Search results for "Parameter identification"

showing 10 items of 30 documents

Least squares and genetic algorithms for parameter identification of induction motors

2001

Abstract This paper deals with off-line parameter identification of induction motors by means of least square (LS) techniques and genetic algorithms (GA), using stator voltages, stator currents and velocity as input–output data. For analytical identification by LS algorithms, filtering of experimental data is performed by means of anticausal filters. Two models useful for identification are derived in which the products of acceleration and rotor fluxes, usually neglected, are taken into account. The GA-based identification method consists of the determination of the best parameters which match input–output behaviour of the motor. Both methods are investigated and compared by means of experi…

EngineeringParameter identificationRotor (electric)Statorbusiness.industryApplied MathematicsExperimental dataLeast squareLeast squaresComputer Science Applicationslaw.inventionAccelerationIdentification (information)Stator voltageGenetic algorithmSettore ING-INF/04 - AutomaticaControl and Systems EngineeringlawControl theoryElectrical and Electronic EngineeringInduction motorbusinessInduction motor
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An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification

2019

The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…

Computer scienceSVMKNN02 engineering and technologylcsh:TechnologyIIF imageHough transformlaw.inventionlcsh:Chemistry03 medical and health scienceslawClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringPreprocessorGeneral Materials ScienceSegmentationcell segmentationlcsh:QH301-705.5InstrumentationIIF images030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesIndirect immunofluorescencelcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)ROC curvelcsh:QC1-999Computer Science ApplicationsSupport vector machineParameter identification problemFluorescence intensityHough transformlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencelcsh:Engineering (General). Civil engineering (General)businesslcsh:Physicsactive contours modelApplied Sciences
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On the numerical solution of the distributed parameter identification problem

1991

A new error estimate is derived for the numerical identification of a distributed parameter a(x) in a two point boundary value problem, for the case that the finite element method and the fit-to-data output-least-squares technique are used for the identifications. With a special weighted norm, we get a pointwise estimate. Prom the error estimate and also from the numerical tests, we find that if we decrease the mesh size, the maximum error between the identified parameter and the true parameter will increase. In order to improve the accuracy, higher order finite element spaces should be used in the approximations.

PointwiseParameter identification problemPoint boundaryNorm (mathematics)Applied mathematicsNumerical testsInverse problemMaximum errorFinite element methodMathematics
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Identification for a general class of LPV Models

2000

Abstract In this paper we consider the problem of identifying discrete-time Linear Parameter Varying (LPV) models of non-linear or time-varying systems. LPV models are considered for their connection with the industrial practice of gain-scheduling. We assume that inputs, outputs and the scheduling parameters are measured, and a form of the functional dependence of the coefficients on the parameters is known. We show how the identification problem can be reduced to a linear regression so that a Least Mean Square identification algorithm can be reformulated. Conditions on the persistency of excitation in terms of the inputs and parameter trajectories are given to ensure the consistency of the…

Parameter identification problemLeast mean squares filterGain schedulingControl theoryLinear regressionMathematicsScheduling (computing)
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Wind Shear On-Line Identification for Unmanned Aerial Systems

2014

An algorithm to perform the on line identification of the wind shear components suitable for the UAS characteristics has been implemented. The mathematical model of aircraft and wind shear in the augmented state space has been built without any restrictive assumption on the dynamic of wind shear. Due to the severe accelerations on the aircraft induced by the strong velocity variation typical of wind shear, the wind shear effects have been modeled as external forces and moments applied on the aircraft. The identification problem addressed in this work has been solved by using the Filter error method approach. An Extended Kalman Filter has been developed to propagate state. It has been tuned …

Wind shear System Identification Unmanned Aerial SystemsEngineeringbusiness.industryCovariance matrixState vectorSettore ING-IND/03 - Meccanica Del VoloFilter (signal processing)Parameter identification problemExtended Kalman filterControl theoryRobustness (computer science)Wind shearState spacePharmacology (medical)business
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A Sequential Quadratic Programming Method for Volatility Estimation in Option Pricing

2006

Our goal is to identify the volatility function in Dupire's equation from given option prices. Following an optimal control approach in a Lagrangian framework, we propose a globalized sequential quadratic programming (SQP) algorithm with a modified Hessian - to ensure that every SQP step is a descent direction - and implement a line search strategy. In each level of the SQP method a linear-quadratic optimal control problem with box constraints is solved by a primal-dual active set strategy. This guarantees L^1 constraints for the volatility, in particular assuring its positivity. The proposed algorithm is founded on a thorough first- and second-order optimality analysis. We prove the existe…

Hessian matrixMathematical optimizationLine searchComputer scienceMathematicsofComputing_NUMERICALANALYSISOptimal controlsymbols.namesakeValuation of optionsLagrange multipliersymbolsDescent directionVolatility (finance)Dupire equation parameter identification optimal control optimality conditions SQP method primal-dual active set strategySequential quadratic programming
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A Numerical Method for an Inverse Problem Arising in Two-Phase Fluid Flow Transport Through a Homogeneous Porous Medium

2019

In this paper we study the inverse problem arising in the model describing the transport of two-phase flow in porous media. We consider some physical assumptions so that the mathematical model (direct problem) is an initial boundary value problem for a parabolic degenerate equation. In the inverse problem we want to determine the coefficients (flux and diffusion functions) of the equation from a set of experimental data for the recovery response. We formulate the inverse problem as a minimization of a suitable cost function and we derive its numerical gradient by means of the sensitivity equation method. We start with the discrete formulation and, assuming that the direct problem is discret…

Parameter identification problemFinite volume methodFlow (mathematics)DiscretizationNumerical analysisConjugate gradient methodApplied mathematicsBoundary value problemInverse problemMathematics
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A linear approach for the nonlinear distributed parameter identification problem

1991

In identifying the nonlinear distributed parameters we propose an approach, which enables us to identify the nonlinear distributed parameters by just solving linear problems. In this approach we just need to identify linear parameters and then recover the nonlinear parameters from the identified linear parameters. An error estimate for the finite element approximation is derived. Numerical tests are also presented.

Parameter identification problemIdentification (information)Mathematical optimizationNonlinear systemDistributed parameter systemNonlinear parametersApplied mathematicsNumerical testsInverse problemPhysics::History of PhysicsFinite element methodMathematics
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Modeling of Wind Turbine Gearbox Mounting

2011

In this paper three bushing models are evaluated to find a best practice in modeling the mounting of wind turbine gearboxes. Parameter identification on measurements has been used to determine the bushing parameters for dynamic simulation of a gearbox including main shaft. The stiffness of the main components of the gearbox has been calculated. The torsional stiffness of the main shaft, gearbox and the mounting of the gearbox are of same order of magnitude, and eigenfrequency analysis clearly reveals that the stiffness of the gearbox mounting is of importance when modeling full wind turbine drivetrains.

EngineeringParameter identificationbusiness.industryDrivetraingearbox mountingStructural engineeringTurbinelcsh:QA75.5-76.95Computer Science ApplicationsDynamic simulationwind turbineControl and Systems EngineeringModeling and SimulationBushinglcsh:Electronic computers. Computer sciencebusinessSoftwareModeling, Identification and Control
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Vibration-based identification of mechanical properties of orthotropic arbitrarily shaped plates: Numerical and experimental assessment

2018

Abstract An innovative procedure is introduced for the identification of the mechanical parameters of orthotropic plates of arbitrary shape, under various boundary conditions, based on vibration data. The method employs a combination of a convenient Rayleigh-Ritz approach and Particle-Swarm Optimization to estimate elastic constants of the orthotropic material in a straightforward manner, without requiring computationally demanding iterative Finite Element analyses. Specifically, the pb-2 Rayleigh-Ritz procedure is extended and applied to deal with orthotropic plates, simplifying the approach to more easily treat generic plate shapes, taking advantage of the Green's theorem. The method is t…

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciMaterials sciencePb-2 Rayleigh-Ritz approachContext (language use)Ceramics and Composite02 engineering and technologyOrthotropic materialIndustrial and Manufacturing Engineering0203 mechanical engineeringVibration testMaterial parameter identificationMechanics of MaterialBoundary value problemParticle-swarm optimizationComposite materialReliability (statistics)business.industryExperimental analysiMechanical EngineeringParticle swarm optimizationExperimental dataStructural engineering021001 nanoscience & nanotechnologyFinite element methodVibration020303 mechanical engineering & transportsMechanics of MaterialsCeramics and Composites0210 nano-technologybusinessSettore ICAR/08 - Scienza Delle Costruzioni
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