Search results for "Control theory"

showing 10 items of 1333 documents

Nonfragile Gain-Scheduled Control for Discrete-Time Stochastic Systems with Randomly Occurring Sensor Saturations

2013

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/629621 Open Access This paper is devoted to tackling the control problem for a class of discrete-time stochastic systems with randomly occurring sensor saturations. The considered sensor saturation phenomenon is assumed to occur in a random way based on the time-varying Bernoulli distribution with measurable probability in real time. The aim of the paper is to design a nonfragile gain-scheduled controller with probability-dependent gains which can be achieved by solving a convex optimization problem via semidefinite programming method. Subsequen…

Semidefinite programmingMathematical optimizationArticle SubjectSaturation phenomenonApplied Mathematicslcsh:MathematicsControl (management)lcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Lyapunov functionalDiscrete time and continuous timeBernoulli distributionControl theoryConvex optimizationAnalysisMathematics
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Deconvolution filtering for nonlinear stochastic systems with randomly occurring sensor delays via probability-dependent method

2013

This paper deals with a robustH∞deconvolution filtering problem for discrete-time nonlinear stochastic systems with randomly occurring sensor delays. The delayed measurements are assumed to occur in a random way characterized by a random variable sequence following the Bernoulli distribution with time-varying probability. The purpose is to design anH∞deconvolution filter such that, for all the admissible randomly occurring sensor delays, nonlinear disturbances, and external noises, the input signal distorted by the transmission channel could be recovered to a specified extent. By utilizing the constructed Lyapunov functional relying on the time-varying probability parameters, the desired su…

SequenceArticle SubjectApplied Mathematicslcsh:Mathematicslcsh:QA1-939SignalNonlinear systemControl theoryBernoulli distributionConvex optimizationFiltering problemDeconvolutionVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Analyse: 411Random variableAnalysisMathematics
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Output Feedback Control of Discrete Impulsive Switched Systems with State Delays and Missing Measurements

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/283426 Open Access This paper is concerned with the problem of dynamic output feedback (DOF) control for a class of uncertain discrete impulsive switched systems with state delays and missing measurements. The missing measurements are modeled as a binary switch sequence specified by a conditional probability distribution. The problem addressed is to design an output feedback controller such that for all admissible uncertainties, the closed-loop system is exponentially stable in mean square sense. By using the average dwell time approach a…

SequenceArticle Subjectlcsh:MathematicsGeneral MathematicsGeneral EngineeringBinary numberConditional probability distributionlcsh:QA1-939Expression (mathematics)Dwell timeExponential stabilitylcsh:TA1-2040Control theoryState (computer science)lcsh:Engineering (General). Civil engineering (General)MathematicsMathematical Problems in Engineering
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Probability Distribution of the Residence Times in Periodically Fluctuating Metastable Systems

1998

We investigate experimentally and numerically the probability distribution of the residence times in periodically fluctuating metastable systems. The experiments are performed in a physical metastable system which is the series of a biasing resistor with a tunnel diode in parallel to a capacitor. The numerical simulations are performed in an overdamped model system with a time-dependent potential. We investigate both the cases where the system is deterministically overall-stable and overall-unstable. In the overall-unstable regime, the experimental and the numerically investigated systems show noise enhanced stability in the presence of a finite amount of noise. The determined P(T) is mult…

Series (mathematics)Applied MathematicsMechanicsStability (probability)Noise (electronics)Standard deviationsymbols.namesakeControl theoryModeling and SimulationMetastabilityTunnel diodeGaussian functionsymbolsProbability distributionEngineering (miscellaneous)MathematicsInternational Journal of Bifurcation and Chaos
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A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators

2020

Highly-compliant elastic actuators have become progressively prominent over the last years for a variety of robotic applications. With remarkable shock tolerance, elastic actuators are appropriate for robots operating in unstructured environments. In accordance with this trend, a novel elastic actuator was recently designed by our research group for Serpens, a low-cost, open-source and highly-compliant multi-purpose modular snake robot. To control the newly designed elastic actuators of Serpens, a two-feedback loops position control algorithm was proposed. The inner controller loop is implemented as a model reference adaptive controller (MRAC), while the outer control loop adopts a fuzzy pr…

Series (mathematics)Computer sciencebusiness.industryFeedback controlRoboticsLoop (topology)Computer Science::RoboticsVDP::Teknologi: 500Control theoryReinforcement learningArtificial intelligenceReinforcement learning algorithmActuatorbusiness
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Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction

2008

The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…

Series (mathematics)Degree (graph theory)Computer Science Applications1707 Computer Vision and Pattern Recognitionk-nearest neighbors algorithmTerm (time)Nonlinear systemPosition (vector)Control theorySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaComputer Science Applications1707 Computer Vision and Pattern Recognition; Cardiology and Cardiovascular MedicineTime seriesPredictabilityCardiology and Cardiovascular MedicineAlgorithmMathematics
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A correction method for dynamic analysis of linear continuous systems

2005

A method to improve the dynamic response analysis of continuous classically damped linear system is proposed. As in fact usually, following a classical approach, a reduced number of eigenfunctions are accounted for and the response is evaluated by integrating the uncoupled differential equations of motion in modal space, neglecting the contribution of high frequency modes (truncation procedure). Here, starting from the given system, it is proposed to set up two differential equations governing the motion of two new continuous systems: the first one contains only the first m non-zero eigenvalues of the given system and the second one contains the remainder non-zero infinity - m eigenvalues. …

Series (mathematics)Differential equationTruncationMechanical EngineeringLinear systemEquations of motionContinuous time systemModal analysiDynamic analysiComputer Science ApplicationsMethod of undetermined coefficientsDynamic responseControl theoryModeling and SimulationStress concentrationApplied mathematicsGeneral Materials ScienceDynamic loadDynamic methodEigenvalues and eigenvectorsCivil and Structural EngineeringMathematics
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Is Admission-Controlled Traffic Self-Similar?

2002

It is widely recognized that the maximum number of heavy-tailed flows that can be admitted to a network link, while meeting QoS targets, can be much lower than in the case of markovian flows. In fact, the superposition of heavy-tailed flows shows long range dependence (self-similarity), which has a detrimental impact on network performance. In this paper, we show that long range dependence is significantly reduced when traffic is controlled by a Measurement-Based Admission Control (MBAC) algorithm. Our results appear to suggest that MBAC is a value added tool to improve performance in the presence of self-similar traffic, rather than a mere approximation for traditional (parameter-based) ad…

Service qualitysymbols.namesakeControl theoryComputer scienceCall Admission ControlQuality of servicesymbolsRange (statistics)Markov processNetwork performanceAdmission controlSimulation
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Expert control of DO in the aerobic reactor of an activated sludge process

2000

Abstract An expert control structure is proposed for the control of dissolved oxygen (DO) in a Nitrification Denitrification Biological Excess Phosphorus Removal (NDBEPR) plant to account for the several processes that are influenced by the DO concentration in the aerator. In the scheme a supervisory fuzzy controller determines the set point of an inner DO control loop where an Adaptive Robust Generic Model Control (ARGMC) controller is used. The fuzzy supervisory control has a hierarchical structure. Off-line measurements of biological parameters of influent and effluent streams can be used to periodically update the set points of the fuzzy controllers. The complete control scheme has been…

Set (abstract data type)Activated sludgeWaste managementSupervisory controlbusiness.industryControl theoryComputer scienceControl systemProcess (computing)AerationProcess engineeringbusinessFuzzy logic
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Unknown order process emulation

2002

Approaches the emulation problem using feedforward neural networks of single input single output (SISO) processes, applying a backpropagation method with a higher convergence rate. In this kind of application, difficult problems appear when the system's order is a priori unknown. A search through the SISO processes space is proposed, aiming to find a favorable neural emulator over the training examples set.

Set (abstract data type)EmulationRate of convergenceTime delay neural networkComputer scienceControl theoryComputer Science::Neural and Evolutionary ComputationLinear systemFeedforward neural networkBackpropagationIJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)
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