Search results for "Estimation"

showing 10 items of 924 documents

Extended Kalman Filter for sensorless control of induction motors

2010

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…

State variableEngineeringbusiness.industryControl engineeringKalman filterInvariant extended Kalman filterExtended Kalman filterSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryFilter (video)Control systemFull state estimation sensorless control experimental validation.TorquebusinessInduction motor2010 First Symposium on Sensorless Control for Electrical Drives
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Space-vector State Dynamic Model of the Synchronous Reluctance Motor Considering Self, Cross-Saturation and Iron Losses

2021

This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation, cross-saturation effects, and iron losses expressed in state form, where the magnetizing current has been selected as a state variable. The proposed dynamic model is based on an original function between the stator flux and the magnetizing current components, improving a previously developed magnetic model. Additionally, the proposed model includes, besides the magnetic saturation, also iron losses. The proposed model requires 11 coefficients, among which 6 describe the self-saturation on both axes and 5 describe the cross-saturation. Starting from the definition of a…

State variablemagnetic modelComputer simulationEstimation theoryStatorFunction (mathematics)parameters' estimationMagnetic fluxlaw.inventionError functionSettore ING-INF/04 - AutomaticaControl theorylawIron lossesReciprocity (electromagnetism)space-vector dynamic modelSynchronous Reluctance Motor (SynRM)Mathematics
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A Bayesian analysis of the thermal challenge problem

2008

Abstract A major question for the application of computer models is Does the computer model adequately represent reality? Viewing the computer models as a potentially biased representation of reality, Bayarri et al. [M. Bayarri, J. Berger, R. Paulo, J. Sacks, J. Cafeo, J. Cavendish, C. Lin, J. Tu, A framework for validation of computer models, Technometrics 49 (2) (2007) 138–154] develop the simulator assessment and validation engine ( SAVE ) method as a general framework for answering this question. In this paper, we apply the SAVE method to the challenge problem which involves a thermal computer model designed for certain devices. We develop a statement of confidence that the devices mode…

Statement (computer science)Stochastic processComputer sciencebusiness.industryMechanical EngineeringBayesian probabilityComputational MechanicsGeneral Physics and AstronomyUnbiased EstimationComputer Science Applicationssymbols.namesakeMechanics of MaterialssymbolsArtificial intelligenceRepresentation (mathematics)businessGaussian processSimulationComputer Methods in Applied Mechanics and Engineering
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Linear and nonlinear experimental regimes of stochastic resonance

2000

We investigate the stochastic resonance phenomenon in a physical system based on a tunnel diode. The experimental control parameters are set to allow the control of the frequency and amplitude of the deterministic modulating signal over an interval of values spanning several orders of magnitude. We observe both a regime described by the linear response theory and the nonlinear deviation from it. In the nonlinear regime we detect saturation of the power spectral density of the output signal detected at the frequency of the modulating signal and a dip in the noise level of the same spectral density. When these effects are observed we detect a phase and frequency synchronization between the st…

Statistical Mechanics (cond-mat.stat-mech)Stochastic resonanceSpectral densitySpectral density estimationFOS: Physical sciencesSignalSynchronization (alternating current)Nonlinear systemAmplitudeOrders of magnitude (time)Control theoryStatistical physicsCondensed Matter - Statistical MechanicsMathematics
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Markov Chain Monte Carlo Methods for High Dimensional Inversion in Remote Sensing

2004

SummaryWe discuss the inversion of the gas profiles (ozone, NO3, NO2, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the ‘Global ozone monitoring of occultation of stars’ instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for…

Statistics and Probability010504 meteorology & atmospheric sciencesAttenuationInversion (meteorology)Markov chain Monte CarloDensity estimationInverse problem01 natural sciencesOccultation010104 statistics & probabilitysymbols.namesakeMetropolis–Hastings algorithmStatisticsPrior probabilitysymbols0101 mathematicsStatistics Probability and UncertaintyAlgorithm0105 earth and related environmental sciencesMathematicsJournal of the Royal Statistical Society Series B: Statistical Methodology
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Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach

2017

Summary This paper is concerned with interval estimation for the breakpoint parameter in segmented regression. We present score-type confidence intervals derived from the score statistic itself and from the recently proposed gradient statistic. Due to lack of regularity conditions of the score, non-smoothness and non-monotonicity, naive application of the score-based statistics is unfeasible and we propose to exploit the smoothed score obtained via induced smoothing. We compare our proposals with the traditional methods based on the Wald and the likelihood ratio statistics via simulations and an analysis of a real dataset: results show that the smoothed score-like statistics perform in prac…

Statistics and Probability010504 meteorology & atmospheric sciencesInterval estimationBreakpointinduced smoothingScore01 natural sciencesConfidence intervalchangepoint010104 statistics & probabilitypiecewise linear relationshipconfidence intervalscore inferenceStatistics0101 mathematicsStatistics Probability and UncertaintySegmented regressionSettore SECS-S/01 - StatisticaStatisticSmoothing0105 earth and related environmental sciencesMathematicsAustralian & New Zealand Journal of Statistics
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An association model for bivariate data with application to the anlysis of university students' success.

2015

The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible …

Statistics and Probability05 social sciencesBivariate analysisLogistic regression01 natural sciencesTerm (time)010104 statistics & probabilityGoodness of fitBivariate data0502 economics and businessStatisticsCovariateEconometricsRange (statistics)Settore SECS-S/05 - Statistica Sociale050207 economics0101 mathematicsStatistics Probability and UncertaintyAssociation (psychology)Mathematicsmodels for association students' performance bivariate ordinal response Dale's model maximum penalized likelihood estimation
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Disorder relevance for the random walk pinning model in dimension 3

2011

We study the continuous time version of the random walk pinning model, where conditioned on a continuous time random walk Y on Z^d with jump rate \rho>0, which plays the role of disorder, the law up to time t of a second independent random walk X with jump rate 1 is Gibbs transformed with weight e^{\beta L_t(X,Y)}, where L_t(X,Y) is the collision local time between X and Y up to time t. As the inverse temperature \beta varies, the model undergoes a localization-delocalization transition at some critical \beta_c>=0. A natural question is whether or not there is disorder relevance, namely whether or not \beta_c differs from the critical point \beta_c^{ann} for the annealed model. In Birkner a…

Statistics and Probability60K35 82B4482B44Probability (math.PR)Random mediaGeometryMarginal disorderFractional moment methodMean estimationMathematics::Probability60K35Local limit theoremFOS: MathematicsCollision local timeDisordered pinning modelsStatistics Probability and UncertaintyRandom walksHumanitiesRenewal processes with infinite meanMathematics - ProbabilityMathematicsAnnales de l'Institut Henri Poincaré, Probabilités et Statistiques
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A Comparison of Formulae for Calculating Cost-Efficient Sample Sizes of Case-Control Studies with an Internal Validation Scheme

2000

When a case-control study is planned to include an internal validation study, the sample size of the study and the proportion of validated observations has to be calculated. There are a variety of alternative methods to accomplish this. In this article some possible procedures will be compared in order to clarify whether considerable differences in the suggested optimal designs occur, dependent on the used method.

Statistics and ProbabilityAlternative methodsScheme (programming language)Optimal designMathematical optimizationCost efficiencyEstimation theoryComputer scienceSmall sampleGeneral MedicineSample size determinationStatisticsStatistics Probability and UncertaintyInternal validationcomputercomputer.programming_languageBiometrical Journal
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Use of functionals in linearization and composite estimation with application to two-sample survey data

2009

An important problem associated with two-sample surveys is the estimation of nonlinear functions of finite population totals such as ratios, correlation coefficients or measures of income inequality. Computation and estimation of the variance of such complex statistics are made more difficult by the existence of overlapping units. In one-sample surveys, the linearization method based on the influence function approach is a powerful tool for variance estimation. We introduce a two-sample linearization technique that can be viewed as a generalization of the one-sample influence function approach. Our technique is based on expressing the parameters of interest as multivariate functionals of fi…

Statistics and ProbabilityAnalysis of covarianceeducation.field_of_studyOptimal estimationApplied MathematicsGeneral MathematicsPopulationEstimatorVariance (accounting)Agricultural and Biological Sciences (miscellaneous)One-way analysis of varianceDelta methodLinearizationStatisticsApplied mathematicsStatistics Probability and UncertaintyGeneral Agricultural and Biological ScienceseducationB- ECONOMIE ET FINANCEMathematicsBiometrika
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