Search results for "integral"

showing 10 items of 902 documents

Design of unknown inputs proportional integral observers for TS fuzzy models

2014

In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for …

Lyapunov functionUnknown inputs reconstructionCognitive NeuroscienceLinear matrix inequalityComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy logicComputer Science ApplicationsStability conditionssymbols.namesakeDecision variablesComputer Science::Systems and ControlArtificial IntelligenceControl theoryBounded functionNorm (mathematics)Unmeasurable decision variablessymbolsTS fuzzy modelsProportional integral observer; TS fuzzy models; Unknown inputs reconstruction; Unmeasurable decision variables; Artificial Intelligence; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive NeuroscienceProportional integral observerMathematicsNeurocomputing
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On integral input-to-state stability for a feedback interconnection of parameterised discrete-time systems

2014

This paper addresses integral input-to-state stability iISS for a feedback interconnection of parameterised discrete-time systems involving two subsystems. Particularly, we give a construction for a smooth iISS Lyapunov function for the whole system from the sum of nonlinearly weighted Lyapunov functions of individual subsystems. Motivations for such a construction are given. We consider two main cases. The first one investigates iISS for the whole system when both subsystems are iISS. The second one gives iISS for the interconnected system when one of subsystems is allowed to be input-to-state stable. The approach is also valid for both discrete-time cascades and a feedback interconnection…

Lyapunov functionsmall-gain conditions0209 industrial biotechnologyInterconnectionStability (learning theory)Computer Science Applications1707 Computer Vision and Pattern Recognition02 engineering and technologyState (functional analysis)Computer Science ApplicationsWhole systems0-global asymptotic stabilityTheoretical Computer Scienceinput-to-state stabilitysymbols.namesakeparameterised discrete-time systems020901 industrial engineering & automationDiscrete time and continuous timeControl theoryControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processing0-global asymptotic stability; input-to-state stability; integral input-to-state stability; parameterised discrete-time systems; small-gain conditions; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern Recognitionintegral input-to-state stabilityMathematics
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Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

2013

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/670878 Open Access This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory…

Lyapunov stabilityPolynomialObserver (quantum physics)Article Subjectbusiness.industryApplied MathematicsMultiple integrallcsh:MathematicsChaoticlcsh:QA1-939Fuzzy logicVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Nonlinear Sciences::Chaotic DynamicsSecure communicationControl theorySynchronization (computer science)businessAnalysisMathematicsAbstract and Applied Analysis
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La gestión de casos como metodología para la conexión de los sistemas sanitario y social en España

2015

ResumenObjetivoEl objetivo de este artículo es presentar la evaluación de un proyecto de gestión de casos con pacientes crónicos en Valencia para la integración de la atención social y sanitaria. Este proyecto está vinculado con el «Modelo sociosanitario sostenible».EmplazamientoDepartamento de Salud 6, Comunidad Valenciana.ParticipantesPacientes con patologías crónicas de 65 o más años.IntervencionesEstudio comparativo con un grupo control y otro de intervención, no aleatorizado ni ciego. La intervención consistió en la creación de un equipo interdisciplinar de gestión de casos, el uso de una cartera común de recursos y su aplicación a una muestra piloto. Duración de la intervención: 6-9 m…

MaleSocial WorkCuidados de larga duraciónCase managementLong-term careHumansAtención sanitariaPacientes crónicos mayoresAgedMedicine(all)lcsh:R5-920Primary Health CareHealth careIntegrated careSocial SupportGeneral MedicineOriginalesGestión de casosElderly chronic patientsPatient SatisfactionSpainChronic DiseaseCosts and Cost AnalysisHealth ResourcesFemaleAtención integrallcsh:Medicine (General)Family PracticeAtención Primaria
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A new method for computing one-loop integrals

1994

We present a new program package for calculating one-loop Feynman integrals, based on a new method avoiding Feynman parametrization and the contraction due to Passarino and Veltman. The package is calculating one-, two- and three-point functions both algebraically and numerically to all tensor cases. This program is written as a package for Maple. An additional Mathematica version is planned later.

MapleFeynman parametrizationFeynman integralNumerical analysisElectroweak interactionFOS: Physical sciencesGeneral Physics and Astronomyengineering.materialNumerical integrationRenormalizationAlgebraHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Hardware and ArchitectureComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONComputer Science::Mathematical SoftwareengineeringContraction (operator theory)Mathematics
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oneloop 2.0 — A program package calculating one-loop integrals

1997

We present an improved version of our program package oneloop which -- written as a package for MAPLE -- solves one-loop Feynman integrals. The package is calculating one-, two- and three-point functions both algebraically and numerically to any tensor rank. In addition to the original version oneloop 2.0 also calculates infrared divergent integrals. Higher powers of propagator terms and the $O(\eps)$ parts relevant for two-loop calculations are now supported.

MaplePhysicsParticle physicsFeynman integralTensor rankFOS: Physical sciencesGeneral Physics and AstronomyPropagatorengineering.materialLoop (topology)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Hardware and ArchitectureComputer Science::Mathematical SoftwareengineeringMathematical physicsComputer Physics Communications
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Diferencialrēķini un integrālrēķini: inženierzinātņu un mehānikas fakultātes studentiem

1941

Matemātiskā analīzeIntegral calculusDifferential calculusIntegrālrēķiniDiferencēšana:MATHEMATICS::Algebra geometry and mathematical analysis::Mathematical analysis [Research Subject Categories]DiferenciālrēķiniFunkcijasDiferencialģeometrija
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Integrālie rēķini

1941

Saturs: 1. d. Nenoteiktie integrāli -- 2. d. Noteiktie integrāļi -- Pielikums: Zīmējumi

Matemātiskā analīzeIntegral calculusIntegrāliIntegrālrēķini:MATHEMATICS::Algebra geometry and mathematical analysis::Mathematical analysis [Research Subject Categories]
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Thickness Inhomogeneity Effect in EXAFS Spectroscopy

2005

In many cases x-ray absorption spectra measured in transmission mode are degraded by an inhomogeneity in thickness of the samples. As a result, the EXAFS amplitude is decreased and information about the coordination numbers is distorted. To avoid this influence, it is necessary to prepare a homogeneous sample. But, for powder samples, thick inhomogeneous foils, and sputtered films this is not possible. Absorption spectra on these samples should be corrected for the thickness inhomogeneity effect.To correct an absorption spectrum it is necessary to know the sample thickness distribution function. We propose a method of solving an integral equation for a distribution function as an inverse pr…

Materials scienceExtended X-ray absorption fine structureAbsorption spectroscopybusiness.industryCoordination numberCondensed Matter PhysicsIntegral equationMolecular physicsAtomic and Molecular Physics and OpticsSpectral lineTikhonov regularizationDistribution functionOpticsAbsorption (electromagnetic radiation)businessMathematical PhysicsPhysica Scripta
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Infrared thermography-based evaluation of the elastic-plastic J-integral to correlate fatigue crack growth data of a stainless steel

2019

Abstract The elastic-plastic J-integral is adopted to correlate fatigue crack growth data of ductile metals. An analytical link is known to exist between the J-integral and the strain energy density averaged in a control volume embracing the crack tip. On the other hand, the strain energy fluctuation is the source of temperature variations close to a fatigue crack tip of a metal material; hence the possibility to measure the J-integral from infrared thermographic scanning at the crack tip is envisaged and it is the focus of this paper. It is proposed that the elastic component of the J-integral is derived from a thermoelastic stress analysis, while the plastic component of the J-integral is…

Materials scienceFracture mechanic02 engineering and technologyIndustrial and Manufacturing EngineeringStrain energyStress (mechanics)Thermoelastic damping0203 mechanical engineeringThermoelastic Stress AnalysisGeneral Materials ScienceComposite materialFatigueJ-integralCrack tip plasticityMechanical EngineeringEnergy methodTemperatureStrain energy density functionFracture mechanicsParis' law021001 nanoscience & nanotechnologyFinite element method020303 mechanical engineering & transportsMechanics of MaterialsModeling and SimulationFracture mechanics Crack tip plasticity Thermoelastic Stress Analysis Energy methods Fatigue Temperature J-integralThermography0210 nano-technology
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