 Jun 22.

Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616-3793, USA.

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. Read More

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Numerical solution of a conspicuous consumption model with constant control delay.

Automatica (Oxf) 2011 Sep;47(9):1868-1877

Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany.

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. Read More

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September 2011

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

Automatica (Oxf) 2011 Jun;47(6):1236-1242

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

Synchronization of connected oscillator networks under global and local cues is ubiquitous in both science and engineering. Over the last few decades, enormous attention has been paid to study synchronization conditions of connected oscillators in chemistry, physics, mechanics, and particularly in biology. However, the influences of global and local cues on the rate of synchronization have not been fully studied. Read More

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State Estimation and Detectability of Probabilistic Discrete Event Systems.

Automatica (Oxf) 2008 Dec;44(12):3054-3060

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. Read More

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December 2008

Multivariable Harmonic Balance for Central Pattern Generators.

Tetsuya Iwasaki

Automatica (Oxf) 2008 Dec;44(12):3061-3069

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

The central pattern generator (CPG) is a nonlinear oscillator formed by a group of neurons, providing a fundamental control mechanism underlying rhythmic movements in animal locomotion. We consider a class of CPGs modeled by a set of interconnected identical neurons. Based on the idea of multivariable harmonic balance, we show how the oscillation profile is related to the connectivity matrix that specifies the architecture and strengths of the interconnections. Read More

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December 2008

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

Automatica (Oxf) 2009 Apr;45(4):956-964

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. Read More

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Identification of a Modified Wiener-Hammerstein System and Its Application in Electrically Stimulated Paralyzed Skeletal Muscle Modeling.

Automatica (Oxf) 2009 Mar;45(3):736-743

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

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. Read More

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